A prompt gamma camera for real-time range control in Proton Therapy

Transcription

1 POLITECNICO DI MILANO Dipartimento di Elettronica e Informazione DOTTORATO DI RICERCA IN INGEGNERIA DELL INFORMAZIONE A prompt gamma camera for real-time range control in Proton Therapy Doctoral Dissertation of: Irene PERALI Advisor: Prof. Carlo FIORINI Tutor: Prof. Angelo GERACI Supervisor of the Doctoral Program: Prof. Carlo FIORINI XXVII

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3 Thesis advisor Prof. Carlo Firoini Author Dr. Irene Perali Abstract Proton therapy is a form of radiation therapy that uses high-energy proton beams for cancer treatment. Differently from conventional radiation therapy, proton beams deliver their maximum energy within a defined range, thereby reducing adverse effects to adjacent healthy tissues. However, uncertainties in the determination of this range can impact the applied dose distribution, preventing proton therapy to exploit its maximum potential. For this reason, real-time range monitoring is highly desirable to deliver safer and more effective treatments. In the last few years, several research groups are investigating different techniques for real-time range control. Among these, prompt gamma imaging, that uses the prompt gammas emitted by target nuclei after the interaction of protons with the tissues, is a promising method for range verification during treatment. The clinical application of prompt gamma range verification has failed so far due to the absence of an optimized prompt gamma detector. The aim of this thesis is to design and develop a dedicated prompt gamma detector suitable to the clinical application. In the first chapter we introduce the primary motivation of the work, that is the need of in vivo range control. The sources of range uncertainties are identified and an overview on the different techniques for range monitoring is proposed. We finally state the advantages of prompt gamma imaging in terms of accuracy, counting statistics and possibility of actual real-time control. The second chapter is focused on prompt gamma imaging. Different approaches of several research groups are described and the latest results presented. Particular interest is given to the knife-edge slit-camera concept, proposed by IBA (Ion Beam Applications). Based on this idea, a collaboration among IBA, Politecnico di Milano and XGLab started with the aim of developing a dedicated detector suitable for the integration into the slit-camera design. The design and validation of the detector is the specific task of this thesis.

4 ii In chapter three we present a general overview about gamma-rays detection with a particular focus on scintillator-based detectors. The chapter summarizes the basic concepts useful to understand the design choices that we made during the development of the detector. The first step of the project is the experimental verification of the slitcamera concept. In chapter four we show acquired profiles using the HiCAM camera, a gamma camera developed by Politecnico di Milano for low energy gamma imaging and suitably modified for prompt gamma imaging. Even if the measurements conditions are far from the ones expected during a clinical application, these achievements prepared the ground for the design of the new detector module. Chapter five reports on the design study of the gamma detector for prompt gamma imaging in clinical conditions. Based on the required performances, we analyze the design options and objectives. Each component of the detector is then presented, with particular focus on the evaluations that led to the final configuration. The scintillator and the photo-detector properties are described, as well as the electronics and the data acquisition system, specifically designed for this application. The absolute novelty of the proposed design requires a work of characterization of each component in order to definitively establish the final configuration of the camera. In chapter six, we present the results of the detector characterization performed in Politecnico di Milano. In the first part of the chapter, we discuss on the experiments aimed at validating the slab configuration. For this purpose, a reduced-size prototype is developed and measurements with a collimated 137 Cs radiation source performed. The second part is dedicated to gamma spectroscopy measurements on the full-size camera for the calculation of the energy resolution of the system, the number of scintillation photons and a first order energy calibration. Measurements of prompt gammas during proton irradiation are presented in chapter seven. We first show acquired energy spectra with PMMA and water targets, whose characteristic lines are identified and used for a precise calibration of the system. From profiles acquisitions, we calculate the accuracy for range retrieval. We detail the influence of several parameters on the

5 performances of the camera: distance from the target, beam energy, energy window selection, target composition. The beam entrance in the target and the ability of the camera to detect range shifts are also evaluated. We then investigate the effect of inhomogeneities, by irradiating a 2D map on a target with an air cavity. The very last experiment consists in the delivery of a realistic PBS (Proton Beam Scanning) treatment to an anthropomorphic phantom. iii

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7 Acknowledgments Team work is the key-point for successful scientific research. During my Ph.D. I had been fortuned to work with an excellent group. The results would have not be possible without the continuous collaboration with the members of the team. I would like to thank IBA members involved in the project: Julien Smeets, Damien Prieels, Francois Vander Stappen, Frauke Roellinghoff and Guillaume Janssens for the simulations studies that preceded this work, for the preparation of the experimental setup for prompt gamma measurements and for the precious help in data analysis. XGLab people gave me a useful support during the design and development of the detector and particular acknowledgments go to Andrea Celani, Luca Bombelli and Roberta Peloso. I would like to thank the people that everyday work with me at Politecnico di Milano for suggestions and help on a day-by-day basis: Paolo Busca and Riccardo Quaglia are the ones who have been present since the beginning of my Ph.D. Finally, a great acknowledgement goes to Carlo Fiorini, who gave me the opportunity to work in his group, has guided me during these years and supported my ideas and decisions. I am a very lucky person.

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9 Contents Abstract Acknowledgments i v 1 Introduction Proton therapy: advantages and drawbacks Range uncertainties in proton therapy In vivo range verification Direct methods Indirect methods Conclusions and motivation of the dissertation State of the art in prompt gamma imaging Challenges and objectives in prompt gamma imaging Scanning systems and multi-slit cameras Measurement of discrete prompt gamma lines The use of ToF Compton Cameras Knife-edge slit-camera The concept Optimization of the design through simulations First experimental results Conclusions and remaining challenges in PGI Gamma-ray detectors General properties of radiation detectors Modes of operation Energy resolution Detection efficiency

10 viii Contents Dead time Scintillation detectors Gamma-ray interactions Response function Scintillators classification Light collection Photo-detectors for scintillation light read out Photomultiplier tubes and position sensitive photomultipliers Photo-diodes The silicon photo-multiplier Scintillation pulse shape analysis Energy resolution in scintillators coupled to Silicon Photomultipliers Preliminary experimental results and definition of the specifications for the new detector Measurements on a first slit camera prototype HiCam camera Experimental setup Energy calibration and data treatment to obtain prompt gamma profiles Measured profiles Definition of the specifications Setup geometry and crystal volume Count rate requirements Improvements for a new prototype Design of the new prototype Design objectives and alternatives The gamma camera architecture The scintillator Scintillator material Scintillator geometry The photo-detector Comparison among available photo-detectors Photo-detector configuration The electronics

11 Contents ix 5.6 The camera assembly Conclusion Laboratory characterization of a prototype and of the full-size detector Characterization of a reduced size prototype The 2-channels prototype Comparison between rough and polished surfaces treatments Position sensitivity Count rate performances Setup and methods Experimental results Characterization of the full-size camera The camera Gamma spectroscopy and energy resolution Light yield estimation and preliminary energy calibration Conclusions Experimental measurements of prompt gammas during proton irradiation Prompt gamma acquisitions on PMMA targets Experimental setup Measured spectra and energy calibration Data treatment for profiles acquisition Profile accuracy Profiles at different beam energies Profiles at different distances from the target Profiles with different energy windows Measurement of the beam entrance in the target Range control Comparison between measured profiles and simulations Determination of the event rate Delivery of a 2D map on targets with inhomogeneities First results toward clinical applications Experimental setup Influence of target composition

12 x Contents Acquisitions of realistic treatment delivered on an anthropomorphic phantom Conclusions Conclusions and perspectives 147 References 151

13 List of Figures 1.1 Top: comparison of photon depth dose curve (dotted line) and mono-energetic proton depth dose curve (dashed line). Bottom: influence of uncertainties to these depth dose curves [1] Typically applied range uncertainty margins in proton therapy treatment planning as currently applied in proton therapy facilities (dotted lines) and comparison between margins without (dashed line and solid line) and with (Dashed-dotted line) the use of Monte Carlo dose calculation [2] Gamma production cross sections from proton reactions with 12 C (top) and 16 O (bottom). Data from [3] Depth-dose profiles (left) and photon production profiles (right) for pencil beams of protons of different energies incident along the axis of a cylindrical water target [4] Energy spectrum of prompt gammas generated by a 16 MeV proton beam on a PMMA target [5] FLUKA simulation of the number of emitted gammas after the interaction of a mono-energetic proton beam (214 MeV) of a water phantom (4 1 1 cm 3 with respect to the gamma exit point R e. Gammas are selected at 9 ± Θ [6] Prompt gamma scanning system [7] Comparison of the depth-dose distributions measured by the ionization chamber with the PGS measurements at three different proton energies of 1, 15 and 2 MeV [7] Schematic diagram of an array-type prompt gamma detection system based on a multi-slit collimator and CsI scintillators coupled to photo-diodes [8]

14 xii List of Figures 2.4 Setup for energy and time-resolved detection of prompt gamma rays for proton range verification [9] Energy-integrated and discrete prompt-gamma ray emissions along the path of proton pencil-beams in water [9] Simulated ToF spectra of the prompt gamma photons (blue and red) and neutrons (black) for a 2 MeV proton beam [1] Setup used for prompt gamma imaging with a single-slit collimator and ToF technique [11] Comparison between a profile without (blue line) and with (green line) ToF. The red line is the difference between the two profiles[11] Configuration of the detection system for prompt gamma imaging with a Compton camera and a hodoscope [12] Concept of prompt gamma imaging with a slit camera [13] Simulated differential (left axis) and cumulative (right axis) energy spectra of photons (top) and neutrons (center) leaving the 2 cm PMMA target irradiated by a 16 MeV proton pencil beam. Bottom: simulated differential angular spectra of photons and neutrons leaving the 2 cm PMMA target irradiated by a 16 MeV proton pencil beam [13] Top: simulated detection profile of a 16 MeV pencil beam decomposed in its photon and neutron contribution. Bottom: simulated detection profile where the contribution of photons and neutrons passing through the collimator wall, through the knifeedge and through the slit opening are distinguished [4] Detection profiles measured at 1 MeV (left) and 16 MeV (right) in different positions of the target along the beam axis. The shifts of the detection profiles are estimated by fits of the experimental data with a reference 3-line segment curve simulated for the mm position [13] Accuracy of the shift retrieving method at 1 MeV (left) and 16 MeV (right) in the simulations and the measurements [13] Example of response function for a detector. For peaks whose shape is Gaussian with standard deviation σ, the FWHM is given by 2.35σ Comparison between the behaviors of a detector which follows the paralyzable model and one which follows the non-paralyzable model

15 List of Figures xiii 3.3 Observed rate as a function of the true rate for paralyzable and non-paralyzable models Gamma ray absorption characteristics for a NaI(Tl) scintillator [14] Schematic of the photoelectric absorption mechanism Schematic of the Compton scattering mechanism Example of the response function of a scintillator detector. The spectrum on the left is relative to low energy events. The spectrum on the right describes the situation for high energy events, where pair production is significative [15] Monolithic (top) and pixelated (bottom) scintillators coupled to photo-detectors. The light tracks are not realistic Conditions at the interface of dissimilar optical media. Ray 1 may escape but ray 2 will be internally reflected at the surface Photograph of typical photomultiplier tubes with difference sizes and shapes (Hamamatsu [14]) Schematic of a Photomultiplier Tube [14] Electrode structure and electron trajectories of a metal channel dynode type multi-anode photomultiplier tube [14] Schematic diagram of a SiPM, consisting of an array of microcells (photo-diode plus quenching resistor) with summed output Typical reverse I-V characteristics of a SiPM at room temperature and at 253 K. The breakdown voltage is indicated with a vertical bar [16] Dependences of the gain and the dark count rate on the temperature for a typical device [17] Schematic of SiPM readout with on a resistor Plots of the voltage pulses for the two extremes of large (green line) and small (red line) time constant. The anode current is depicted in blue Experimental setup including the cylindrical PMMA target, the tungsten slit collimator and the HiCam gamma camera Detection profiles measured with the camera centered at the expected range depth at 1 MeV, 16 MeV and 23 MeV before (left) and after (right) uncorrelated contribution subtraction. The acquisition in the three different positions of the camera are depicted with different colors

16 xiv List of Figures 4.3 Zoom on the detection profiles measured at 23 MeV as the target is moved along the beam axis to induce the detection of range shifts by the camera. A polynomial fitting was applied to the profiles to better appreciate the shifts Top view of the reference solution consisting of the target, the slit collimator and the detector in the 25:2 geometry Block detector configuration used in standard PET modules (left). Photograph of a typical block detector (right) [18] Count rate performances of General Electric PET scanners [19] Schematic of the gamma camera architecture Expected performances comparison of PWO, LYSO and BGO in terms of counting efficiency Statistical contribution of the energy resolution for PWO, LYSO and BGO Spectrum of the self-activity of LYSO provided by Saint Gobain for a 1 inches diameter by 1 long crystal [2] Crystal geometry: the scintillator consists of two rows of 2 slabs with mm 3 dimensions Left: package dimensions of a SiPM of the S1632 series. The active area with respect to the package area is highlighted in blue. Right: photon Detection Efficiency versus wavelength for Hamamatsu SiPMs [21] Number of fired microcells (left) and energy resolution (right) as a function of the energy, for different SiPMs models Photograph of a PCB where two SiPM arrays are mounted. The PCB includes also a NTC sensor for temperature monitoring SiPM array configuration and coupling to the scintillator Block diagram of the acquisition system Photograph of the PCB which includes the electronics for the acquisition of the scintillation signals. One PCB is used to read out two pixels Drawing of the assembly of the gamma camera components. In the drawing the scintillator slabs, the SiPMs arrays and all the electronic boards are shown Drawing of the configuration of the camera and the collimator for the use in clinical routine

17 List of Figures xv 5.16 Drawing of the configuration of the camera and the collimator for the use in clinical routine D sketch of the 2-channels prototype. SiPM arrays are mounted on the top-side of a PCB. On the bottom-side the front-end electronics is implemented. A Peltier cooler stabilizes the SIPMs temperature Block-scheme of the reduced-size prototype (Top). Photograph of the adopted setup for the prototype characterization Schematic of the experimental setup used for the position sensitivity characterization on the vertical axis Acquired spectra before (blue line) and after (red line) the subtraction of LYSO background. The Gaussian fitting curve is depicted in black Energy spectra obtained using crystal slabs with rough surfaces (left) and with polished surfaces (right) at different positions of the source along the height of the crystal Plot of the position of the 137 Cs photo-peak versus the position of the source along the height of the crystal. In the case of rough surfaces, the position of the peak depends on the position of the source; for polished surfaces the position of the peak is uniform Schematic of the experimental setup used for the position sensitivity characterization on the horizontal axis (a) Energy spectra of 137 Cs before and after the LYSO background subtraction. The energy range into which the events are counted is highlighted in green. (b) Point Spread Functions of the two channels. Each point corresponds to the number of totaled counts in the range of interest for each position of the source along the x-axis of the system. The ideal PSF are marked with dashed lines Illustration of the pile-up of two events. The events that occurs during the dead time of the first one extends the dead time by another period τ Experimental setup for the measurement of counting efficiency. The setup consists of a detector emulator as the input of a frontend board, which is biased by a laboratory supply unit. The board is connected to the NI sbrio which collects data and sends them to the PC

18 xvi List of Figures 6.11 Number of totaled counts in 1 s by the counter of the front-end board of the camera versus input rate (a). Counting efficiency of the counter at different input rates (b). The pulses correspond to a single energy line Left: back view of the gamma camera with the front-end and backplane boards. Right: front view of the camera with the aluminum case including the crystal slabs Crystal slabs assembly inside the aluminum box. The slabs are separated by black absorber sheets Arrays of Silicon Photomultipliers for scintillator light read out in their holder Spectrum of the self activity of LYSO acquired from one of the slab of the gamma camera Energy spectrum of 662 kev gamma rays from 137 Cs source and corresponding Gaussian fitting (Left) Energy spectrum of 1173 kev and 1335 kev gamma rays from 6 Co source and corresponding Gaussian fitting Energy spectra obtained irradiating the camera with a 137 Cs radiation source for the 4 independent channels of the camera Energy spectra obtained irradiating the camera with a 6 Co radiation source for the 4 independent channels of the camera Left: Energy resolutions FWHM of the 4 channels at the three energy lines of 137 Cs (662 kev) and 6 Co (1173 kev and 1335 kev). Right: peak positions (ADC channel) at the three energy lines measured as the centroid of the Gaussian fitting of the photo-peaks Energy calibration curve for one channel, resulting from the peaks of 137 Cs and 6 Co Top: schematic of the experimental results for prompt gamma imaging measurements. Bottom: photograph of the experimental setup for the test session at the WPE. The setup consists of a cylindrical PMMA target, a tungsten slit collimator and the gamma detector in the 25:2 configuration Detector response to gamma emissions from an activated Aluminum target. On the left the whole spectrum is shown. On the right a zoom of the spectrum around the energy peaks of interest is presented. The energy peaks are identified by red bars.114

19 List of Figures xvii 7.3 Spectra measured for 1 MeV protons without collimator and with the closed collimator for the PMMA target (left) and the water bottle target (right) Subtraction between the spectra acquired without the collimator and the spectra acquired with the collimator closed for water and PMMA targets. Measured gamma peak energies are marked with a bar Comparison between the linear energy calibration performed with 137 Cs and 6 Co radiation sources and the exponential calibration performed with energy peaks resulting from activated aluminum and irradiated water target Comparison between a profile before (blue line) and after (red line) smoothing. The profile was acquired with a beam energy of 16 MeV and with the collimator closed (left) and open (right) Detection profiles re-sampled for different number of protons Top: range retrieval precision versus the number of protons. Bottom: number of detected gammas versus the number of protons Detection profiles for therapeutic proton energies Precision for different levels of dose. The number of protons needed to achieve a 4 mm precision is marked with a red line Number of protons needed to reach a 2σ precision of 4 mm for different beam energies. For comparison to the order of magnitude of a therapeutic spots, this number was divided by Detection profiles at 1, 16 and 23 MeV for with the collimator 25 and 22 cm far from the beam axis. On the right, the shapes of the profiles are compared by rescaling the profiles acquired in the 25:2 geometry Detection profiles measured at 1 MeV with different energy windows. The red line is relative to the acquisition with the collimator open and the green line is the difference between the acquisition with the collimator open and the acquisition with the collimator closed Detection profiles measured at 16 MeV with different energy windows. The red line is relative to the acquisition with the collimator open and the green line is the difference between the acquisition with the collimator open and the acquisition with the collimator closed

20 xviii List of Figures 7.15 Detection profiles measured at 23 MeV with different energy windows. The red line is relative to the acquisition with the collimator open and the green line is the difference between the acquisition with the collimator open and the acquisition with the collimator closed Accuracy for 1, 16 and 23 MeV for 4 different energy windows Top view of the setup for the measurement of the entrance point Detected profiles centered on the entrance point in the target. A comparison with the distal fall-off acquisition is shown in red Detection profiles measured at 1 MeV, 16 MeV and 23 MeV as the target is moved along beam axis to induce the detection of range shifts by the camera Example of the shift retrieval method. The reference profile (solid blue line) is shifted along the x axis (dashed blue lines). The retrieved shift is found for the position along the x axis that minimizes the error between the acquired profile (red line) and the shifted reference profile Detection profile retrieved from the acquisition for each position of the target along the beam axis for pencil beams of 1, 16 MeV and 23 MeV Detection profiles measured with the camera centered at the expected range depth of 1 MeV, 16 MeV and 23 MeV pencil beams. On the left are shown the profiles acquired with the collimator open and closed and the respective simulation. On the right the profiles acquired with the collimator open are subtracted from the uncorrelated contribution. The simulations are scaled to fit the acquisitions Event rate recorded by a single slab as a function of the beam current at the nozzle. The beam energy was 23 MeV. On the right axis, the expected rate of events belonging to the whole spectrum is reported Event rate between 3 and 6 MeV recorded by a single slab as a function of the beam current at the nozzle at 23 MeV. Blue line indicates the measured rate and red line is the linear regression based on the first three measured points

21 List of Figures xix 7.25 Acquired profiles at different beam currents at 23 MeV. Profiles are normalized to the beam current and to the time of the acquisition. Profiles after the correction for the expected input rate at each current are depicted in red while raw profiles are represented in blue Schematic of the 49 points of the 2D map delivered on the target. The first point of the map is close to the camera and the last point is far from the camera. The section of the cavity is also reported Detail of the target used for irradiation with a 2D map. The target core was composed of 5.13 mm PMMA, 1.7 mm air cavity and PMMA up to the total length of the target Total number of counts acquired by the camera within the 3-6 MeV energy window along the time of the delivery of the 2D map. The figure on the bottom is a detail of the figure on the top: separation between spots is visible. The x-axis indicates the number of the intermediate profile of 5 µs Comparison between profiles acquired with the full target (blue) and the target with the cavity (red) in three different spots of the map. It is evident that the two spots out of the cavity are similar for the full target and the empty target, while the profile acquired with the spot in correspondence of the cavity is shifted Profiles acquired during the delivery of column of the 2D map on a target with a half cavity inside. Profiles relative to the points within the cavity are shifted with respect to the ones in the full PMMA Retrieved shift for the 49 points of the map for the target with the full cavity Retrieved shift for the 49 points of the map for the target with the half cavity Photograph of the trolley positioning system. A detail of the collimator-detector system is presented in the picture on the left Setup for profiles acquisition with a bone target Detection profiles for target with different composition for proton beams of 16 MeV. Bone, water, PMMA and fat are compared Setup for the test session. A base-of-skull treatment plan was delivered to an anthropomorphic phantom

22 xx List of Figures 7.37 Dose distribution from the base-of-skull treatment plan on the CT of the anthropomorphic phantom. Pencil beam 1 (left) and 2 (right) were selected for illustration purposes and are depicted in red lines. Their range are 8.6 and 7.7 cm, respectively Profiles corresponding to pencil beam 1 (red line) and 2 (green line) given by the sum of all counts acquired by each pair of slabs during the delivery of the corresponding pencil beam (6 gy)

23 List of Tables 1.1 Relevant positron emitter reactions in tissue from proton therapy Gamma ray lines from proton reactions with 12 C and 16 O. Data from [3] Simulated count rates per second per 1 cm 3 LYSO crystal above various hardware thresholds at maximum beam current as a function of the beam energy. Data taken from [4] Expected count rates per second per a 5 cm 3 scintillator above various hardware thresholds at maximum beam current as a function of the beam energy Physical properties of various inorganic scintillators under consideration in the present section Comparison of the most common photo-detectors for scintillation counting Gamma Emissions of 22 Na Energy and interpretation of the peaks in the spectrum at 1 MeV without collimator (based on Kozlovsky) Projected range in PMMA for therapeutic proton energies. Data taken from [22] Elemental compositions of PMMA, water and various standard human tissue from ICRU ([23]) Energy layers with the corresponding number of spots and interaction depth in water for the base-of-skull treatment

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25 Chapter 1 Introduction In the first chapter we introduce the problem of range uncertainty in proton therapy, that is the motivation of this thesis. We first present the sources of uncertainty and how they are currently managed during treatment, highlighting that in vivo range control is highly desirable to deliver safer treatments. For this reason, range control in proton therapy is a hot topic in medical physics and several research groups are investigating different techniques for beam monitoring. A brief overview on the various methods under investigation is given. We categorize the different approaches on the basis of the measurement technique into direct methods and indirect methods. The current status from the point of view of clinical implementation, together with potential and further directions of the different approaches are discussed.

26 2 Introduction 1.1 Proton therapy: advantages and drawbacks Standard radiation therapy has evolved and improved over the years and it is effective in controlling many cancers. However, X-ray beams deposit their energy along the path of the beam, to the targeted tumor and beyond, and deliver radiation to healthy tissues before and after the tumor site. An ideal radiotherapy treatment would deliver a dose distribution precisely localized to the tumor target, without affecting the surrounding healthy tissues. The use of protons in radiotherapy benefits of their physical selectivity due to the lower deposited energy in the entrance of the target volume and steeper increase and fall-off toward the end of their range in the Bragg peak [24]. Figure 1.1 (Top) shows the potential dose benefit of a proton treatment compared to a photon treatment. In most treatments, protons of different energies with Bragg peaks at different depths are applied to treat the entire tumor. The total radiation dosage of the protons is called the Spread-Out Bragg Peak (SOBP). In the figure it is evident that, in principle, the SOBP can cover the whole tumor sparing the normal tissues [1]. However, due to the steep dose gradient at the distal edge of the Bragg peak, uncertainties in determination of this range can have a profound impact on the actually applied dose distribution. Figure 1.1 (bottom) compares the expected changes in the delivered doses of a photon (left) and proton (right) field in the case that a density heterogeneity in the beam path would be ignored in the treatment planning process. In the case of photons, this results in a reduced dose beyond the heterogeneity of only a few percent. For the proton SOBP field, the same error in calculation could result in changes of doses of up to 1%. This uncertainty is the main factor limiting the efficiency of proton therapy over conventional radiation therapy. In order to fully use the potential advantage when using protons, the range of proton beams in patients needs to be predicted as accurate as possible in the treatment planning and delivery process. In vivo proton range verification is extremely desirable to improve even more the precision of the therapy. Spurred on by this desire, over the last years, many different approaches for in vivo range control have been proposed and investigated [1]. 1.2 Range uncertainties in proton therapy The range of protons needs to be defined for a SOBP, because, due to range straggling, not all protons of the same energy have the same range. Ideally the

27 1.2 Range uncertainties in proton therapy 3 Figure 1.1 Top: comparison of photon depth dose curve (dotted line) and monoenergetic proton depth dose curve (dashed line). Bottom: influence of uncertainties to these depth dose curves [1]. range would be defined at the position where the dose has decreased to 8% of the maximum dose, i.e. in the distal fall-off. The 8% fall-off positions indeed coincides with the range at which 5% of the protons have stopped. Nevertheless, in most proton therapy facilities, the prescribed range is defined at the 9% fall-off position in water because of historic reasons [2]. Uncertainties in proton range can be categorized in: Systematic: a treatment plan is based on a single computed tomography (CT) acquisition. CT data sets could have systematic errors that reflect on the accuracy of dose delivery. These kinds of uncertainties will likely to be the same for every delivered fraction of a treatment. Random: they include uncertainties that could change on a day-to-day basis and thus are unpredictable. Systematic sources of uncertainties in range are calculations inherent to the limitations of CT image acquisitions, on the basis of treatment planning. CT numbers are expressed in Hounsfield units (HU), which give the relative x-rays attenuation of the tissue in relation to water. Before proton ranges can

28 4 Introduction be calculated for treatment planning, HU must be first converted to relative proton stopping powers, which describe the protons energy loss in the tissue due to Coulomb interactions. Calibration curves are generated with the use of sophisticated algorithms, but inevitable uncertainties are associated with this curves, notably the problem that the actual conversion is dependent on the chemical composition of the material [25]. Errors due to this conversion alone have been estimated at 1.1% for soft tissues and 1.8% in bone [26]. In addition, there is an uncertainty in the relative biological effectiveness (RBE). Proton therapy uses a generic value for the RBE to relate prescribed proton doses to photon doses. This uncertainty corresponds to an uncertainty in biological range of a few mm [27]. Going to the random sources of uncertainty, the most important is the patient mis-positioning in relation to the beam. Range uncertainties arising from positioning errors can be quite substantial, particularly when treating through areas of large density heterogeneities and patient surfaces that are oblique to the beam direction. Organ motion, breathing is the most obvious example, is another not negligible source of uncertainty. Finally, it must be taken into account that a conventional treatment takes place over a long period (typically many weeks). Over such a timescale, patient anatomy can change significantly due to weight loss or gain, daily changes in the filling of internal cavities and also the tumor mass reduction. The current approach to manage range uncertainty in proton therapy is a robust treatment planning. The objective of treatment planning is to find the optimal dose distribution in terms of dose conformity, healthy tissue sparing and robustness toward uncertainties. Most current commercial planning systems are based on analytical pencil-beam dose calculations. The guidelines include a generic margin recipe, that depends on the proton therapy facility and on the specific treatment scenarios [2]. The applied range uncertainty margins in proton therapy treatment planning at Massachusetts General Hospital (3.5% of the prescribed range + 1 mm), MD Anderson Proton Therapy Center in Houston (3.5% + 3 mm), the Loma Linda University Medical Center (3.5% + 3 mm), the Roberts Proton Therapy Center at the University of Pennsylvania (3.5% + 3 mm) and the University of Florida Proton Therapy Institute (2.5% mm) are displayed in figure 1.2. The figure also reports on the achievable improvements that can be gained with the use of Monte Carlo simulations. A significant impact of Monte Carlo dose calculation, instead of analytical calculation, can be expected in complex geometries. Analytical dose calculation algorithms typically project the range based on water equivalent depth in the

29 1.3 In vivo range verification 5 Figure 1.2 Typically applied range uncertainty margins in proton therapy treatment planning as currently applied in proton therapy facilities (dotted lines) and comparison between margins without (dashed line and solid line) and with (Dashed-dotted line) the use of Monte Carlo dose calculation [2]. patient neglecting the position of inhomogeneities relative to the Bragg peak depth. Consequently, analytical algorithms are not able to correctly predict the effect of range degradation caused by multiple Coulomb scattering, which occurs in complex geometries. The dashed line and the solid line are the estimated uncertainty without the use of Monte Carlo dose calculation for simple and complex geometry, respectively. The dashed-dotted line is the estimated uncertainty with the use of Monte Carlo simulations. Even if simulations could be a powerful tool to reduce safety margins in the treatment, there will always be the need to monitor and verify the delivered treatment in the patient with in vivo proton range verification. 1.3 In vivo range verification This paragraph summarizes the methods for in vivo range verification in proton therapy according to a recent review article [1]. In vivo range verification can be performed with different approaches. Different categorizations can be applied, based on the measurement technique, the timing (On-line and Off-line) or the dimension (1D, 2D or 3D). We will focus on the first kind of classification, i.e. the distinction between direct methods, which measure proton range by direct dose measurements and indirect

30 6 Introduction approaches, which imply particle range from secondary signals resulting from the proton irradiation Direct methods Direct methods include the use of implantable markers, range probes and proton radiography to obtain a direct measurement of the dose. Point dose measurements use an implantable dosimeter with a wireless readout to measure the point dose in the target volume. Range determination from the point dose measurement is based on the fact that the time dependence of a delivered SOBP is unique at every point in depth and thus encodes the depth information [28]. This approach was first tested using a small ionization chamber (IC) and then with semiconductor diodes [29]. For both detector types, it was shown that the root mean square of the dose burst provides submillimeter precision for determination of the proton range at a specific position in a water phantom. The use of implantable dosimeters makes range verification during the delivery of each field possible and does not require additional time for the patient. An obvious limitation of this approach is the fact that it can only verify the range at a limited number of points, that would not be sufficient for treatment sites that require range verifications at a finer resolution. Tissue inhomogeneities can also distort the dose distribution through multiple scattering and degradation of the distal edge dose fall-off. Another drawback is the fact that the dosimeters must be inserted inside the target volume: the implantation of markers may not be possible for many tumor types, thus limiting the applicability of this approach. In vivo implanted markers provide a 1D range signal measured at a limited number of points within the patient. An alternative 1D range measurement that avoids the use of implantable dosimeters directly in the patient, is the concept of range probe. The range probe approach consists in the application of a single proton pencil beam of sufficient energy to pass completely through the patient and the measurement of its residual range on its exit from the patient [3]. The main advantage of this technique is that by using a multiple layer ionization chamber (MLIC) the complete Bragg peak can be measured, including potentially a high-resolution measurement of the distal gradient. In addition, only plateau dose is delivered in the patient, meaning that doses delivered from such range probes can be very low. This approach is relatively simple and required only a MLIC as a detector,

31 1.3 In vivo range verification 7 which is available commercially. The main disadvantages are the requirement for higher energy protons (higher than 23 MeV), poor spatial resolution and the fact that only the total range change through the whole patient can be measured, and not the range directly at the tumor position. The third direct technique is proton radiography, which has been investigated since the late 196s, and is the 2D extension of the range probe concept. Differently from the range probe approach, in proton radiography, a 2D fluence of protons is used and the entrance and exit coordinate of each proton is detected in coincidence with the range measurement [31]. The main advantage of proton radiography is that it directly provides stopping power values of the tissues, which are the basis for treatment planning in proton therapy and it can thus be used both for planning and verification that the treatment plan is in accordance with the actual body composition [32]. The main disadvantage of proton radiography is the limited spatial resolution. This limitation is due to the multiple Coulomb scattering. Protons undergo numerous small angle deflections caused by their interaction with the Coulomb field of the nuclei in the traversed material, which produces uncertainties in the reconstructed proton trajectory [31] Indirect methods Indirect methods imply particle range from surrogate signals resulting from the proton irradiation. They can be divided in prompt gamma imaging (PGI), PET imaging and MRI imaging. The two first are related to the fact that, while passing through tissue, protons undergo nuclear reactions, some of which result in the emission of gammas [7],[6]: coincident 511 kev gammas from the positron annihilation following the decay of the positron emitters produced in beam interactions with the body prompt gammas from excitations of the target nuclei Both secondary emissions can be exploited for range verification. Differently from the former methods, MRI imaging can be applied only after the treatment, because it images the changes in the constitution of tissue, after exposure to radiations.

32 8 Introduction Table 1.1 Relevant positron emitter reactions in tissue from proton therapy. Reaction Threshold energy Half life Positron energy [MeV] [min] [MeV] 16 O(p, pn) 15 O O(p, α) 13 N N(p, pn) 13 N C(p, pn) 11 C N(p, α) 11 C O(p, αpn) 11 C PET imaging Range verification through in vivo PET imaging makes use of coincident gammas resulting from the annihilation of emitted positrons with electrons. When traversing tissue, a small fraction of protons create positron emitting isotopes ( 11 C, 13 N and 15 O) through nuclear interactions. The β + -decay of these isotopes results in two coincident gammas that can be observed with a PET camera [33]. Table 1.1 shows the main isotopes produced by inelastic collisions of protons in tissue [34]. Clinically, this approach is appealing because it provides in vivo range information without additional dose cost for the patient. For proton irradiation, β + -activation results from induced target activation, which depends on the elemental composition of the underlying irradiated tissue [35]. The relation between the induced activity distribution and the dose distribution is not straightforward, due to its strong dependence on the elemental composition: the same dose distribution delivered to different inhomogeneous tissue geometries will result in different activity distributions. Due to the delayed annihilation signal, PET method is not actually a realtime method. For this reason, a critical aspect in range verification with PET is the washout problem which happens in perfused tissues, where the activity signal also changes over time [36],[37]. All these factors prevent a direct range verification by simply comparing dose and activity profiles and a comparison of measured activity distribution with a modeled activity distribution is required. For the range verification in patients, two approaches has been investigating: Monte Carlo (MC) simulations and the use of filtering functions. One limiting factor of MC simulations is the underlying cross-sectional data: more experimental data is needed to reduce the uncertainties below 1 mm [2]. The second approach consists in the convolution of the planned dose distribution

33 1.3 In vivo range verification 9 with filter functions [38], that allows the prediction of the distal fall-off region of the PET signal. PET imaging can be performed either on line (during the actual irradiation with protons) or off line (after the treatment is completed). While for on line imaging all β + isotopes contribute to the measured activity distribution, off line images predominantly show activity from radioisotopes whose half-life is comparable to the transportation time, and is mainly restricted to 11 C (see table 1.1). The yield of 11 C is small, due to the rarity of target elements in human tissues. The main advantage of off line imaging is that commercial, full-ring PET can be used with a sufficient reproducibility, consistency and sensitivity [39]. On line approaches have several advantages over off line approaches. First, no repositioning of the patient is necessary and, in principle, on-line corrections of the treatment would be possible. However, in order to gain enough statistics, imaging times of some minutes have to be considered and this compromises the patient throughput. The integration of PET imaging into the treatment room poses geometric constraints because of the need of an opening for the beam portal and typically results in a dual-head configuration [4]. In vivo PET range verification has moved from a research tool to clinical implementation. For head-and-neck patients, it has been stated that the beam range can be verified with an accuracy of 1 2 mm in well-co-registered bony structures [36]. In summary, PET imaging can be performed both during treatment and after the treatment, but, in order to achieve a sufficient signal-to-noise ratio, only after the delivery of each treatment field. One of the major advantages of this approach is that, if used in the off-line mode, commercial PET scanners can be employed. Anyway, research groups that are investigating PET imaging for real-time control can take advantage of the great know-how grown in the last decades on the development of PET detectors and reconstruction methods. Prompt gamma imaging Inelastic interactions of protons and target nuclei occur along almost the whole proton penetration path, until 2 3 mm before the Bragg-peak, where the reaction cross sections start dropping with decreasing energy of the projectiles. After an interaction, the target nucleus is excited to a higher energy state and then emits a gamma cascade to return to its ground state [6]. Thus, the emission of prompt gammas is correlated with the penetration path of the

34 1 Introduction Table 1.2 [3]. Gamma ray lines from proton reactions with 12 C and 16 O. Data from Energy [MeV] Transition Reaction Mean life [s] B.718 g.s. 12 C(p,x) 1 B C(p,x)1C(ϵ) 1 B O(p,x) 1 B B B C(p,x) 1 B O(p,x) 1 B N N O(p,x) 14 N C 2. g.s. 12 C(p,x) 11 C B g.s. 12 C(p,x) 11 B N g.s. 16 O(p,x) 14 N O O O(p,p ) 16 O C g.s. 16 O(p,x) 13 C C g.s. 16 O(p,x) 13 C C g.s. 12 C(p,p ) 12 C O(p,x) 12 C B g.s. 12 C(p,2p) 11 B N 5.16 g.s. 16 O(p,x) 14 N O g.s. 16 O(p,x) 15 O < O g.s. 16 O(p,x) 15 O N 5.27 g.s. 16 O(p,x) 15 N N g.s. 16 O(p,x) 15 N O 6.13 g.s. 16 O(p,p ) 16 O O g.s. 16 O(p,x) 15 O < N g.s. 16 O(p,x) 15 N C g.s. 12 C(p,x) 11 C < C g.s. 12 C(p,x) 11 C < B g.s. 12 C(p,x) 11 B B g.s. 12 C(p,x) 11 B O g.s. 16 O(p,p ) 16 O O g.s. 16 O(p,p ) 16 O N 7.31 g.s. 16 O(p,x) 15 N C g.s. 12 C(p,p ) 12 C

35 1.3 In vivo range verification 11 Figure 1.3 Gamma production cross sections from proton reactions with 12 C (top) and 16 O (bottom). Data from [3]. protons in the tissue, so that measurements of the prompt gammas can be used to draw conclusions on the proton range. The correlation is illustrated in figure 1.4, where the depth-dose profiles (on the left) and photon production profiles (on the right) are plotted for pencil beams of protons of different energies. The emission spectrum (see figure 1.5) of the prompt gammas is in the range of 1 15 MeV and is dominated by a number of discrete gamma-lines from specific nuclear de-excitations. Gamma ray lines from proton reactions with 12 C and 16 O are presented in table 1.2 and their cross sections are plotted in figure 1.3 (data taken from [3]). The correlation between the Bragg peak fall-off and prompt gammas was first observed with Monte Carlo simulations [6] and then verified with experimental results [7],[13],[9],[11], that will be discussed in the next chapter. The decreased prompt gamma activity in proximity of the Bragg peak fall-off, once

36 12 Introduction Figure 1.4 Depth-dose profiles (left) and photon production profiles (right) for pencil beams of protons of different energies incident along the axis of a cylindrical water target [4]. Figure 1.5 Energy spectrum of prompt gammas generated by a 16 MeV proton beam on a PMMA target [5]. an angular cut is applied, is visible in figure 1.6, where mono-energetic beams are applied to a water phantom. The main advantage of prompt gamma imaging is the ability to perform real-time verification of proton dose delivery. The isotropic prompt gammas can be detected instantly, within a few nanoseconds, following the nuclear interactions. Even the application of a therapeutic dose of 2 Gy/min results in a sufficiently high production rate of gammas. With a beam of 1 8 protons,

37 1.3 In vivo range verification 13 Figure 1.6 FLUKA simulation of the number of emitted gammas after the interaction of a mono-energetic proton beam (214 MeV) of a water phantom (4 1 1 cm 3 with respect to the gamma exit point R e. Gammas are selected at 9 ± Θ [6]. which is a reasonable order of magnitude of protons delivered in a single spot, about PG rays are produced [41]. For this reason, prompt gamma imaging enables treatment monitoring without additional dose. Differently from PET imaging, standard SPECT modules cannot be used because they are usually designed to work in an energy range up to 1 MeV and with count rates lower than the one expected from prompt gamma imaging. MRI imaging Radiation can cause changes in the constitution of human tissues which can be visible by MRI imaging. One example is bone marrow, where within 1 2 weeks an increase in MR signal intensity in T2-weighted and STIR images can be observed [42]. Such MRI-visible changes in tissue thus provide the opportunity to observe delivered dose distributions in vivo. A visual inspection of the MRI images alone is not sufficient to verify proton range [43], because the location of the greatest signal intensity (SI) gradient does not exactly correspond to the delivered dose gradient. Considering the lateral dose fall-off, a dose-response curve

38 14 Introduction for radiation-induced fatty marrow conversion has to be established. The strength of the MRI method includes its high spatial resolution, lack of additional ionizing radiation exposure and the availability of MRI scanners. Its main weakness is its reliance on a ground truth dose-si relationship. However, the use of MRI imaging for in vivo range verification is still in its first phase. 1.4 Conclusions and motivation of the dissertation Protons are an interesting modality for radiotherapy because of their welldefined range and favorable depth dose characteristic. These same characteristics lead to uncertainties in their delivery. The full potential of particle therapy will only be exploitable when it will be possible to precisely monitor and control range uncertainties in vivo. For this purpose, different techniques have been investigated. Implanted markers, range probes and proton radiography are based on the direct measurement of the proton range. Sub-millimeter precision was obtained with implantable markers on phantoms, but it has to be confirmed in clinical studies on patients. The range probe approach is simple and commercially available, but it has a poor spatial resolution. Proton radiography is the most direct way of obtaining range verification information but it is currently not being used clinically. Indirect methods such as prompt gamma imaging, PET imaging and MRI imaging can rely on the wide knowledge and research developments in medical imaging. MRI imaging can have a very high spatial resolution and therefore accuracy in prediction and commercially available MRI scanner can be used. Conclusive MRI imaging for proton range verification is expected to be possible from the eight day past radiotherapy, so real-time range control in not feasible. PET imaging can be performed both on line and off line. The substantial difference between the two measurements is that off line acquisition can be performed with standard PET scanners while for on line imaging facility-specific detector solutions are required. Verification accuracy of 5 1 mm is reasonable, depending on the tumor location, the tissue characteristics of the target area and the data acquisition approach. A comparison between PET and PGI in terms of clinical adaptation is presented in a review paper [44]. Prompt gamma imaging has several advantages over PET imaging: Sub-millimeter accuracy is potentially achievable [41].

39 1.4 Conclusions and motivation of the dissertation 15 High counting statistics would allow range control without additional dose to the patient. Actual real-time control can be performed due to the emission of prompt gammas within few nanoseconds [1]. For these reasons we believe in the effectiveness and potential introduction of this technique in clinical routine. Nowadays no detector solutions are available to perform PGI in clinical conditions. The motivation of this dissertation is to give a concrete demonstration of the use of prompt gamma imaging by the design, development and test of a dedicated gamma detector. The main objectives are: Experimental proof of concept of PGI with a slit camera up to 23 MeV, not necessarily in clinical conditions and without an engineered prototype. Design of a new detector, including the required electronics and data acquisition system, which satisfies the requested specifications for the use during the delivery of realistic treatments. Development and characterization of the detector. Prompt gamma imaging in clinical conditions on homogeneous and heterogeneous targets to evaluate the performance of the detector in a slitcamera system. Delivery of a realistic treatment on an anthropomorphic phantom and test of the capability of the slit camera to verify the treatment.

40 16 Introduction

41 Chapter 2 State of the art in prompt gamma imaging This second chapter is dedicated to the presentation of the state-of-the-art in prompt gamma imaging, which is one of the most promising indirect methods for range control in proton therapy. Throughout a review of different techniques proposed in literature, we analyze advantages and drawbacks of each method, as well as its status. Finally, the slit camera concept, which constitutes the basis of this work of thesis, is presented in detail. We conclude with the list of the remaining challenges of PGI, which are the questions that we aim at answering with this work.

42 18 State of the art in prompt gamma imaging 2.1 Challenges and objectives in prompt gamma imaging As discussed in the first chapter, the clinical application of PGI is more challenging with respect to PET imaging due to the absence of an optimized prompt gamma detector. Conventional single photon computed tomography (SPECT) is not feasible because of the high energy (up to 1 MeV) of the prompt gamma emission spectrum. Hence, various alternative approaches are being pursued. The objective in PGI is to detect prompt gammas emitted along the proton tracks to measure the penetration depth inside the patient. As the incident proton beam axis is a priori well known, the camera has to supply information on the interaction coordinates of the emitted gammas with the detector and on their incident direction. These two pieces of information are essential to reconstruct the emission point of prompt gammas. The information on the interaction coordinates requires a position sensitive detector. As we will see in section 3.2, scintillator detectors are suitable for the imaging of gamma rays. Both monolithic crystals with a center of gravity approach and pixelated structures can be taken into consideration. Concerning the incident direction, two solutions are available. The simplest solution is to select gammas with a collimator. A more sophisticated technique is to detect prompt gammas in a specific detection system by causing a Compton scattering in a first layer of the detector, and then by detecting the scattered photon and/or the electron set in motion in additional layers of the detection system. We can then use balance equations to deduce potential incident directions of the prompt gammas. The interaction coordinates and the incident direction are necessary to retrieve the gamma emission point and therefore the penetration depth of the beam. However, as we report in section 2.6, not only photons correlated with the range escape the patient and reach the camera. The photon fluence is also composed of uncorrelated photons that were scattered in the patient, or emitted by secondary particles inside the patient. A huge background of uncorrelated neutrons is also incident on the camera and different techniques can be implemented to minimize this contribution. These techniques are based on the different physical properties of neutrons with respect to gammas. These differences have impact on the measured signal and allow the discrimination of the two types of particles. The first important dissimilarity regards the energy spectrum. Neutrons have a wide continuous energy spectrum, from the incident proton beam energy down to the thermal

43 2.2 Scanning systems and multi-slit cameras 19 energy. On the other hand, prompt gammas correlated with the range have energies between 1 and 8 MeV. Energy discrimination is essential to isolate the prompt gamma contribution from the dominant background of uncorrelated events. Timing is the second important property that differentiates neutrons and photons. Photons travel from their emission point to the camera at the speed of light; neutrons are slower. If photons cover a 3 cm distance in 1. ns, neutrons cover the same distance in 6.9 ns at 1 MeV and 21.7 ns at 1 MeV. With a fast scintillator and a dedicated electronics with implemented time of flight (ToF) option, we can select events that are detected within a specific time window corresponding to the photons only. This requires information on the time structure of the proton beam to determine when the incident protons hit the patient. For this purpose either the RF signal from the cyclotron or a specific detector crossed by the protons just before they hit the patient can be used. Based on these considerations about the physical properties of the emitted particles after the interaction of proton beams with the patient, different research groups have been investigating different solutions. An overview is given in the next paragraphs. 2.2 Scanning systems and multi-slit cameras The first experimental results of prompt gamma imaging were obtained using a scanning system whose setup is depicted in figure 2.1 [7]. The setup is based on the principle that the range can be determined by counting the gammas emitted from the 9 of the beam direction. The design of the collimator was chosen to suppress fast neutrons and to select gammas passing only the collimation hole. The prompt gamma scanner (PGS) consists of three layers of shielding against neutrons generated from the phantom. The gamma detector is a CsI(Tl) scintillator whose dimensions were determined to match with the collimator hole. The scintillation light is collected by a photomultiplier tube. With this setup, millimeter correlation of prompt gamma peaks to the Bragg peaks was obtained as shown in figure 2.2. These first results revealed that the prompt gammas can be used to verify the proton range in proton therapy, but the use of a scanning system is not practical for clinical use. The acquisition of the full FoV is not possible during a single measurement, but the detection system must be moved in different positions. During treatment delivery, there would not be time to scan the

44 2 State of the art in prompt gamma imaging Figure 2.1 Prompt gamma scanning system [7]. Figure 2.2 Comparison of the depth-dose distributions measured by the ionization chamber with the PGS measurements at three different proton energies of 1, 15 and 2 MeV [7]. patient to see the fall off of the prompt gamma profile. To overcome the difficult application of scanning systems in clinical routine, the use of position sensitive cameras was investigated. One of the proposed solution is the use of an array-type measurement system, incorporating a linear array of scintillator detectors and a multi-slit collimation system [8]. The principle of array-type prompt gamma measurement system is simple. Multiple scintillation detectors count prompt gammas 9 emitted from the proton pas-

45 2.3 Measurement of discrete prompt gamma lines 21 Figure 2.3 Schematic diagram of an array-type prompt gamma detection system based on a multi-slit collimator and CsI scintillators coupled to photo-diodes [8]. sage through their respective collimation slits and then a multichannel data acquisition (DAQ) system analyzes the measured gamma distribution from each detector to determine the distal dose edge. A possible multi-slit configuration is presented in figure 2.3. The prompt gamma detection system is composed of a collimator with 4 mm-wide collimation slits, each separated by a 6 mm-thick lead shield and an array of CsI(Tl) scintillators coupled to photo-diodes. When using a multi-slit camera system, the acquired profile is a direct onedimensional projection of the emission profile along the beam path. To obtain the range, there are two positions that need to be measured: the projection of the point where the beam enters into the patient and the location of the Bragg peak. The advantages of a multi-slit design is that a multi-slit camera can be made large enough for the field of view to encompass both positions and both correspond to sharp edges in the prompt-gamma profile that can be identified. Due to the direct projection, there is no parallax effect. Although the multi-slit camera is a potential candidate for prompt gamma imaging, no experimental results have been reached yet. 2.3 Measurement of discrete prompt gamma lines A further technique for range determination consists in measuring discrete prompt gamma lines. Measured spectra revealed that the total PG emission

46 22 State of the art in prompt gamma imaging Figure 2.4 Setup for energy and time-resolved detection of prompt gamma rays for proton range verification [9]. from 12 C (4.44 MeV) and 16 O (6.14 MeV) per incident proton and per Gray of absorbed dose depends on the concentration of carbon and oxygen in the target [45]. Identifying discrete gamma lines, attributed to specific nuclear level transitions, can provide several benefits to improve the accuracy and sensitivity of range verification. First, each of these discrete gamma emissions has a unique correlation to the proton energy, and nuclear reaction cross sections may be used as prior knowledge in the range verification. Second, using the prompt gamma-ray production cross sections, the concentrations of target nuclei for the proton-induced reactions in the irradiated tissue may be estimated based on the specific gamma emissions, which can make range verification more robust if the proton beam stops in tissue with an uncertain composition. Range verification using this technique has been successfully performed with the setup presented in figure 2.4 [9]. The detector consists of a cylindrical LaBr 3 scintillator coupled to a photomultiplier tube (PMT). Four optically separated BGO crystals surrounding the primary detector act as an inactive shield to reduce both the Compton background and the neutron-induced gamma-ray background. A digital data acquisition system is used to acquire data at high count rates. A slit collimator is used to collimate the prompt gamma-rays and the magnitudes of discrete gamma lines at 4.44, 5.2 and 6.13 MeV are quantified for 27 positions along the path of proton beams. A clear correlation of the prompt gamma-ray emission with the proton depth-dose curve can be observed in figure 2.5. This technique is suitable for clinical use, but improvements in detector design and larger-scale prototypes are needed for the use in clinical routine.

47 2.4 The use of ToF 23 Figure 2.5 Energy-integrated and discrete prompt-gamma ray emissions along the path of proton pencil-beams in water [9]. Figure 2.6 Simulated ToF spectra of the prompt gamma photons (blue and red) and neutrons (black) for a 2 MeV proton beam [1]. 2.4 The use of ToF As already stated at the beginning of this chapter, one of the main challenges of prompt-gamma imaging is the presence of an important contribution not correlated with the range. This concept was proven by simulations and an example of simulated prompt gamma ToF spectrum is presented in figure 2.6 [1]. The prompt gamma ToF spectrum appears to form a relatively narrow peak that occurs earlier than the maximum of the much broader neutron ToF spectrum. ToF has been applied experimentally for proton beams using a single-slit

48 24 State of the art in prompt gamma imaging Figure 2.7 Setup used for prompt gamma imaging with a single-slit collimator and ToF technique [11]. Figure 2.8 Comparison between a profile without (blue line) and with (green line) ToF. The red line is the difference between the two profiles[11]. camera as depicted in figure 2.7 [11]. The setup consists of a tungsten collimator with a single parallel-edge slit. Prompt gammas are detected with a LYSO scintillator detector and, in order to acquire an image of the whole promptgamma emission profile with the single-slit collimator, the target was moved along the beam axis incrementally. For ToF discrimination, the hit in the detector was used as a start signal and the frequency signal of the cyclotron was used as stop signal, so that the arrival time of the particle is measured in relation to the proton bunches. In figure 2.8, it is evident that applying a TOF discrimination reduces the

49 2.5 Compton Cameras 25 background significantly, while leaving the falloff signal amplitude intact and it thus represent a powerful option to include in a prompt gamma camera design. The only drawback is that it adds a degree of complexity to the design and requires additional data elaboration. 2.5 Compton Cameras An alternative method for prompt gamma ray detection is the Compton camera, which does not require collimation. The Compton camera is a multi-stage measurement device capable of determining the initial energy and direction of a gamma ray as it Compton scatters in the different stages of the detectors. Using an electronically collimated detector is likely to improve the detection efficiency. Traditionally, a Compton camera consists of one scatter detector and one absorber detector [46]. Photons scatter in the first detector and are absorbed in the second one. Provided photons are totally absorbed in the second detector or their incident energy is known, it is possible, from the measurement of the deposited energies and interaction positions in both detectors, to reconstruct cones containing their incident trajectories. The photon emission points can be reconstructed by intersecting all these cones. A possible use of a Compton camera for prompt gamma imaging is a detection system that combines a beam hodoscope and a double scattering Compton camera [12]. The beam tagging device has a dual function. First, it gives a time reference for time of flight measurements performed in order to discriminate the gamma signal from the background. Second, it makes it possible to tag the incident ions spatially in the plane transverse to the beam. Figure 2.9 is a schematic of the principle of the camera. The camera consists of three position-sensitive and energy-resolved detectors: two silicon scatter detectors and a pixelated LYSO scintillation absorber detector. A second scatter detector is required to make a direct analytic reconstruction possible. As high energy gamma rays do not deposit all their energy in the camera detectors, the gamma energy cannot be deduced by simply adding the deposited energies in the detectors. The prompt gamma emission points are reconstructed from events corresponding to one Compton scattering without energy escape in each scatter detector and one interaction of the prompt gamma in the last detector. For each of these events, the incidence angle of the primary photon can be deduced from the position measurements in the three detectors and the energy measurements in the two scatter detectors.

50 26 State of the art in prompt gamma imaging Figure 2.9 Configuration of the detection system for prompt gamma imaging with a Compton camera and a hodoscope [12]. Figure 2.1 Concept of prompt gamma imaging with a slit camera [13]. The proposed configuration was studied by means of Monte Carlo simulations revealing the potential application of the Compton camera concept for prompt gamma imaging. This technique could offer more than 1D imaging of the beam penetration depth but, due to its complexity, to our knowledge, it has not been applied yet during proton irradiation. 2.6 Knife-edge slit-camera The concept An alternative to the multi-slit camera to acquire prompt gamma profiles during a single acquisition and avoid the use of scanning systems is the slit camera [13]. In the present thesis, we propose a novel detector suitable for the use with

51 2.6 Knife-edge slit-camera 27 a slit collimator. As sketched in figure 2.1, slit collimation gives a 1D projection of prompt gamma emissions along the beam path on a scintillation detector. The strength of the slit geometry is that it is focused on a single objective that is measuring the depth at which the beam stops in the patient. If compared to the other techniques reported throughout this chapter, the slit design has the advantages of simplicity, reduced cost and limited footprint. Since the image has only one dimension, this technique is considered to be well suited to the measure of a single pencil beam Optimization of the design through simulations The design of the camera has been optimized by means of Monte Carlo simulations with the code MCNPX version 2.5. [4] to determine optimal values for parameters such as the collimator material, slit width and slit angle. This study is reported in the PhD thesis of Smeets [4]. We will give a summary of the results which are useful for the design of the detector. More details can be found in [4] and [13]. The reference setup for simulations consists of a cylindrical PMMA target, which replaces the patient, with 2 cm length and 15 cm diameter. A 16 MeV pencil beam of protons is incident along the target axis. A single spot of 1 9 protons is considered. In the case of a real beam delivered by an IBA system with a Gaussian profile of 5 mm sigma at the target entrance, these 1 9 protons would give an approximate dose of 1.65 Gy at the Bragg peak. A 2D scintillation detector is placed at 3 cm from the beam axis and a slit collimator is located halfway, at 15 cm from the beam axis, to obtain a 1:1 projected image of the beam on the scintillator. The slit collimator has a knife-edge aperture. The scintillator is 1 cm wide along the beam axis and 2 cm high. Protons have a range of 15.2 cm in PMMA at 16 MeV and the slit collimator and scintillator are centered at this particular depth along the beam axis. According to simulations, the secondary particles leaving the target are mostly neutrons and photons: we have 12 neutrons and 9 photons for 1 incident protons. The contribution of all the other particles, such as electrons and protons, can be neglected. Energy and angular spectra of secondary photons and neutrons are presented in figure Photons are emitted along a continuous energy spectrum up to about 7 MeV, where the different characteristic gamma lines reported in figure 1.2 can be identified. On the other hand, neutrons have a wide energy spectrum up to the beam energy. Regarding the angle of emission, photons are

52 28 State of the art in prompt gamma imaging Figure 2.11 Simulated differential (left axis) and cumulative (right axis) energy spectra of photons (top) and neutrons (center) leaving the 2 cm PMMA target irradiated by a 16 MeV proton pencil beam. Bottom: simulated differential angular spectra of photons and neutrons leaving the 2 cm PMMA target irradiated by a 16 MeV proton pencil beam [13] emitted isotropically, while high energy neutrons are forward peaked along the beam axis. Based on this signal to be detected, the simulation study led to the definition of the main parameters of the camera system. A Tungsten alloy collimator with 4 mm thickness, 63.4 slit angle and 6 mm slit aperture was dimensioned.

53 2.6 Knife-edge slit-camera 29 Figure 2.12 Top: simulated detection profile of a 16 MeV pencil beam decomposed in its photon and neutron contribution. Bottom: simulated detection profile where the contribution of photons and neutrons passing through the collimator wall, through the knife-edge and through the slit opening are distinguished [4]. The energy window where there is best correlation between prompt gammas and the Bragg peak was found to be between 3 and 6 MeV. Figure 2.12 shows the simulated detection profiles of a 16 MeV pencil beam on a scintillator detector. The photons and neutrons contributions are separated on the top figure, highlighting that the neutrons contribution is not correlated to the Bragg peak. The contributions of photons and neutrons passing through the collimator wall, the slit knife edge and the slit opening are distinguished on the graph on the bottom. The collimator wall component include counts due to particles set in motion in the collimator wall by incident photons and neutrons. The potential benefit of an additional time-of-flight discrimination was in-

54 3 State of the art in prompt gamma imaging Figure 2.13 Detection profiles measured at 1 MeV (left) and 16 MeV (right) in different positions of the target along the beam axis. The shifts of the detection profiles are estimated by fits of the experimental data with a reference 3-line segment curve simulated for the mm position [13]. vestigated, but this option has been discarded so far. ToF selection would help reduce the baseline of uncorrelated particles, but would not increase the peak of the correlated particles. Our objective is indeed to maximize the accuracy in range determination while reducing as much as possible the complexity of the design. The priority is to have a reliable instrument with short developing times for the use in clinical routine First experimental results This approach was experimentally verified with a first prototype based on a gamma detector developed for low energy SPECT applications [13]. Measurements were conducted with low beam currents not to saturate the count rate capabilities of the camera and with a maximum beam energy of 16 MeV. More details about the experimental setup are given in chapter 4. Figure 2.13 shows the detection profiles measured at 1 MeV and 16 MeV as the target was moved along the beam axis to induce the detection of range shifts by the camera. The shifts of the detection profiles are estimated by fits of the experimental data with a reference 3-line segment curve simulated for the mm position. The acquisitions were realized for a high number of incident protons (about 1 1 ). In order to evaluate the accuracy of the camera as a function of the number of incident protons, detection profiles corresponding to different fractions of the total number of protons delivered were considered. The horizontal shift of the corrected reference profile that best fits each measured profile was calculated. The relation between the shift P of the detection profile fit and the exact

55 2.7 Conclusions and remaining challenges in PGI 31 Figure 2.14 Accuracy of the shift retrieving method at 1 MeV (left) and 16 MeV (right) in the simulations and the measurements [13]. range shift R was modeled with a second order polynomial of the form R = a 1 ( P ) + a 2 ( P ) 2 [13]. A standard deviation σ = [1/7 Σ 7 i=1 = ( R i R i ) 2 ] 1/2 was then calculated from the difference between the estimated shift R and the exact shift R for the seven values (1,, +1, +2, +3, +5 and +1 mm). The results are plotted in figure The graphs show that the slit camera would achieve a 1 2 mm standard deviation on range estimation for number of incident protons that correspond to doses in water at the Bragg peak as low as 15 cgy at 1 MeV and 25 cgy at 16 MeV. These are reasonable values of dose for a single spot in a proton therapy treatment delivered in pencil beam scanning mode. 2.7 Conclusions and remaining challenges in PGI Prompt gamma imaging is a promising technique for real-time range control in proton therapy and has emerged as an hot topic in the last few years. The main challenge of this approach is the realization of a technical solution which is suitable for the measurement of prompt gammas in clinical conditions. Throughout this chapter we investigated different approaches. Our efforts will be focused on the slit camera design, which already demonstrated the possibility to reach millimeter accuracy for doses as low as the ones used during treatment. At the beginning of this work, based on the state of the art of PGI, three important issues needed to be experimental verified: Shift detection capability up to 23 MeV. So far, prompt gamma profiles were successfully acquired up to 16 MeV. However, the IBA C23 cyclotron s maximum beam energy is 23 MeV. This represents the most

56 32 State of the art in prompt gamma imaging challenging condition because this is the case with the less favorable signal to background ratio, due to the increased number of neutrons. Camera operation at clinical beam currents. As stated in paragraph 2.6, the first measurements with the slit camera were performed with beam currents lower than the ones used in clinical routine. This was made to limit the event rate reaching the detector. Realizing a gamma detector able to sustain the event rate in clinical conditions is one of the main objectives of this work. Evaluation of the effect of inhomogeneities. All the works that we could find in literature were aimed to validate the proof of concept of PGI for real-time range control in proton therapy. For this purpose, homogeneous PMMA or water targets have been used. Nevertheless, range uncertainty is increased by tissue inhomogeneities and a slit camera would make sense if it can control the beam range in inhomogeneous tissues.

57 Chapter 3 Gamma-ray detectors Before discussing the design of the gamma-ray detector object of this thesis, we first outline some general properties that apply to all kind of detectors. We particularly focus on energy resolution, detection efficiency and count rate performances of a detector operating in pulse mode. After that, we give a description of scintillator detectors and of the most common photo-detectors for scintillation light readout. Silicon Photomultipliers are described in depth because they are used in this work. After an overview on scintillation pulse processing, we describe the contributions to energy resolution in the specific case of scintillators coupled to SiPMs.

58 34 Gamma-ray detectors 3.1 General properties of radiation detectors Radiation detectors provide a signal that is converted to an electric current, which is proportional to the characteristics of the incident radiation. Throughout this chapter we will focus on scintillator detectors, where the incident radiation is converted into pulses of visible light. The conversion to a current signal is performed in a further step by means of photo-detectors which operate with radiation emitted along the visible spectrum Modes of operation There are three modes of operation of radiation detectors: pulse mode, current mode and mean square voltage mode. The two last modes are adopted at very high events rates, when the time between adjacent events becomes too short to carry out an adequate analysis. These measurement techniques respond to the time average taken over many individual events. In pulse mode operation, the measurement instrumentation is designed to record each individual quantum of radiation that interacts in the detector. In most common applications, the time integral of each burst of current is recorded, since the energy deposited in the detector is directly related to the charge. A simpler approach may be to register all pulses above a low-level threshold, regardless of the value of the charge. This approach is called pulse counting. An evaluation of the possibility to use a detector operating in current mode for prompt gamma imaging was performed in [4] and finally discarded. In current mode there wouldn t be any energy discrimination and therefore the contribution of correlated particles would be overwhelmed by uncorrelated particles, unless we use a time-of-flight discrimination. However, time-of-flight discrimination would be more complicated to implement and calibrate than energy discrimination. For this reason, the design study for the gamma detector assumes a detector operating in pulse mode. Throughout the dissertation we will only consider pulse mode of operation Energy resolution One important property of a detector in radiation spectroscopy can be examined by observing its response to a mono-energetic source of that radiation. Figure 3.1 illustrates an example of the photo-peak for the response function of a radiation detector. The distribution is centered at the average value H

59 3.1 General properties of radiation detectors 35 and the width of the distribution is a factor of quality of the energy resolution of the detector. This width reflects the fluctuation recorded from pulse to pulse even though the same energy was deposited in the detector for each event. If the amount of these fluctuations is made smaller, the width of the corresponding distribution will also become smaller and the peak will approach a sharp spike. The energy resolution of the detector is conventionally defined as the FWHM divided by the location of the peak centroid H. The smaller the figure for the energy resolution, the better the detector will be able to distinguish between two radiations whose energies lie near each other. In most cases, the dominant source of fluctuation is the statistical noise arising from the discrete nature of the measured signal itself. The statistical noise arises from the fact that the charge Q generated within the detector by a quantum of radiation is not continuous variable but instead represents a discrete number of charge carriers. An estimate can be made of the amount of inherent fluctuation by assuming that the formation of each charge carrier is a Poisson process. Under this assumption, if a total number N of charge carriers is generated on the average, one would expect a standard deviation of N to characterize the statistical fluctuations in that number. If this were the only source of fluctuation in the signal, the response function, should have a Gaussian shape following: G(H) = A σ 2π exp( (H H ) 2 2σ 2 ) (3.1) The width parameter σ determines the FWHM of any Gaussian through the relation FWHM= 2.35σ. H and A represent the centroid and the area, respectively. The response of many detectors is approximately linear, so that the average pulse amplitude H = KN, where K is a factor of proportionality and N is the number of charge carriers. The standard deviation σ of the peak in the pulse height spectrum is then σ = K N and its FWHM is 2.35K N. The limiting resolution R due only to statistical fluctuations in the number of charge carriers is: R P oisson limit = F W HM = 2.35K N H KN = 2.35 N (3.2)

60 36 Gamma-ray detectors Y R = FWHM / H Counts Y/2 σ FWHM H Energy Figure 3.1 Example of response function for a detector. For peaks whose shape is Gaussian with standard deviation σ, the FWHM is given by 2.35σ. This limiting value of energy resolution depends only on the number of charge carriers N and the resolution improves as N is increased Detection efficiency In principle, all radiation detectors give rise to an output pulse for each quantum of radiation that interacts within its active volume. Gamma rays or neutrons must first undergo a significant interaction in the detector before detection is possible. Because these radiations can travel large distances between interactions, detectors are often less then 1 % efficient. The detector efficiency is the relation between the number of pulses counted and the number of photons incident on the detector and can be subdivided in absolute and intrinsic. Absolute detection efficiency is defined as: ϵ abs = number of pulses recorded number of radiation quanta emitted by source (3.3) and depends not only on detector properties but also on the geometry, primarily the distance from the source to the detector. The intrinsic efficiency is defined as: ϵ int = number of pulses recorded number of radiation quanta incident on detector (3.4)

61 3.1 General properties of radiation detectors 37 Events in the detector Dead Live Dead Live τ Paralyzable Non paralyzable Figure 3.2 Comparison between the behaviors of a detector which follows the paralyzable model and one which follows the non-paralyzable model. and does not include the solid angle subtended by the detector as an implicit factor. The intrinsic efficiency usually depends primarily on the detector material, the radiation energy and the physical thickness of the detector in the direction of the incident radiation Dead time In nearly all detector systems, there is a minimum amount of time that must separate two events in order that they be recorded as two separate pulses. This minimum time separation is usually called the dead-time of the counting system and can be set by processes in the detector itself, by the associated electronics or the combination of both. Because of the random nature of radioactive decay, there is always some probability that a true event will be lost because it occurs too quickly following a preceding event. We can consider two models of dead time behavior of counting systems: paralyzable and non-paralyzable response [15]. In this last model, a fixed time τ is assumed to follow each true event that occurs during the live period of the detector. True events that occur during the dead period are lost and assumed to have no effect whatsoever on the behavior of the detector. In contrast, in a paralyzable detector, the same dead time τ is assumed to follow each true interaction that occurs during the live period of the detector. True events that occur during the dead period, however, although still not recorded as counts, are assumed to extend the dead time by another period τ following the lost event. Figure 3.2 illustrates the fundamental assumptions of the two models. In the example shown, the non-paralyzable detector would record four counts from the six true interactions. In contrast, the paralyzable detector records

62 38 Gamma-ray detectors only three of the six counts. The two models predict the same first-order losses and differ only when true event rates are high. Real counting systems often display a behavior that is intermediate between these extremes. In the non-paralyzable case, the fraction of all time that the detector is dead is given simply by the product of the recorded count rate m and the dead-time τ. Therefore, the rate at which true events are lost is simply [15]: n m = nmτ (3.5) where n is the true interaction rate. The recorded rate is therefore: m = n 1 + nτ (3.6) In the paralyzable case, dead periods are not always of fixed length. The distribution of intervals between random events occurring at an average rate n is [15]: P 1 (T )dt = ne nt dt (3.7) The probability of intervals larger than τ can be obtained by integrating this distribution between τ and P 2 (T ) = τ P 1 (T )dt = e nτ (3.8) The rate of occurrence of such intervals is then obtained by simply multiplying the above expression by the true rate n m = ne nτ (3.9) A plot of the observed rate m versus the true rate n is given in figure 3.3 for both models. When rates are low the two models give the same result, but the behavior at high rates is markedly different. A non-paralyzable system will approach an asymptotic value for the observed rate 1/τ. For paralyzable behavior, the observed rate is seen to go through a maximum. Very high true

63 3.2 Scintillation detectors 39 1 / τ Recorded count rate (m) 1 / τe m = n Paralyzable Non-paralyzable 1 / τ True interaction rate (n) Figure 3.3 Observed rate as a function of the true rate for paralyzable and nonparalyzable models. interaction rates result in a multiple extension of the dead period following an initial recorded count, and very few true events can be recorded. One should avoid measurement conditions under which dead time losses are high because of the errors that inevitably occur in making corrections for the losses. The value of τ may be uncertain or subject to variation, and the system behavior may not follow exactly either the models described above. When losses are greater than 3 or 4 %, the calculated true rate becomes very sensitive to small changes in the measured rate and the assumed system behavior. That s why we should seek to reduce the losses as much as possible with a fast counting system. However, we will explain in paragraph 3.4 that a small dead-time conflicts with energy resolution and a trade-off between counting efficiency and energy resolution should be found. 3.2 Scintillation detectors Scintillation counting is an indirect method for radiation detection, based on a scintillator which generates photons of light in response to incident radiation and a sensitive photo-detector which converts the light to an electrical signal. Some of the advantages of scintillation counting are the wide choice of scintillator materials, fast time response, high detection efficiency and large detection area.

64 4 Gamma-ray detectors Figure 3.4 Gamma ray absorption characteristics for a NaI(Tl) scintillator [14] Gamma-ray interactions When ionizing radiation enters a scintillator, it produces a fluorescent flash known as scintillation. In case of gamma rays, this scintillation occurs as a result of excitation of the bound electrons by means of free electrons inside the scintillator. These free electrons are generated by three mutual interactions: the photoelectric effect, Compton effect and pair production. The probability of occurrence of these interactions depends on the type of scintillator and the energy level of the gamma rays. Figure 3.4 shows the extent of these interactions when gamma-ray energy is absorbed by a NaI(Tl) scintillator. It is clear that the photoelectric effect predominates at low energy levels and pair production increases at high energy levels. Of these three interactions, the amount of scintillation produced by photoelectric effect is proportional to gamma-ray energy [15]. Photoelectric absorption is an interaction in which the incident gamma-ray photon disappears and a photoelectron is produced from one of the electron shells of the absorber atom [15] as represented in figure 3.5. The photoelectron appears with an energy given by:

65 3.2 Scintillation detectors 41 Ee- hν incoming photon photoelectron leaving Figure 3.5 Schematic of the photoelectric absorption mechanism. hν scattered photon hν incoming photon θ recoil electron Figure 3.6 Schematic of the Compton scattering mechanism. E e = hν E b (3.1) For typical gamma-ray energies, it is probable that the photoelectron emerges from the K shell, which have typical binding energies from few kev for low-z materials to tens of kev for high-z materials. During the process of filling of the created vacancy by electron rearrangement, the binding energy is liberated either in the form of a characteristic X-ray or Auger electron. These X-rays are usually reabsorbed through photoelectric interactions. The effect of photoelectric absorption is the liberation of a photoelectron, which carries off most of the gamma-ray energy and of one or more low-energy electrons corresponding to absorption of the original binding energy of the photoelectron. Under these conditions, the expected spectrum due to photoelectric absorption is ideally a single peak at a total electron energy corresponding to the energy of the incident gamma rays. Compton scattering takes place between the incident gamma-ray photon and an electron in the absorbing material. In Compton scattering, the incoming gamma-ray photon is deflected through an angle θ with respect to its original direction as illustrated in figure 3.6. The photon transfers a portion of its energy to the electron (assumed to be initially at rest), which is then known as a recoil electron, or a Compton electron. The energies of the scattered photon is given by:

66 42 Gamma-ray detectors hν 1 = hν 1 + α(1 cosθ) (3.11) where α is given by: α = hν m c 2 (3.12) where m c 2 is the rest mass energy of the electron (.511 MeV). The kinetic energy of the recoil electron is therefore: E e = hν hν (3.13) Because all scattering angles generally occur in the detector, a continuum of energies can be transferred to the electron, from zero up to the maximum energy where θ is equal to π, which creates a the so called Compton edge in the spectrum. If a photon enters matter with an energy in excess of 1.22 MeV, it may interact by a process called pair production. The photon, passing near the nucleus of an atom, is subjected to strong field effects from the nucleus and may disappear as a photon and reappear as a positive and negative electron pair. The two electrons produced, e- and e+, are not scattered orbital electrons, but are created, de novo, in the energy/mass conversion of the disappearing photon. The kinetic energy of the electrons produced will be the difference between the energy of the incoming photon and the energy equivalent of two electron masses (2.511, or 1.22 MeV) following: E e + + E e = hν 1.22 MeV (3.14) For typical energies, both the electron and positron travel a few millimeters bfore losing all their kinetic energy to the absorbing medium. Similarly to the photoelectric effect, the total charged particle kinetic energy created by the incident gamma ray results in a delta function in the spectrum, located 2m c 2 below the incident gamma-ray energy. This energy corresponds to the position of the double escape peak in actual gamma-ray height spectra, as reported in

67 3.2 Scintillation detectors 43 Figure 3.7 Example of the response function of a scintillator detector. The spectrum on the left is relative to low energy events. The spectrum on the right describes the situation for high energy events, where pair production is significative [15] the next section Response function The response function of a detector shows contributions from all the interactions listed above. We now consider a detector with intermediate size, meaning that its size is larger than the mean free path of the secondary gamma radiations (1-2 cm) but not large enough so that all secondary radiation interact with the detector active volume. The spectrum of a detector for energies where pair production is not significant is presented in figure 3.7 (left) and consists of a Compton continuum and a photopeak. In addition to these two last contributions, the effect of multiple Coulomb scattering is also shown. The spectrum on the right is an example of the response of a detector to gamma rays whose energy is high enough to make pair production significant. The annihilation photons now may either escape or undergo further interaction within the detector. These additional interactions may lead to either partial or full-energy absorption of either one or both of the annihilation photons. If both annihilation photons escape without interaction, events occur that contribute the double escape peak. If one annihilation photon escapes but the other is totally absorbed, the events contribute to a single escape peak.

68 44 Gamma-ray detectors Gamma ray Gamma ray Monolithic Scintillator Light-guide Photo-detectors Pixelated Scintillator Light-guide Photo-detectors Figure 3.8 Monolithic (top) and pixelated (bottom) scintillators coupled to photodetectors. The light tracks are not realistic Scintillators classification Scintillators can be classified into inorganic scintillators and organic scintillators. Most inorganic scintillators are made of a halogen compound and offer advantages of excellent energy conversion efficiency, high absorption efficiency and a good probability for the photoelectric effect compared to organic scintillators. Organic scintillator include plastic scintillators, liquid scintillators and anthracene of organic crystal. These scintillators display a short decay time and have no deliquescence. Organic scintillators have low density and high sensitivity to fast neutrons due to an important proportion of hydrogen. For these reasons they are not suitable for the detection of prompt gammas. Two different geometries are commonly used: monolithic scintillators and pixelated scintillators (see figure 3.8). A monolithic scintillator consists of a continuous block of scintillator material whose surfaces are covered with a reflector. A pixelated scintillator is made of an array of small blocks. Pixelated detectors have become commonly used in modern PET modules due to their several advantages. First, the interaction coordinates in a pixelated detector are usually determined by crystal segment identification, while in a monolithic scintillator complex algorithms are required. Another advantage is the improvement in the detector count rate. The small pixels channel the light toward the photo-detectors, thereby reducing the light spread. If 1:1 coupling between the scintillator pixel and the photo-detector is performed, the probability for pulse pile-up at high count rate decreases. There are however many drawbacks in the use of pixelated scintillators. First, they are more expensive and difficult to assembly. Second, the scintilla-

69 3.2 Scintillation detectors 45 Sorrounding medium Refractive index = n1 θc θ 1 θ 2 Scintillator Refractive index = n Figure 3.9 Conditions at the interface of dissimilar optical media. Ray 1 may escape but ray 2 will be internally reflected at the surface. tion light experiences a lot of reflections which lead to a considerable amount of photon absorption and this could result in a worse energy resolution Light collection In any scintillation detector, it is highly desirable to collect the largest possible fraction of the light emitted isotropically from the track of the ionizing particle. As stated in section 3.1.2, the energy resolution improves with the number of photons. Less than perfect light collection is mainly due to losses at the scintillator surfaces. Therefore, the uniformity of light collection depends primarily on the conditions that exist at the interface between the scintillator and the container in which it is mounted. The light collection conditions affect the energy resolution of a scintillator in two ways [15]. First, the statistical contribution of energy resolution discussed in paragraph will worsen as the number of scintillation photons that contribute to the measured pulse is reduced. Second, the uniformity of the light collection will determine the variation in signal pulse amplitude as the position of the radiation interaction is varied throughout the scintillator. Perfect uniformity would assure that all events depositing the same energy, regardless of where they occur in the scintillator, would give rise to the same pulse amplitude. With ordinary scintillators of a few centimeters, uniformity of light collection is seldom a significant contributor of the overall energy resolution. However, one should deeply consider this aspect when using crystals with high aspect ratios, i.e crystals with high length and small width. Because the scintillation light is emitted in all directions, only a limited fraction can travel directly to the surface at which the photo-detector is located. The remainder must be reflected one or more times at the scintillator surfaces. Two situations may prevail when the light photon reaches the sur-

70 46 Gamma-ray detectors face, as illustrated in figure 3.9. If the angle of incidence Θ is greater than the critical angle Θ c, total internal reflection will occur. If Θ is less than Θ c, partial reflection and partial transmission will occur. The critical angle Θ c is determined by the indexes of refraction for the scintillation medium n and the surrounding medium n 1 : Θ c = sin 1 n 1 n (3.15) To recapture the light that does escape from the surface, the scintillator is normally surrounded by a reflector at all surfaces except that at which the photo-detector is mounted. Reflectors can be either specular or diffusive. A polished metallic surface will act as a specular reflector for which the angle of reflection equals the angle of incidence. On the other hand, with a diffusive reflector, the angle of reflection is approximately independent of the angle of incidence and follows a Lambertian distribution. 3.3 Photo-detectors for scintillation light read out The use of scintillation counting in radiation detection and spectroscopy would not be possible without the availability of devices to convert the extremely weak light output (hundreds of photons) of a scintillation pulse into a corresponding electrical signal. Photo-detectors for scintillation counting can be divided into vacuum detectors and solid-state detectors. A description of the most common photo-detectors is provided throughout this section Photomultiplier tubes and position sensitive photomultipliers The Photomultiplier Tube (PMT), a well established and widely available device, has been the detector of choice for commercial medical imaging applications. PMTs with different sizes provided by Hamamatsu are shown in figure 3.1. A PMT is a vacuum tube consisting of an input window, a photo-cathode, focusing electrodes, an electron multiplier and an anode usually sealed into an evacuated glass tube as sketched in figure The light which passes through the input window excites the electrons in the photo-cathode so that photoelectrons are emitted into the vacuum. This is known as external photoelectric

71 3.3 Photo-detectors for scintillation light read out 47 Figure 3.1 Photograph of typical photomultiplier tubes with difference sizes and shapes (Hamamatsu [14]). Figure 3.11 Schematic of a Photomultiplier Tube [14]. effect. Photoelectrons are then accelerated and focused by the focusing electrode onto the first dynode where they are multiplied by means of secondary electron emission. This secondary emission is repeated at each of the successive dynodes. The multiplied secondary electrons emitted from the last dynode are finally collected by the anode. The current multiplication mechanism offered by dynodes makes photomultiplier tubes ideal for low-light-level measurement. Typical values of gain and quantum efficiency are 1 6 and.25, respectively. A particular kind of PMTs, known as Position Sensitive (PS) PMT, offers the possibility to detect the position of interaction and is particularly interesting for imaging systems. Figure 3.12 shows the electrode structure for metal channel dynodes and

72 48 Gamma-ray detectors Figure 3.12 Electrode structure and electron trajectories of a metal channel dynode type multi-anode photomultiplier tube [14]. the associated electron trajectories. Compared to other types of dynodes, metal channel dynode type multi-anode photomultiplier tubes feature very low crosstalk during secondary electron multiplication. This is because the photoelectron emitted from the photocathode are directed onto the first dynode by the focusing mesh and then flow to the second dynode, third dynode etc to the last dynode and finally to the anode, while being multiplied with a minimum spatial spread in the secondary electron flow. The figure shows a multi-anode device, where the output signal is read using independent multiple anodes. A different approach is the use of current or charge dividing center-of-gravity detection [14] Photo-diodes An alternative to vacuum device for scintillation light detection is the use of solid state devices [47]. Solid state devices are based on a PN junction that generates a current or voltage when is irradiated by the light. Solid state devices can be classified by function and construction into Silicon photo-diodes (PN type), Si PiN photo-diodes, Si APD (Avalanche photo-diodes), Silicon Drift Detectors (SDD) and Silicon Photomultipliers (SiPM). When light is incident on a semiconductor, electron-hole pairs are generated. Photons corresponding to typical scintillation light carry about 3-4 ev of energy, sufficient to create electron-hole pairs in a semiconductor with a bandgap of 1-2 ev. The conversion is not limited by the need for charge carriers to escape from surface as in conventional photo-cathode, so the maximum quan-

73 3.3 Photo-detectors for scintillation light read out 49 tum efficiency can be as high as 8%, larger than in a PMT. However, there is no subsequent amplification of this charge, so the output signal is smaller by orders of magnitude. In a common configuration for a silicon photo-diode, light is incident on a p-layer entrance window. Electron and holes produced by the light are collected by the boundaries of the central intrinsic region driven by the electric field resulting from the applied voltage. Because of the small signal amplitude, electronic noise is a major problem in pulse mode operation and that s the reason why standard photo-diodes have not been used for scintillation light readout. A particular type of photo-diode is the PIN diode, which features a highresistivity intrinsic semiconductor layer between the P and the N regions. In this way, the depletion region extends and the sensitive volume of the diode increases. The PIN photo-diode has been used as photo-detector for scintillation counting but, differently from the PMT, the lack of an internal gain mechanism makes necessary the use of low-noise electronics. The energy resolution is mainly defined by the electronic noise instead of the photo-electron statistics as in the case of PMTs. The small amount of charge that is produced in a conventional photo-diode by a typical scintillation event can be increased through an avalanche process that occurs in a semiconductor at high values of the applied voltage. This is the case of avalanche photo-diodes. The charge carries are accelerated sufficiently between collision to create additional electron-hole pairs along the collection path. The common configuration of avalanche photo-diodes is the reach-through configuration. Light enters the thin p + layer and and interacts within the π region. The results of interactions are electron-hole pairs and the electron is drawn to the n + region into the multiplying region where a high electric filed exists. Here additional electron-hole pairs are created, increasing the measured signal. The internal gain helps pull the signal up from the electronic noise level and allows good energy resolution in pulse mode at lower radiation energy than possible using conventional photo-diodes. In silicon drift detectors (SDD) semiconductor junctions are formed at both faces of a large-area wafer and each is reverse biased until the detector is fully depleted. Electrons created by ionizing radiation within the semiconductor are confined within an electric potential well and caused to drift a direction parallel to the wafer surface. A collecting anode is fabricated near the edge of the wafer. The drift detector configuration has the advantage that can be exploited to improve energy resolution. Because the electrons can be drifted over large distance and collected on an electrode of very small size, the capacitance of the

74 5 Gamma-ray detectors Cathode Microcell hν Figure 3.13 Schematic diagram of a SiPM, consisting of an array of microcells (photo-diode plus quenching resistor) with summed output. Anode detector can be much smaller than that of an equivalent semiconductor diode, therefore reducing the noise [15] The silicon photo-multiplier Operating principle The operating principle of a SiPM is based on single photon counting diodes [48]. These photon counting diodes are designed to operate above breakdown voltage in a mode of operation known as Geiger mode. In Geiger mode, photons entering the photo-diode generate a self-sustaining avalanche current which is quenched and reset by use of either passive elements or active quenching circuits. The limitation of a photon counting detector is the need for it to quench and reset after every photon event. Additionally, a photon counting detector is a binary device that is either on or off. The binary nature is usually exploited for photon timing; however, the output is independent of the number of simultaneous incident photons. A photon counting diode cannot distinguish between multiple photons incident on the detector at the same time. To overcome this limitation, a parallel array of photon counting diodes, whose schematic is depicted in figure 3.13, can be implemented such that the output becomes proportional to the incident photon flux [16]. Practically, a silicon photomultiplier consists of one array of Geiger mode photo-diodes, where

75 3.3 Photo-detectors for scintillation light read out 51 Breakdown voltage Figure 3.14 Typical reverse I-V characteristics of a SiPM at room temperature and at 253 K. The breakdown voltage is indicated with a vertical bar [16]. each photo-diode is coupled to an integrated quench element to form the SiPM microcell. For a SiPM, the breakdown voltage can be defined as the bias point at which the electric field strength generated in the depletion region is sufficient to create a Geiger discharge. The point of breakdown is clearly visible on an I-V plot by the sudden increase in current, as in figure SiPMs manufacturers recommend to work few Volts above the breakdown voltage. The over-voltage is the difference between the operating voltage and the breakdown voltage and is critical in defining the parameters of the SiPM. Gain As already stated, each microcell in an SiPM is comprised of a Geiger-mode photo-diode in series with an integrated quench resistor. Each microcell generates a quantized amount of charge every time the microcell undergoes a Geiger breakdown. The gain of a microcell (and hence the detector) is defined as the ratio of the output charge to the charge of an electron. The output charge can be calculated from the over-voltage V ov and the microcell capacitance: G = (C V ov )/q (3.16) In first approximation, the gain has no impact on the number of photo-electrons detected, hence on the energy resolution of the system, but a high gain results in a less critical electronic readout scheme, because it makes the electronic

76 52 Gamma-ray detectors noise contribution in the energy resolution equation negligible. Photon Detection Efficiency The Photon Detection Efficiency is the statistical probability that an incident photon will produce a Geiger pulse from one of the SiPM microcells. It is determined by three parameters: quantum efficiency, geometrical efficiency and avalanche initiation probability, according to: P DE(V, λ) = η(λ) ϵ(v ) F (3.17) where η(λ) is the silicon quantum efficiency, ϵ(v) is the avalanche initiation probability and is a function of the bias voltage and F is the SiPM geometrical efficiency. The quantum efficiency of silicon depends on the wavelength and it is more than 8 % over much of the visible spectrum (4 7 nm). The geometrical efficiency is defined as the ratio of the total active area of all the SiPM microcells to the total area of the SiPM. The avalanche initiation probability is the probability that a carrier in the depletion region initiates a Geiger avalanche and is a function of the bias voltage. Not every photogenerated carrier will succeed in generating a Geiger avalanche. There is a nonzero probability that the seed carrier will lose energy to phonon interactions and recombine such that the chain of ionizations stop before the entire junction goes into Geiger breakdown. Linearity and Dynamic Range The detection of photons by a SiPM is a statistical process based on the probability of detecting randomly distributed photons by the limited number of sensitive elements. The SiPM PDE and the total number of microcells determine the dynamic range of the device. The number of microcells fired as a function of the number of incident photons can be approximated by the following expression [16]: N fired = M(1 exp( P DE N ph /M)) (3.18) where M is the total number of microcells in the SiPM, N ph is the number of instantaneous photons and PDE is the SiPM photon detection efficiency. The SiPM response is linear when the number of incident photons is much less

77 3.3 Photo-detectors for scintillation light read out 53 than the total number of cells and becomes sub-linear when the number of fired microcells reaches approximately a quarter of the total number of microcells. This behavior must be taken into account in the choice of the right device according to the number of photons expected. Devices with a large number of microcells have a wider dynamic range, thus a wider linear range, but a worse PDE because of the reduced fill-factor. Devices with less microcells are less linear but have a better PDE. A trade-off must be found according to the application. Sources of noise The SiPM main sources of noise are the dark count rate (DCR), the optical cross-talk and the after-pulses. The dark rate results from thermally generated carriers that can also initiate a Geiger avalanche that results in a current pulse indistinguishable from a pulse produced by the detection of a photon. This is particularly important for room temperature operation, because the dark rate increases with the temperature. The SiPM dark rate is the average frequency of the thermally generated Geiger avalanches from all the microcells in the array. Since this noise is comprised of a series of pulses, its magnitude is often quoted as a pulse rate, typically in khz or MHz. For continuous or current integration measurements, it might be more convenient to consider the contribution as a dark current in µa. If a threshold can be set above the single photon level, false triggers from the noise can be avoided, but the dark counts will always form a contribution to the measured signal. When undergoing Geiger avalanche, carriers near the junction emit photons as they are accelerated by the high electric field [17]. The photons emitted are spread across the visible spectrum and typically photons are emitted per electron crossing the junction [18]. These photons can travel to neighboring microcells and initiate a Geiger avalanche in one or more of the neighboring microcells. This process is known as optical crosstalk. The crosstalk probability is the probability that an avalanching microcell will trigger a second microcell to avalanche. The process happens practically instantaneously and results in an output pulse with twice the charge or twice the amplitude of a Geiger pulse from a single microcell. The optical crosstalk probability is a function of SiPM bias voltage and the distance between neighboring microcells. After-pulsing is the name given to Geiger pulses that occur after and are correlated to a random dark or photon initiated Geiger pulse. After-pulsing

78 54 Gamma-ray detectors Figure 3.15 Dependences of the gain and the dark count rate on the temperature for a typical device [17]. occurs due to the release of carriers captured by traps during a Geiger avalanche. During a Geiger avalanche, a large number of mobile carriers cross the junction. When this occurs there is a finite probability that a carrier may become trapped by a band-gap state. The carrier may then be released at some later time and trigger a new Geiger avalanche event. The effect of the above listed sources of noise results in a noise with a level of few photons. This affect the measurement for applications where very low levels of light are detected or where good time resolution is required. Temperature dependency One of the main advantages of SiPM is that they can work at room temperature. Although, the properties of this device show a strong dependence on temperature. The primary effects of temperature on the SiPM are a change in the breakdown voltage of the diode and in the dark count rate. In particular, an higher temperature results in an increased breakdown voltage and in an increased dark count. The breakdown voltage changes as a function of temperature, and, unless compensated for, this will result in a change in the effective over-voltage. Since the over-voltage affects many of the SiPM s characteristics, it follows that, for stable operation, the detector should have its temperature regulated or the bias voltage adjusted in order to maintain a constant over-voltage with respect to the altered breakdown voltage. If a constant over-voltage is maintained, many parameters, such as gain, PDE and timing, will remain the same as

79 3.4 Scintillation pulse shape analysis 55 at room temperature. However, regardless of constant over-voltage, the DCR will be altered by a change in temperature. Two typical curves that show the dependence of gain and DCR on ambient temperature are shown in figure The graph on the left shows that the gain decreases with temperature: the gain is proportional to the over-voltage that decreases with temperature. The graph on the right shows the increased dark count rate at higher temperature. The solid line is the DCR trend if the hardware threshold is 1.5 photoelectrons and the point-dashed line is the DCR with a threshold of.5 photoelectrons. 3.4 Scintillation pulse shape analysis The anode circuit of a photo-detector for scintillation light detection can be idealized as shown in figure C represents the capacitance of the anode itself, plus capacitance of the connecting cable and input capacitance of the circuit to which the anode is connected. The load resistance R may be a physical resistor or the input impedance of the connected circuit. The principal component of emitted light from most scintillators can be represented as a simple exponential decay. If the transit time of the photo-detector is small compared with this decay time, a realistic model of the electron current arriving at the photo-detector anode is [15]: i a (t) = i e t/τ (3.19) where τ is the scintillator decay constant. The initial current i can be expressed in terms of the total charge Q collected over the entire pulse: Q = i a (t)dt = i e t/τ dt = i τ (3.2) Therefore i is equal to Q/τ and: i a (t) = Q/τe (t/τ) (3.21) The voltage V a (t) is given by [15]:

80 56 Gamma-ray detectors V (t) a I (t) a C R Figure 3.16 Schematic of SiPM readout with on a resistor. Q/τ Anode current Q/C Anode current i(t) RC << τ RC >> τ Q/C RC/τ Voltage pulse V(t) Figure 3.17 Plots of the voltage pulses for the two extremes of large (green line) and small (red line) time constant. The anode current is depicted in blue. V a (t) = RC RC τ Q C (e t/rc e t/τ ) (3.22) Two extreme conditions can be identified: the first corresponds to those situations in which the time constant is chosen to be large compared with the decay time of the scintillator; the second is obtained by setting the anode circuit time constant to be much smaller than the scintillator decay time. The pulses corresponding to the two cases are plotted in figure 3.17 If RC >> τ equation 3.22 can be approximated by: V a (t) = Q C (e t/rc e t/τ ) (3.23) The rise time of the leading edge of the pulse is determined by the scintillator decay constant and the tail of the pulse decays at a rate determined by RC. The amplitude of the pulse is given simply by Q/C. In this condition, the pulse height is maximized and subsequent sources of noise will have minimum

81 3.5 Energy resolution in scintillators coupled to Silicon Photomultipliers 57 degrading effect on pulse height resolution. In the opposite extreme, the anode time constant is set at a small value compared with the scintillator decay time (RC << τ). Now equation 3.22 becomes: V (t) = RC τ Q C (e t/τ e t/rc ) (3.24) The leading edge of the pulse is determined by RC and the tail of the pulse has the time behavior of the scintillator pulse. The maximum amplitude of the pulse is RC/τ Q/C, that is smaller than Q/C because, by definition RC << τ. The voltage pulse is of much shorter duration that comes at the price of a reduced pulse amplitude, which results in a worse energy resolution, in case we score only the amplitude of the pulse without any further integration. 3.5 Energy resolution in scintillators coupled to Silicon Photomultipliers We analyze in detail the contributions of the energy resolution of a system composed of a scintillator and a SiPM-based detector, which is the solution adopted for our gamma camera as we will see in chapter 5. The energy resolution of a radiation detector based on scintillation counting is affected by several factors: the energy conversion efficiency of the scintillator, which has impact on the number of scintillation photons and therefore on the statistical contribution. the intrinsic energy resolution of the scintillator, which includes sources of resolution loss which are characteristic of the crystal itself. the light-collection efficiency of the photo-detector, which determines the actual number of scintillation photons that reach the photo-detector and can be converted into a charge. the quantum efficiency of the photo-detector. Given a number of incident photons, the number of photo-electrons depends on the quantum efficiency.

82 58 Gamma-ray detectors the dark current of the photo-detector and the electronic noise, which add a fluctuation to the output signal and causes an additional source of degradation of energy resolution. The energy resolution E/E of the full energy peak measured with a scintillator coupled to a photo-detector can be written as [49]: ( E/E) 2 = (δ sc ) 2 + (δ p ) 2 + (δ st ) 2 + (δ n ) 2 (3.25) where δ sc is the intrinsic resolution of the crystal, δ p is the transfer resolution, δ st is the statistical contribution and δ n is the noise contribution. The intrinsic resolution of the crystal is mainly associated with the nonproportional response of the scintillator, but is also affected by inhomogeneities in the scintillator causing local variations in the light output. Significant fluctuations arise because of the not perfect reflections conditions at the surface of the crystal [15]. The consequent non-uniform light collection efficiency can introduce significant line broadening. We will experimentally verify the impact of surface treatment on the uniformity of light collection, and therefore on energy resolution in section The transfer component is described by the variance associated with the fluctuation in the probability that a photon from the scintillator results in the production of a photo-electron in the SiPM. The transfer component depends on the quality of the optical coupling of the crystal and photo-detectors, homogeneity of the quantum efficiency of the photo-cathode and efficiency of charge collection. In modern scintillation detectors this component is negligible [5]. The statistical contribution has been already discussed in paragraph for general radiation detectors. In the case of SiPM we need to introduce the excess noise factor (ENF) in the equation 3.2. The ENF describes the statistical noise that is inherent with the stochastic multiplication process. The statistical contribution can be rewritten as [49]: δ st = ENF N (3.26) where N is the number of fired microcells. The noise contribution includes the dark current of the SiPM and the electronic noise. Due to the high gain of the SiPM, the electronic noise is negligible

83 3.5 Energy resolution in scintillators coupled to Silicon Photomultipliers 59 because its contribution is divided by the gain. As stated in paragraph 3.3.3, the SiPM noise is mainly at the single photon level and can become negligible in case of huge amount of scintillation light (thousands of photons). As a conclusion, in a system consisting of a scintillator coupled to a SiPMs the energy resolution is mainly defined by the intrinsic energy resolution of the scintillator and the statistical contribution.

84 6 Gamma-ray detectors

85 Chapter 4 Preliminary experimental results and definition of the specifications for the new detector In the present chapter we present results obtained with a first prototype slit camera, exploiting a gamma detector originally developed for low energy medical imaging. Measurements were useful to establish the proof of concept and to verify the ability of the slit camera design to detect target shifts up to the maximum beam energy (23 MeV). Based on these results, improvements and key-points for the design of a new detector are reported.

86 62 Preliminary experimental results and definition of the specifications for the new detector 4.1 Measurements on a first slit camera prototype The first objective of the PhD thesis was the proof of concept of prompt gamma imaging with a knife-edge slit camera. Preliminary experimental measurements were performed with a SPECT camera, originally developed for low energy (up to 1 MeV) applications. The aim of the test session was to verify the feasibility of PGI with the setup proposed by Smeets and optimized by means of Monte Carlo simulations [4]. In particular, we verified the ability of the camera to detect shifts of the proton beam range in the target at the maximum beam energy (23 MeV). Results served as the basis for the design of the new detector and were useful to assess the detector s specifications HiCam camera First profiles acquisition with a slit collimator were made using the HiCam camera, an Anger gamma camera developed in the framework of the HiCam (High resolution Camera) project, whose purpose was the development of a compact camera to be used in clinical and research environments [51]. The camera features a monolithic crystal coupled to 25 square-shaped silicon drift detectors (SDD) of 1 cm 2. SDD have high quantum efficiency (> 8%) and low electronic noise and are read out by a custom-designed ASIC. The image is reconstructed with a centroid algorithm and a nice intrinsic spatial resolution of.8 mm FWHM was achieved both in clinical and pre-clinical measurements. The standard HiCam system uses a 1 mm CsI(Tl) scintillator and it is suited to low energies (the ASIC dynamic range was designed for maximum photon energy of 2 kev) and low rates (the maximum rate capability is 5 counts/s) applications. Some modifications were needed to adapt the camera to prompt gamma imaging. The dynamic range issue was solved by replacing the CsI(Tl) crystal with a 1 cm thick LYSO (54 mm 61.5 mm transverse dimensions) and light collection was limited by using absorbers instead of reflectors on the lateral and top faces of the crystal. The limitations of the counting rate are due to the SDD drift time of a few µs and no modifications could be made to reach the expected rate of some MHz. For this reason, the beam was operated at lower beam currents with respect to the ones used in clinical conditions.

87 4.1 Measurements on a first slit camera prototype 63 Proton beam Tungsten Slit collimator HiCam Camera 15 cm 15 cm - 4 cm - cm + 4 cm PMMA Target Figure 4.1 Experimental setup including the cylindrical PMMA target, the tungsten slit collimator and the HiCam gamma camera Experimental setup Measurements were conducted at the West German Proton Therapy Centre of Essen (WPE), where the proton source is a isochronous cyclotron (IBA C23) with a constant energy of 23 MeV. An energy degrader and selection system provides the range adaptation. The experimental setup is shown in figure 4.1 and consists of a PMMA cylindrical target, a tungsten alloy (19.96 g/cm 3 with 9% W, 6% Nic and 4 % Cu) slit collimator and the HiCam camera. As shown on the left side of figure 4.1, the camera was placed at 3 cm distance from the target and the collimator was located halfway at 15 cm from beam axis, with 4 cm thickness, 63 slit angle, 6 mm slit width, 12 cm height and 16 cm length along the beam axis for each block. The PMMA target has 2 cm length and 7.5 cm radius. Another PMMA target was added for 23 MeV tests for a total axis length of 4 cm and the tungsten collimator was made longer to cover the additional target as shown in figure 4.1 (Photograph on the right). The detector field of view (FOV) is 6.4 mm 52. mm, not sufficient to cover a FOV of at least 1 cm along the beam axis. The camera was therefore translated by 4 cm and +4 cm along its axis to obtain a broader image as illustrated in figure 4.1. Measurements with closed collimator were also realized by joining the right-angled faces of the two tungsten blocks, resulting in a 4 cm thick tungsten wall. For profile acquisition at 1, 16 and 23 MeV the target was placed at the expected beam range depth (6.7, 15.2 and 27.7 cm, respectively). At 23 MeV only, the camera was then moved along the beam axis so that it looks like a range shift to the camera. Measuring the range shift of high energy proton beam is more challenging, since the neutron background is significantly increased and the fall-off of the detection profile at Bragg peak

88 64 Preliminary experimental results and definition of the specifications for the new detector depth is less steep. The efficiency of the energy selection system at cyclotron exit was this time purposely reduced in order to produce a stable proton beam current of the order of only 1 pa at nozzle exit not to saturate the camera. The current values are 1 times lower than maximum clinical values. The number of protons delivered was recorded with a large parallel plate ionization chamber intercepting the beam Energy calibration and data treatment to obtain prompt gamma profiles Energy calibration of the detector was realized with 6 Co and 22 Na sources, as well as with the activity of the LYSO crystal. The calibration equation was based on the mean of the centroid of the measured 1.17 and 1.33 MeV photopeaks of 6 Co spectrum and the 597 kev peak of LYSO spectrum. It was then checked that this calibration was consistent with the bump resulting from the 1.27 MeV peak of 22 Na. After the energy calibration, a hardware threshold was set to discard events below.8 MeV. During profiles acquisitions, all the events above the hardware threshold were detected and analog to digital conversion was performed on the amplitude of the signal corresponding to each event. Data corresponding to events out from the 3 6 MeV energy range were discarded off-line and a set of advanced filters was applied to improve image quality by discarding events whose position and energy could not be reconstructed accurately. For each beam energy, more than one acquisition was necessary to obtain the desired profile. The profile reconstruction was done in the following steps: A first acquisition was made without collimator in order to give a uniform irradiation to the scintillator and use the profile as uniformity map. A second acquisition was made with the closed collimator. This was made to acquire only uncorrelated signal including neutrons and the secondaries they produce in the collimator, as well as radiations scattered in the treatment room. Prompt gammas are indeed stopped by the collimator. A final acquisition was performed with the open collimator (knife-edge configuration) to select both uncorrelated and correlated contributions. The closed collimator acquisition was subtracted from the open collimator contribution and the obtained profile normalized to the uniformity flood acquired without the collimator.

89 4.1 Measurements on a first slit camera prototype 65 For each configuration of the collimator three acquisitions were made with the camera in the three positions ( 4 cm, cm and 4 cm) to cover the total FOV. A long irradiation time of 45 s was necessary to obtain a sufficient statistics at very low beam current Measured profiles 7 x MeV: collimator open - 4 cm mm + 4 cm x MeV: collimator open - collimator closed Counts [a.u.] Counts [a.u.] X [mm] x MeV: collimator open X [mm] Counts [a.u.] Counts [a.u.] X [mm] x MeV: collimator open - collimator closed X [mm] x MeV: collimator open 3 x MeV: collimator open - collimator closed Counts [a.u.] X [mm] X [mm] Figure 4.2 Detection profiles measured with the camera centered at the expected range depth at 1 MeV, 16 MeV and 23 MeV before (left) and after (right) uncorrelated contribution subtraction. The acquisition in the three different positions of the camera are depicted with different colors. Measurements were realized with a continuous proton beam current of 4 pa at nozzle exit at 1 MeV, 2 pa at 16 MeV and 14 pa at 23 MeV.

90 66 Preliminary experimental results and definition of the specifications for the new detector Profiles measured with the camera centered at the expected range depth are given in figure 4.2. The acquisitions in the three different positions of the camera (-4 cm, centered and +4 cm) are displayed in different colors (red, blue and green respectively). On the left column, the acquisition with the collimator open is displayed. The plots show that the uncorrelated background grows with the beam energy. On the right column, the prompt gamma contribution is isolated after the subtraction of the acquisition made with the closed collimator. Profiles are more sharpened at low beam energies because of the more favorable gamma-to-neutron background x mm mm +1 mm +2 mm +3 mm +5 mm +1 mm Counts [a.u.] X [mm] Figure 4.3 Zoom on the detection profiles measured at 23 MeV as the target is moved along the beam axis to induce the detection of range shifts by the camera. A polynomial fitting was applied to the profiles to better appreciate the shifts. The ability of the camera to detect shifts of the proton beam range in the target was evaluated at 23 MeV, which is the most challenging condition. From the expected range depth ( mm), the target was then shifted by 1, +1, +2, +3, +5 and +1 mm along the beam axis. The measured profiles were fitted with polynomials as shown in figure 4.3. By eye inspection, we can distinguish the profiles: the shifts of the target produce the corresponding shifts of the detection profile. The +3 mm profile shows a different trend with respect to the others, that was not understood. We cannot exclude the possibility of an experimental mistake for this particular measurement.

91 4.2 Definition of the specifications Definition of the specifications Setup geometry and crystal volume The design of the new gamma detector is based on a reference setup whose schematic is shown in figure 4.4. Differently from the adopted setup for the first characterization measurements (see paragraph 4.1.2), the collimator is placed 25 cm, instead of 15, away from the beam axis for clinical reasons. In fact, a distance of 15 cm between the patient and the slit camera is too low for clinical application. The 1:1 geometry (where the target and the scintillator are at the same distance from the collimator) was replaced by a 4:5 geometry (where the two distances are in a 4/5 ratio), in order to have a 1 cm field of view (FoV) on the target projected on an 8 cm wide scintillator. This was made to reduce the size of the scintillator, hence the size and the weight of the collimator with an advantage in terms of overall costs. The scintillator detector will be divided in vertical segments corresponding to position bins along the beam axis. Events detected in the slabs will be scored to get a 1D detection profile. Target Slit collimator Scintillator d1 1 cm = 25 cm d2 = 2 cm 8 cm Figure 4.4 Top view of the reference solution consisting of the target, the slit collimator and the detector in the 25:2 geometry. The crystal volume calculation was based on data from [13], where a 1 2 mm accuracy was measured for a dose as low as 15 cgy, which is a reasonable value for a single spot in a realistic treatment [52]. This value refer to the setup described in paragraph 4.1.2, where the crystal volume was cm 3 and the collimator was placed half-way between the scintillator and the target, which are 3 cm far from each other. Our objective is to reach the same accuracy for the same dose (15 cgy) with the setup sketched in 4.4. The volume was calculated as follows:

92 68 Preliminary experimental results and definition of the specifications for the new detector Table 4.1 Simulated count rates per second per 1 cm 3 LYSO crystal above various hardware thresholds at maximum beam current as a function of the beam energy. Data taken from [4] Counts per second 1 MeV 16 MeV 23 MeV Above 5 ev Above 1 MeV Above 2 MeV Above 3 MeV Table 4.2 Expected count rates per second per a 5 cm 3 scintillator above various hardware thresholds at maximum beam current as a function of the beam energy. Counts per second 1 MeV 16 MeV 23 MeV Above 5 ev Above 1 MeV Above 2 MeV Above 3 MeV V olume = (V olume) ref (d 1 + d 2 ) (d 1 + d 2 ) ref (d 2 ) (d 2 ) ref 1 Efficiency (4.1) Where the reference volume is 2 cm 3, reference d 1 and d 2 are 15 cm and d 1 and d 2 are the same as in figure 4.4 (25 and 2 cm, respectively). The term Efficiency refers to the detector efficiency, i.e. the ability to count a valid event and 8% was taken as our target value. With these assumptions, we found a volume of 5 cm 3. All the considerations in the design of the new gamma detector of chapter 5 are based on this number Count rate requirements The almost immediate emission of prompt gammas during proton irradiation requires a very high count rate capability for the detector. The detection chain and data acquisition must fulfill rate specifications with a counting efficiency of 8%. Rate specifications are based on Monte Carlo simulations on a 2 cm high, 1 cm wide and 1 cm thick scintillator in the 15:15 geometry [4]. Data refer to the use of IBA Proteus 235 system using a C23 cyclotron, which delivers proton bunches every 1 ns. With C23 cyclotron, the maximum proton current at nozzle exit is limited by the electrometer of the ionization chambers in the nozzle and is reached for a proton beam current of 2.6 na

93 4.3 Improvements for a new prototype 69 at 1 MeV, 3.7 na at 16 MeV and 4.6 na at 23 MeV. The count rates calculated in [4], which are reported in table 4.2 for a unit volume of 1 cm 3, were taken as a reference and rescaled to take into account the 25:2 geometry (a lower rate is expected) and the scintillator volume of 5 cm 3 : Count rate = (Count rate) ref (d 1 + d 2 ) ref (d 1 + d 2 ) (d 2) ref (d 2 ) V olume (4.2) The rates in table 4.1 refer to the maximum beam currents and results are reported above various hardware thresholds. Even if the energy range of interest is between 3 and 6 MeV, we have to consider the events in the whole spectrum, because pile-up effect of such events can cause erroneous counts in the energy range of interest. At 23 MeV and above 5 ev, that represents the worst case scenario, the event rate on the whole camera would be 85 MHz. This value is almost two order of magnitudes higher than the measured count rate of state-of-the-art standard SPECT systems [53],[54]. The pixelation of the crystal is necessary to handle a rate of tens of MHz. The crystal will be divided in 4 segments (see paragraph 5.3.2) with a consequent reduction of the rate by a factor of 4. The readout channel of each crystal segment should be able to treat 2 MHz input rate. However, this is a very conservative estimation and the pile-up of very low energy events would not have a deep impact on profile accuracy. As a reference we consider for our design study a count rate of 1 MHz per channel. 4.3 Improvements for a new prototype Measurements with the first prototype were aimed at demonstrating the feasibility of the slit camera concept. Evaluations of the performances of the adopted solution suggest that its spatial resolution is sufficient and its counting statistic should be improved to be compatible with spots of less than 1 8 protons. HiCAM, as standard SPECT modules, is not adapted for prompt gamma imaging at clinical beam currents. We need to design a totally new gamma detector, able to reach both millimeter spatial resolution and counting statistics. Several modifications of different aspects of the design are necessary: Scintillator geometry: a thicker crystal, placed closer to the collimator could increase the statistics. Moreover, the monolithic configuration represents a bottleneck for the count rate capability. The use of a pixelated

94 7 Preliminary experimental results and definition of the specifications for the new detector crystal coupled to pixelated photo-detectors read out by independent electronic modules would help to overcome count rate limitations. Photo-detectors: The SDD mounted on the HiCAM camera have excellent properties in terms of quantum efficiency, but a drift time of microseconds. This time is not compatible with a count rate of MHz that we expect at clinical beam currents. A faster photo-detector is required. Data acquisition: measurements demonstrated that shift detection with millimeter accuracy can be obtained acquiring events in the 3-6 MeV energy range, therefore there is no need to acquire and process each event in the spectrum. After accurate calibration of the system, energy selection of the events could be handled with hardware thresholds to speed up the process. Camera footprint: the first prototype includes heavy power supply modules for SDD biasing and an external cooling system and it is not suitable for the use in clinical routine. The second prototype should be compact to be compatible with the treatment room and the patient positioning system.

95 Chapter 5 Design of the new prototype The successful prompt gamma measurements performed with a first prototype slit camera based on the HiCAM detector are the starting point for the design of a new detector, which overcomes HiCAM s count rate limitations. In this chapter, we describe the design study for a new, fully dedicated, prompt gamma detector. We first present the design options and alternatives. Then we comment the design choices for the scintillator and the photo-detector modules. In the second part of the chapter, a description of the electronics for pulse processing and the data acquisition system are provided. Finally, the mechanical assembly of the detector is illustrated.

96 72 Design of the new prototype 5.1 Design objectives and alternatives Our objective is to design a new prototype prompt gamma detector in view of performing extensive test of the slit camera concept under proton beam. Beyond the technical requirements, the design phase is driven by several factors such as: Sufficient performances for clinical use: since the proof of concept of the slit-camera had been already validated with HiCAM, we directly strive for a gamma camera compatible to the expected high rates at clinical beam currents. Cost effectiveness: the lower the cost, the higher the possibility to actual use the system with benefits in proton therapy centers. We prefer to find low-cost smart solutions to manage the high count rates, rather than the use of ultra-fast, but expensive, DAQ modules. Development speed: priority is given to a simple and clean electronic design, discarding more hazardous solutions. Engineered solutions: the prototype is desired to be as close as possible to the final solution, avoiding laboratory-oriented prototypes. Figure 5.1 Block detector configuration used in standard PET modules (left). Photograph of a typical block detector (right) [18]. Taking into account these guide-lines, we first investigated the availability of suitable modules on the market. A typical PET module adopted in most of the commercial PET scanners is shown in figure 5.1. The unit module is

97 5.2 The gamma camera architecture 73 Figure 5.2 Count rate performances of General Electric PET scanners [19]. a block detector consisting of a segmented scintillator read out by four photomultiplier tubes. A possible use of such a configuration for our purposes would be to combine several modules to reach the desired field of view and sensitivity. PET modules are 2D detectors, but we could sum the events corresponding to pixel with the same x coordinate to obtain the profile. Looking at the technical specifications of PET scanners of the three main manufactures (Philips [55], Siemens [56] and General Electric [19]) we discarded this option because standard PET modules have typical count rate capability of hundreds of khz, considering the detector and the associated electronics. This rate is 2 orders of magnitude lower than what is required by our specifications (see 4.2.2). Figure 5.2 shows the count rate performances for three PET scanners of the Discovery family produced by General Electric Healthcare [19]. The maximum rate is about 13 khz. Besides rate considerations, the modifications to adapt the modules to prompt gamma imaging could be more time-consuming than the design of a new prototype from scratch. 5.2 The gamma camera architecture Discarded the possibility to use standard PET components, we adopt the traditional configuration of radiation detectors for high energy physics, based on scintillation pulse counting, whose principles have been already discussed in chapter 3. In our particular case, we considered a pixelated scintillation crystal with a 1:1 coupling with the photo-detectors. The schematic of the camera architecture is shown in figure 5.3. The 4

98 74 Design of the new prototype Front-end board Motherboard Energy events crystal pixel 1 crystal pixel 2 crystal pixel 3 SiPM arrays Analog front-end SiPM biasing module Digital conversion from supply module crystal pixel 4 to SiPM arrays from channels 3 and 4 and front-end boards crystal pixel 4 from channels 39 and 4 SPI bus network FPGA Real-Time Processor Supply module to front-end boards Ethernet link Figure 5.3 Schematic of the gamma camera architecture. scintillator pixels convert the energy events into pulses of visible light, which are detected and transformed into current by silicon photomultipliers. The front-end electronics is based on an analog approach, where the digitization of the amplitude of the signal is performed at the end of the analog processing chain. A fully digital approach was discarded to reduce costs and development time. The digitized data from the 4 channels are collected and sent to a Field Programmable Gate Array (FPGA) on a commercial digital acquisition board (mother-board). On the same board, a real-time processor allows the bidirectional communication between the user and the camera by means of an Ethernet cable. A dedicated supply module generates the biasing voltages for the components of the front-end electronics and for a more specific photo-detector biasing module, which is designed taking into account the characteristics of the selected photo-detector. 5.3 The scintillator Scintillator material The choice of the scintillator material is a key aspect of the design of the camera with consequences on the detection efficiency, the photon to neutron count ratio, the energy resolution and the time resolution. A high density material is needed to maximize incident photon detection, while minimizing neutron detection in the 3-6 MeV energy range. For this reason, we focused on crystal scintillators, rather than on plastic scintillators. Among different crystals available on the market, we first considered three candidates: bismuth germanate (Bi 4 Ge 3 O 12 or BGO), lutetium-yittrium oxyorthosilicate (Lu 1.8 Y.2 SiO 5 :Ce or LYSO) and lead tungstate (PbWO 4 or PWO).

99 5.3 The scintillator 75 Table 5.1 Physical properties of various inorganic scintillators under consideration in the present section. Material Density Light Decay Peak Refractive Yield time wavelength index [g/cm 3 ] [ph/mev] [ns] [nm] PbWO 4 (PWO) Lu 1.8 Y.2 SiO 5 :Ce (LYSO) Bi 4Ge 3O 12 (BGO) All the other materials were discarded for different reasons that would deeply impact on the performances of the detector, such as long decay times, low density and poor energy resolution. Hygroscopic crystals, such as Lanthanum Bromide (LaBr 3 ), were discarded because hygroscopy would complicate the manufacturing of a pixelated detector. In the table 5.1 the key parameters for the three scintillators of interest (data are taken from Saint Gobain datasheets) are listed. From the comparison of these parameters we can observe that: PWO is the best among the three materials in terms of density (8.2 g/cm 3 ) and decay time (15 ns), but has a very low light yield (2 photons/mev). LYSO is less dense (7.1 g/cm 3 ) and fast (41 ns), but has very good light yields (32 photons/mev). BGO has the same density of LYSO, but the light yield is lower (9 photons/mev). However, the main drawback of BGO is the slow decay time of 3 ns, that would increase the probability of pile-up events. It is important to note that the choice of the scintillator material is not independent on the choice of the photo-detector. The peak wavelength of the scintillation light emission spectrum has to be in the region where the quantum efficiency of the photo-detector is high. The refractive index influences the choice of the optical interface between crystal and photo-detector. The final choice of the scintillator material was based on the performance evaluation of the potential counting efficiency and energy resolution. Calculations were made in ideal conditions and provided reference values for an objective comparison of the performances of the scintillators. For the count rate capability calculation, the system was modeled as paralyzable (see paragraph 3.1.4) and the events have a single exponential shape

100 76 Design of the new prototype Efficiency [%] PWO LYSO BGO Input rate [MHz] Figure 5.4 Expected performances comparison of PWO, LYSO and BGO in terms of counting efficiency. with unitary amplitude. The counting threshold was set to 3% of the height of the pulse. Using this simplification we did not take into account the integration decay constant introduced by the electronics and the fact that the events impinging on the crystal belong to a continuous spectrum instead of a single line spectrum. The counting efficiency is defined as the ratio between the recorded rate and the actual input rate and was calculated as follows: Counting efficiency = m n = ne τn n = e τn (5.1) where τ is the dead-time of the system, corresponding to the time over threshold of the pulse, and n is the input event rate on the scintillator volume. This is true for a detector whose electronic processing is based on a traditional analog chain as our case, but it could be overcome with a fully digital approach. The results of the calculation are presented in figure 5.4. Comparing the three crystals performance at 1 MHz, it is evident that BGO has to be discarded. PWO and LYSO efficiency is more than 9%, while BGO efficiency shows a steep decrease of the efficiency with the rate, which reaches only 65% at 1 MHz. The comparison of energy resolution achievable was made considering only the statistical contribution as in equation 3.2. The intrinsic resolution was neglected because we did not have sufficient data to predict it over the considered energy range. We used nominal yield from table 5.1, but we have to take into account that a loss of light is probable and will depend on the geometry of the crystal. For our preliminary estimations, the number of photo-electrons generated in the photo-detector was obtained as follows:

101 5.3 The scintillator 77 Energy Resolution [%] PWO LYSO BGO Energy [MeV] Figure 5.5 BGO. Statistical contribution of the energy resolution for PWO, LYSO and N phe = Y ield Energy α (5.2) where α is a factor that includes the quantum efficiency of the photodetector (PDE in the case of SiPM) and the geometric fill-factor at the scintillatorto-photodetector interface. We consider.25 as a reasonable value. Equation 3.2 can be rewritten as: R P oisson = 2.35 Y ield Energy α (5.3) A more precise calculation of the energy resolution, based on experimental measurements, will be given in paragraph The results of the calculation of energy resolution versus the energy are shown in figure 5.5. The energy resolutions of BGO and LYSO are below 1 % over the whole energy spectrum. On the other hand, PWO energy resolution is worse than 2 % in a huge region of the spectrum. A point to note is that the plot takes into account only the statistical contribution and the nominal light yields were considered and therefore data of figure 5.5 correspond to an ideal scenario and are useful for comparison of the three crystals on the basis of the only statistical contribution. We will experimentally verify that the actual energy resolution of the detector is much worse, because of different sources of light loss, such as crystal geometry, actual SiPM PDE and ballistic deficit (for

102 78 Design of the new prototype Figure 5.6 Spectrum of the self-activity of LYSO provided by Saint Gobain for a 1 inches diameter by 1 long crystal [2]. measured data refer to paragraph 6.3.2). Although there are not particular constrictions on energy resolution, the poor energy resolution of PWO would make the energy calibration of the crystal impossible with the use of laboratory radiation sources ( 137 Cs and 6 Co), with energy peaks below 2 MeV. The conclusion of this study is that the best candidate for prompt gamma imaging is LYSO, because it offers both high counting efficiency at 1 MHz due to its fast decay time and good energy resolution thanks to its high light yield. One possible drawback of the use of LYSO is that, being a lutetium-based scintillator,it contains the radioactive isotope 176 Lu, a naturally occurring beta emitter. 176 Lu beta decays to 176 Hf 99.66% of the time to the 597 kev excited state. This state decays with a 3 gamma ray cascade of 37, 22 and 88 kev. Figure 5.6 shows an example of spectrum acquired with a cylindrical 1 inches diameter by 1 long LYSO. The crystal absorbs nearly 1% of the beta particles. However, some of the photons escape leading to four sets of beta+gamma distributions. These four sets of beta distributions, based on which gamma rays are detected in coincidence, are identified in the spectrum. The upper energy of the spectrum is MeV, which is lower than the energy range of interest for the detection of prompt gamma profiles (3-6 MeV). In conclusion, the radioactivity of LYSO will not affect prompt gamma measurement Scintillator geometry The scintillator dimensions have influence on the camera performances and they were defined to leverage several parameters. The considerations on crystal

103 5.3 The scintillator 79 dimensioning are listed below: Thickness: critical for the statistics of the detection profile because it is approximately proportional to the detection efficiency. Using a thicker crystal gives the possibility to reduce its height, and thus also the height of the collimator and the weight of the system. However, a thicker scintillator is responsible for a more significant parallax error and of a higher count rate of detected events. Segment width: determines the intrinsic spatial resolution of the camera. Small segments offer better resolution and reduce the count rate per segment, but they also reduce the probability that a 4.44 MeV photon deposits all its energy in a single segment. The segment width also determines the number of independent channels, therefore the number of photo-detector units and electronic channels, with impact on the costs and complexity of the design. Width: fixed to 8 cm to guarantee a 1 cm FoV in the setup geometry depicted in figure 4.4. Height: not critical for the camera performances. Its dimensioning will be made to obtain a minimum volume, once set all the other dimensions. A detailed study on the dependence of the profile parameters is out of the scopes of this thesis: we started on the basis of the previous simulation study of Smeets [4]. The conclusion of this study was that we have an optimal profile with a thickness of 2 mm, but we might go up to 3 or 4 mm to improve the statistics and to reduce the height of the crystal. If we choose a thickness of 2 mm, we would need an height of 3 mm, that requires a 3 mm high collimator and it also reduces the probability that the photons of scintillation exit from the output face of the slab. A good compromise was found at 3 mm and adapted to 31.5 mm after the choice of the photo-detector. This thickness value fixed the height of the crystal to 2 mm. During his study, Smeets also commented that the collimator of the reference solution has a resolution of 22 mm, resulting from the effective slit width of 11 mm for a real slit width of 6 mm, which takes into account the penetration of 4.44 MeV photons through the slit knife edges. A too low intrinsic spatial resolution would not make sense. In application of the signal sampling theory, the width of the position bins along detector axis used to display the detection profiles should be less or equal to 1 mm, values of 4, 5 and 6 mm were found to

104 8 Design of the new prototype Visible light Pixel pitch: 4 mm 8 mm 1 mm Energy events 1 mm Visible light 31.5 mm Figure 5.7 Crystal geometry: the scintillator consists of two rows of 2 slabs with mm 3 dimensions. be the best to obtain good profiles. The definitive choice was made only after the photo-detector selection, to guarantee 1:1 coupling between the scintillator output face and the photo-detector area. The advantage of 1:1 coupling is indeed to avoid the use of light-guides that would complicate the design and increase the cost of the camera. The side of the chosen photo-detectors is 4 mm, so the segment width was fixed to this value. The final crystal configuration is represented in figure 5.7. The slabs are further divided along their height in order to have crystals 1 mm long. This configuration has several advantages. First, we improve the probability of visible light collection from the output face by reducing the number of internal reflections of photons into the crystal. Second, we half the count rate on the single channel. Finally, a symmetric design will simplify the mechanical assembly and facilitate the request for compactness.

105 5.4 The photo-detector 81 Comparison of the most common photo-detectors for scintillation count- Table 5.2 ing. Property PMT PIN APD SiPM Q.E. or PDE Gain Operational bias 1 2 V 1 V 1 2 V < 1V Mechanical robustness Low High Medium High Readout electronics Simple Complex Complex Simple Form factor Bulky Compact Compact Compact Rise time Fast Medium Slow Fast Sensitivity to magnetic fields Yes No No No 5.4 The photo-detector Comparison among available photo-detectors As already stated in paragraph 4.1, the Silicon Drift Detector (SDD) used in the HiCAM camera is unsuitable for prompt gamma imaging because its drift time of µs is not compatible with the count rate of MHz that we expect. We first investigated the most commonly used photo-detectors in nuclear medical imaging modules (PET and SPECT) whose operating principle is presented in paragraph 3.3. The ideal detector should provide a response proportional to the incident photon flux and incorporate internal gain mechanism, yielding signals of sufficient magnitude to be easily processed. It should offer nanosecond response times and broad spectral sensitivity, be robust and with low dark count rates. A comparison of the most common photo-detector is provided in table 5.2. The Photomultiplier Tube (PMT) has been the detector of choice for commercial medical imaging applications. The semi-transparent photo-cathode deposited inside the entrance window inherently limits the Photon Detection Efficiency (PDE), with typical PMTs having about 2 % at 42 nm. A gain of 1 6 is achieved at the cost of a high bias voltage of 1-2 kv, which requires the use of costly high-voltages power supplies. PMTs have low noise but are bulky and delicate due to their vacuum tube structure. They can also be adversely affected by magnetic fields. Solid state devices have many practical advantages over the PMT, and this led to the PIN (p-type semiconductor, intrinsic semiconductor, n-type semiconductor) diode being used in applications where PMTs were too bulky or delicate, or where high voltages were not possible. However, PIN diodes are severely limited by their complete lack of internal gain.

106 82 Design of the new prototype In the Avalanche Photo-diode (APD) a gain of around 1 is achieved for a bias of 1-2 V. Whilst the gain may be lower than that of a PMT, APDs have the advantage of a PDE which can be more than 65 % and also a compact size, ruggedness and insensitivity to magnetic fields. Their main drawbacks are their excess noise factor and in an important trade-off: the capacitance increases with increasing device area and decreasing thickness, whereas the transit times of the charge carriers increase with increasing thickness, implying a performance trade-off between noise and timing. In the last few years, there has been a growing interest in SiPMs, as alternative to PMT and APD for scintillator light readout [57]. The Silicon Photomultiplier (SiPM) has high gain and moderate PDE (5% is a typical value, but it depends on the structure of the device), with the physical benefits of solid-state devices such as compactness, ruggedness and magnetic insensitivity. In addition, the SiPM achieves its high gain (1 6 ) with low bias voltages (less than 1 V). Due to these traits the SiPM has rapidly gained a proven performance in the state-of-the-art medical imaging applications. SiPMs with different sizes (from 1 mm 2 to 4 mm 2 ) are available on the market and they can be grouped into custom arrays, offering an excellent scalability of the design. For all its features, first of all the compactness, SiPM was chosen as the best photo-detector for our gamma camera Photo-detector configuration Once the Silicon Photomultiplier was chosen as best photo-detector for scintillation light detection, we proceeded with the choice of the model and the design of the configuration that satisfies our necessities. The chosen devices are 3 3 mm 2 active area SiPMs with a plastic package with mm 2 dimensions (see figure 5.8), that allows 1:1 coupling with the 4 3 mm 2 crystal face if we put 7 devices in a row. The SiPMs with these features are available with three different microcell size: 25µ, 5µ, and 1µ. A typical PDE curve as a function of wavelength is shown in figure 5.8 for a device with 5µm microcells. At the peak wavelength, that is 42 nm and coincides with the LYSO one, the PDE is 5 %. The PDE for the 25µ and 1µ model can be found by rescaling the 5µ values according to the fill factor ratio and it is respectively equal to 25 % and 64 %. The choice of the model was based on some considerations about the energy range and the energy resolution achievable. Even if we want to count the energy events in the 3 6 MeV energy range, it is desirable to have a detector with a dynamic

107 5.4 The photo-detector 83 LYSO wavelength of maximum emission (42 nm) Figure 5.8 Left: package dimensions of a SiPM of the S1632 series. The active area with respect to the package area is highlighted in blue. Right: photon Detection Efficiency versus wavelength for Hamamatsu SiPMs [21]. Nfired P -5P -1P Energy Resolution [%] P -5P -1P Energy [MeV] Energy [MeV] Figure 5.9 Number of fired microcells (left) and energy resolution (right) as a function of the energy, for different SiPMs models. range up to 1 MeV. The number of fired microcells was determined using the equation 3.18 and considering a number of photons proportional to the energy, according to the scintillator light yield, as in: N fired = M(1 exp( P DE Y ield Energy/M)) (5.4) Where M is the total number of microcrells which is 18, 252 and 63 for the 25µ, 5µ and 1µ models, respectively. These numbers take into account the 7 SiPMs of one array. Results are presented in figure 5.9. The 1µ model reaches the asymptotic

108 84 Design of the new prototype 7 x 1 SiPM array NTC sensor Figure 5.1 Photograph of a PCB where two SiPM arrays are mounted. The PCB includes also a NTC sensor for temperature monitoring. value at 5 MeV and was thus discarded. The device with µm 2 microcell size has a linear trend in the whole spectrum and the -5P model shows an intermediate behavior. The statistical contribution of the energy resolution was calculated with equation 3.2, re-arranged as follows: R P oisson = 2.35 Nfired (5.5) where we considered a number of photo-electrons equal to the number of fired microcells that we calculated from equation 5.4. The 5µ model offers the best energy resolution and, because the non-linearity can be handled using an exponential calibration curve, was preferred to the 25µ device, which shows the best linearity. It has to be noted that the energy resolution in figure 5.9 takes into account only the statistical contribution and the excess noise factor (ENF) was neglected. In real conditions, we expect worse performances, due to the losses of light in the conversion chain from gamma photons to photo-electrons, which are difficult to predict at this point of the design (a quantitative study, based on experimental measurements will be given in section 6.3.3). The selected devices are arranged in rows of 7 SiPMs each on a printed circuit board (PCB), including two arrays and a negative temperature coefficient (NTC) sensor as shown in figure 5.1. A 1 mm thick sheet of optical pad (EJ-56 provided by Eljen Technologies) will be interposed between the visible light output face of the slab and the SiPMs array. EJ-56 is a silicone rubber with a refractive index of The final configuration of the SiPM arrays coupled to a crystal slab is sketched in figure 5.11.

109 5.5 The electronics 85 Figure 5.11 SiPM array configuration and coupling to the scintillator. 5.5 The electronics The function of the front-end electronics for nuclear physics applications is to acquire the electrical charge pulses generated by a radiation detector, to extract the quantities of interest and to convert them into a digital format. In most applications, the quantities of interest are: Particle energy: it is proportional to the charge generated by the SiPMs, provided that we are working in conditions which are far from the saturation of the device. Particle incidence: it is possible to determine the rate of events in a set energy range by counting the number of detected pulse within a temporal interval. Particle position: for pixelated detector is simply identified by the fired pixel position. Time of arrival: useful for ToF and coincidence measurements. Type of particle: it is possible to discriminate the type of particle on the basis of the pulse shape. This requires the use of scintillators which show a different response to the different type of particle. For our application we are interested in the three first quantities. The energy will be used for spectra reconstruction and energy calibration. After

110 86 Design of the new prototype SiPMs Preamplifier Gain Peak Stretcher ADC Energy Detector bias supply Discriminator Trigger Counter Counting Thresholds Figure 5.12 Block diagram of the acquisition system. calibration, two hardware thresholds will be set to count events in the energy range of interest and reconstruct profiles. The information on particle position, identified by the pixel, is necessary to retrieve the range position of the proton beam, based on the correlation between the prompt gamma profile fall-off and the beam penetration depth. As already discussed in the second chapter, time of flight discrimination could be a useful but not essential tool to discard the neutron contribution, and was not implemented. Another technique to discard neutron events and to reduce the uncorrelated background is pulse shape discrimination. This technique is based on the time variation of the detector response when stimulated by a gamma or a neutron [58]. Even if the concept is attractive and sophisticated, it requires scintillators with particular properties (Cs 2 LiYCl 6 is one example) and was discarded. For the current design, we select an electronic readout system based on a traditional analog chain, represented in figure With this approach, the analog to digital (A/D) conversion is performed at the end of the acquisition chain, just before the readout interface. The first stage of the chain is a charge sensitive preamplifier which integrates the signal coming from the detector, thus it converts the charge into voltage amplitude. The preamplifier should be placed as close as possible to the photo-detector. Ideally, it is just made of a simple capacitor; however, in order to avoid saturation, the integrating capacitor is put in parallel with a discharging resistor as in figure 3.16, so that the preamplifier output will have pulses with a fast rise time and an exponential decay as discussed in paragraph 3.4. The charge information (proportional to energy) is here represented by the pulse height. A gain stage adapts the amplitude of the pulse to the dynamic range of the Analog to Digital Converter (ADC). After that, the signal is split in two paths. The first goes to a peak-stretcher followed by an ADC. The second is the input of a discriminator connected to a counter for pulse

111 5.6 The camera assembly 87 Microcontroller (ADC and Counter) Peak Stretcher Discriminators Gain To the motherboard Preamplifiers Detector bias To the SiPM array board Figure 5.13 Photograph of the PCB which includes the electronics for the acquisition of the scintillation signals. One PCB is used to read out two pixels. counting. The same output of the discriminator is also used as the trigger for the start of conversion of the ADC. The electronic design includes also the detector bias supply, which is a very critical issue for SiPMs, because most of their properties depend on the applied reverse voltage. A simple network for the readout of the temperature from the NTC sensor on the SiPM arrays PCB is also present. A photograph of the PCB designed for the acquisition of the scintillation pulses is provided in figure The analog and digital sections are implemented into two different areas of the board. A microcontroller is used for the analog to digital conversion and the counting functions. On the same board, the voltage regulators for the detector bias are mounted. Two acquisition channels are mounted onto a single PCB and the two channels share one microcontroller. 5.6 The camera assembly The camera assembly follows the symmetrical and modular design of the crystal module. The drawing of the assembly of the components is shown in figure The design should be as compact as possible to be easily introduced in the treatment room. The SiPMs array are connected to 2 front-end boards (1 for each crystal row), stacked behind the crystal in the way to limit the total height of the camera to the height of the crystals. The front-end boards are connected to a back-plane board. A portion of the back-plane board includes

112 88 Design of the new prototype Back-plane board SiPMs arrays Front-end boards Power supply module Data collection and Ethernet connection Gamma rays Figure 5.14 Drawing of the assembly of the gamma camera components. In the drawing the scintillator slabs, the SiPMs arrays and all the electronic boards are shown. the power supply module and the connector to plug the digital acquisition board is soldered in another section of the same PCB. The back-plane is, in fact, both the structural and electrical connection among the 4 front-end boards. The crystals are enclosed in an aluminum box as shown in figure 5.15, which provides mechanical support and self-alignment to the slabs and shields the scintillator from ambient light. Two lateral plates are screwed to the box and used to join the detector to the collimator. The overall dimensions of the detector, including the mechanical structure is mm 3. A possible solution for the use of the camera in clinical routine is displayed in figure The camera and the collimator could be placed on a trolley that can be moved close to the patient during treatment. Such a configuration would allow the rotation of the camera according to the beam direction and the vertical and horizontal translation. The distance between the scintillator and the collimator can be regulated as needed.

113 5.6 The camera assembly 89 Connection to the collimator 245 mm 16 mm 1 mm Figure 5.15 Drawing of the configuration of the camera and the collimator for the use in clinical routine. Gamma camera Slit collimator Figure 5.16 Drawing of the configuration of the camera and the collimator for the use in clinical routine.

114 9 Design of the new prototype 5.7 Conclusion Throughout this chapter we presented the design of the detector module for prompt gamma acquisition. After this first phase of the project, the key features and parameters of the detector were fixed. Among all the commercially available scintillator crystals, LYSO was chosen because its short decay time and high light yield, that would guarantee adequate counting efficiency and energy resolution. The crystal dimensions were set to mm 3. Differently from the HiCAM camera, a pixelated configuration was chosen to handle the expected count rate in clinical conditions. The segment width was fixed to 4 mm to fit the size of the photodetector. Knowing that the SDD, exploited in the HiCAM camera, was too slow for the application of the camera in clinical conditions, we selected Silicon Photomultipliers for their fast response. The SiPM was preferred to the PMT for its compact size and low biasing voltage. A model with a 5 µm microcell size was chosen as the best trade-off between energy resolution and dynamic range. The design of the electronics was aimed at giving the best performances at the lower cost. Simple pulse counting analysis scheme was implemented instead of very expensive ultra-fast DAQ modules. The assembly of all the components was thought to be as compact as possible to be compatible to the clinical use and not only with research measurements. We avoided the use of cooling systems, choosing a smart biasing control of SiPMs and we designed a dedicated power supply module so that heavy and bulky power supply units are not necessary.

115 Chapter 6 Laboratory characterization of a prototype and of the full-size detector In this chapter we present the results of experiments conducted in Politecnico di Milano for the characterization of a small prototype and of the full-size camera with the use of low energy radiation sources. Before the development of the full-size camera, a prototype consisting of two channels has been mounted and tested to benchmark different parameters of the design, among which the surface treatment of the slabs is the most critical. Position sensitivity and count rate capability are tested and presented in this first section. Based on these results, the full-size detector, consisting of 4 channels, was mounted and characterized. Results of the characterization, including the temperature dependency and the energy resolution, are presented in the second part of the chapter.

116 92 Laboratory characterization of a prototype and of the full-size detector 6.1 Characterization of a reduced size prototype The 2-channels prototype The prototype for the experiments of the first section of this chapter features two crystal slabs read out by two SiPMs arrays, as sketched in figure 6.1. The SiPMs are mounted on the top side of a PCB. The front-end electronics is implemented on the same board. Slab dimensions, SiPMs arrays configuration and front-end electronics are the same as in the full-size detector (see paragraphs and 5.4.2), but the power supply is provided by external laboratory units. For this experiments compactness was not required. Reflectors y Front end electronics on the bottom-side 1 mm x Source entrance face Peltier cooler on the bottom-side SiPMs arrays (7 SiPMs each) Figure 6.1 3D sketch of the 2-channels prototype. SiPM arrays are mounted on the top-side of a PCB. On the bottom-side the front-end electronics is implemented. A Peltier cooler stabilizes the SIPMs temperature. The block scheme and the photograph of the setup for the prototype characterization are presented in figure 6.2. The two SiPMs array are biased with the same fixed voltage (72 V) with the use of a high voltage (HV) power supply unit. To avoid gain drifts due to temperature variations, a Peltier cooler was placed under the SiPMs. The temperature was constantly monitored during measurement with a temperature sensor Comparison between rough and polished surfaces treatments We made a test of light-collecting uniformity by allowing a narrowly collimated gamma-ray beam to strike selected portions of the scintillator crystal. As stated in section 3.5, one important contribution of worsening of the energy resolution is the non-uniform response of the scintillator within its volume. Surface treat-

117 6.1 Characterization of a reduced size prototype 93 Peltier cooler Front-end board NI acquisition board crystal pixel 1 crystal pixel 2 SiPM arrays HV module Analog front-end Supply module Digital conversion Supply module SPI FPGA Real-Time Processor Ethernet link Front-end electronics NI acquisition board SPI Bus HV Crystal pixels coupled to SiPMs arrays Figure 6.2 Block-scheme of the reduced-size prototype (Top). Photograph of the adopted setup for the prototype characterization. ment plays a crucial role in the uniformity of the response. To evaluate the best surface treatment for the proposed crystal geometry, we compared crystal with polished and rough surfaces. A 137 Cs collimated source (collimator opening of 1 mm) was used for this purpose. The experimental setup is shown in figure 6.3 and consists of the 2-slabs module and the collimated source on a x-y translator. The camera was set in a fixed position and the collimated source moved along the y direction, i.e. the height of the slab. For the acquisition of the spectra at different positions of the source along the height of the crystal (figure 6.3), the source was moved by steps of 2 mm from the central position ( mm) and spectra were acquired in - 4 mm, - 2 mm, mm, 2 mm and 4 mm positions. The spectrum resulting after the irradiation of the detector with a 137 Cs radiation source has a peak at 662 kev, which lies within the self-activity spectral region of LYSO (see paragraph 5.3.1). A first acquisition without the source was performed and subtracted from all the acquisitions. Figure 6.4

118 94 Laboratory characterization of a prototype and of the full-size detector 31.5 mm y LYSO slab (lateral view) 1 mm 4 mm 2 mm mm 137 Cs -2 mm SiPMs array -4 mm Pinhole colllimator (1 mm opening) Figure 6.3 Schematic of the experimental setup used for the position sensitivity characterization on the vertical axis Figure 6.4 Acquired spectra before (blue line) and after (red line) the subtraction of LYSO background. The Gaussian fitting curve is depicted in black. shows the result of one acquisition obtained with polished crystals before LYSO background subtraction (blue line) and after background subtraction (red line). A Gaussian fitting was then applied to the spectra after background subtraction and the position of the peak identified as the centroid of the Gaussian curve. In figure 6.5 the spectra obtained in the 5 different positions are superimposed both for the crystal with rough surface and for the crystal with polished surfaces. The spectra are normalized to the maximum of the peak, for a bet-

119 Peak position [ch] Peak position [ch] 6.1 Characterization of a reduced size prototype 95 Rough surfaces Polished surfaces mm - 2 mm mm 2 mm 4 mm mm - 2 mm mm 2 mm 4 mm Counts [a.u.].6.4 Counts [a.u.] Energy [ch] Energy [ch] Figure 6.5 Energy spectra obtained using crystal slabs with rough surfaces (left) and with polished surfaces (right) at different positions of the source along the height of the crystal. 8 Rough surfaces 12 Polished surfaces Source position [mm] Source position [mm] Figure 6.6 Plot of the position of the 137 Cs photo-peak versus the position of the source along the height of the crystal. In the case of rough surfaces, the position of the peak depends on the position of the source; for polished surfaces the position of the peak is uniform. ter comparison. Spectra obtained with the crystal with rough surfaces show a dependence of the position of the peak on the position of the source. In particular, a higher amount of light is collected by the photo-detectors if the source is closer to the output face of the crystal. On the other hand, the spectra obtained with the crystal with polished surfaces show no significant dependence on the position of the source. The position of the peaks retrieved after the Gaussian fitting are plotted versus the position of the radiation source and the plots are shown in figure 6.6. Tests demonstrate that, for rough surfaces, those areas closest to the SiPM face give rise to a larger pulse height because of more favorable light collection.

120 96 Laboratory characterization of a prototype and of the full-size detector 4 mm 31.5 mm LYSO slab (top view) x 137 Cs Figure 6.7 Schematic of the experimental setup used for the position sensitivity characterization on the horizontal axis. Totally different situation was observed with the polished surfaces where the thin crystal acts as a light guide. The physical explanation of this behavior is that, in slab geometry, the light that reaches a surface with incident angle Θ greater than the critical angle Θ c is trapped and conducted to the slab edges by total internal reflection as in a light-guide (see paragraph 3.2.4). The experiment confirmed the use of polished surface for the scintillator slabs Position sensitivity As explained in section 5.3.2, the designed detector is a 1-dimensional system which offers position sensitivity along its width (x-axis of figure 6.1). In a pixelated configuration, the position of interaction is identified by the fired pixel, if we ideally assume that a single energy event release all its energy within a single pixel. Although, there is a certain probability that a single event releases part of its energy in the neighboring slabs. The aim of the measurements described in this section is to analyze the imaging capability of the camera. The experimental setup used for the experiment is illustrated in figure 6.7: the radiation source is now translated on the x axis of the linear stage. For the verification of the position sensitivity of the pixelated configuration, the

121 Counts Counts [a.u.] 6.1 Characterization of a reduced size prototype Range of interest Energy [ch] (a) Before background subtraction After background subtraction Channel 1 Channel Source position [mm] (b) Figure 6.8 (a) Energy spectra of 137 Cs before and after the LYSO background subtraction. The energy range into which the events are counted is highlighted in green. (b) Point Spread Functions of the two channels. Each point corresponds to the number of totaled counts in the range of interest for each position of the source along the x-axis of the system. The ideal PSF are marked with dashed lines. camera was operated in counting mode. The detection thresholds were set in order to select the events around the 137 Cs photo-peak (1% of the height, as shown in figure 6.8(a)). The collimator hole was aligned with the center of the height of the slabs ( mm position of figure 6.3), and moved along the x-axis by steps of 1 mm. For each position of the source, the number of counts between the two energy thresholds was acquired. The number of counts for each position was normalized, to have the percentage of counts with respect to the maximum number of counts in both channels. The point spread function (PSF) of the two pixels is shown in figure 6.8(b). As expected, the maximum of the curves corresponds to the position of the source aligned with the center of the slab. The Full Width at Half Maximum (FWHM) of the Gaussian fitting of the curves is 4.19 mm for the first channel and 4.29 mm for the second channel. In a pixelated imaging system, the PSF of each pixel should ideally be a rectangle, as marked with dashed lines in the figure. However, in real conditions there is a non-zero probability that some events release a fraction of energy also in the neighboring slab. This justifies the recorded Gaussian shape of the PSF. Nevertheless, we can conclude that the slab configuration has sufficient spatial resolution if compared to the effective slit collimator resolution of 11 mm.

122 98 Laboratory characterization of a prototype and of the full-size detector Threshold τ1 τ2 Figure 6.9 Illustration of the pile-up of two events. The events that occurs during the dead time of the first one extends the dead time by another period τ Count rate performances Setup and methods As already stated in paragraph 5.3.1, our system can be modeled, at first order, as a paralyzable system because, in counting mode, the dead time is equivalent to the time-over-threshold of the pulse. Figure 6.9 is an illustration of what happens in our detector when one event occurs during the dead time of the previous one. For a paralyzable model the recorded count rate is given by: m = ne nτ (6.1) where m is the recorded rate, n is the true interaction rate and τ is the system dead-time. In the particular case of prompt gamma imaging, the energy spectrum is continuous and the events have different amplitudes. The dead-time cannot be found a priori knowing the parameters of the system because the time-overthreshold varies with the amplitude of the pulse. For the experiments described in the next paragraph, we will consider a single-line spectrum Experimental results The aim of this experiment was the characterization of the efficiency of the counting section of the electronics, independently from the spectral distribution of the events. The main components of the experimental setup are presented in figure 6.1. We used a Digital Detector Emulator (CAEN DT58 [61]),

123 6.2 Count rate performances 99 Power supply unit Detector emulator Front-end board sbrio Figure 6.1 Experimental setup for the measurement of counting efficiency. The setup consists of a detector emulator as the input of a front-end board, which is biased by a laboratory supply unit. The board is connected to the NI sbrio which collects data and sends them to the PC. Output rate [MHz] Measured data Input rate [MHz] (a) Paralyzable model equation Efficiency Efficiency (@ 1 MHz) = Input rate [MHz] (b) Measured data Paralyzable model equation Figure 6.11 Number of totaled counts in 1 s by the counter of the front-end board of the camera versus input rate (a). Counting efficiency of the counter at different input rates (b). The pulses correspond to a single energy line. which substituted the scintillator-sipms system, as input of the front-end electronic boards. The instrument synthesizes a stream of pulses according to the parameters settings given by the user: the pulses emulate the output signals of the SiPMs arrays. The pulses have exponential shape with the decay time constant of LYSO (41 ns) and they follow a temporal Poisson distribution. For our experiment we emulate a single energy line. The amplitude of each pulse was constant and was tuned to have 3.3 V wide pulses at the output of the gain stage of the electronics. The threshold was set to 1.1 V. In figure 6.11 the results of the experiment are shown. The graph on the

124 1 Laboratory characterization of a prototype and of the full-size detector left is the plot of the totaled counts during 1 s acquisition versus the input rate. The blue line corresponds to the paralyzable model equation (equation 6.1). On the right of the same figure, the efficiency of the counting system is presented, calculated as the ratio between the totaled counts and the expected number of counts. An efficiency of.83 was obtained with an input rate of 1 MHz. The dead-time of the system is mainly due to the time-over-threshold of the incoming events, which, in these particular conditions (single line energy events and single threshold) is equal to 195 ns. The experiment confirmed that the electronics satisfies the minimum requirements in terms of count rate capability.

125 6.3 Characterization of the full-size camera Characterization of the full-size camera The camera Following the perspectives opened by the characterization of the reduced-size prototype and of the electronics, the full-size camera (consisting of 4 channels) was mounted and tested in Politecnico di Milano before the use for prompt gamma imaging. Figure 6.12 Left: back view of the gamma camera with the front-end and backplane boards. Right: front view of the camera with the aluminum case including the crystal slabs. Figure 6.12 shows two different views of the camera. On the left, the view from the backside is presented, where the backplane including the power supply module is visible. Flat-cable connectors are used to plug each front-end board to the backplane. On the right side, the scintillator aluminum case is shown. Figure 6.13 illustrates the arrangement of the crystal slab inside the aluminum case. As discussed in paragraph 6.1.2, the crystal slabs have all the surfaces mechanically polished so that they act as light guides. Black absorber sheets are placed between slabs and between slabs and the box walls. A specular reflector is present only on the opposite face to the output one. Figure 6.14 shows the SiPMs arrays in their holder, which guarantees the alignment of the arrays to the crystal surfaces.

126 12 Laboratory characterization of a prototype and of the full-size detector Figure 6.13 Crystal slabs assembly inside the aluminum box. The slabs are separated by black absorber sheets. Figure 6.14 holder. Arrays of Silicon Photomultipliers for scintillator light read out in their kev kev Counts Energy [ch] Figure 6.15 Spectrum of the self activity of LYSO acquired from one of the slab of the gamma camera Gamma spectroscopy and energy resolution We performed gamma spectroscopy measurements of the self-activity of LYSO and during the irradiation of the camera with not collimated 137 Cs and 6 Co ra-

127 6.3 Characterization of the full-size camera Counts FWHM = ±.6 % Energy [ch] Figure 6.16 Energy spectrum of 662 kev gamma rays from 137 Cs source and corresponding Gaussian fitting. diation sources. The measurement conditions were far from what we expected during prompt gamma imaging in terms of count rate and energy range. Nevertheless, measurements provided a first experimental validation of the full system. Figure 6.15 illustrates the self activity of LYSO acquired from one of the slabs of the gamma camera, with an hardware threshold of 1 ch to discard the events due to the dark count of SiPMs. The shape of the spectrum is different from the one provided by Saint Gobain and presented in figure 5.6. This could be due to several factors, such as the geometry of the crystal and the fact that a single slab is surrounded by other crystals. Figure 6.16 and Figure 6.17 show the spectra acquired irradiating one slab with 137 Cs and 6 Co sources. The energy resolutions for this channel are 13.75±.6%, 9.2 ±.13% and 8.4 ±.1% at 662 kev, 1173 kev and 1335 kev, respectively. The spectra for all the 4 channels are displayed in figures 6.18 and 6.19 for 137 Cs and 6 Co. The energy resolutions are plotted in figure 6.2. The error bars are within the data markers.

128 14 Laboratory characterization of a prototype and of the full-size detector 2 FWHM = 9.2 ±.13 % 15 FWHM = 8.4 ±.1 % Counts Energy [ch] Figure 6.17 (Left) Energy spectrum of 1173 kev and 1335 kev gamma rays from 6 Co source and corresponding Gaussian fitting Figure 6.18 Energy spectra obtained irradiating the camera with a 137 Cs radiation source for the 4 independent channels of the camera.

129 6.3 Characterization of the full-size camera Figure 6.19 Energy spectra obtained irradiating the camera with a 6 Co radiation source for the 4 independent channels of the camera.

130 16 Laboratory characterization of a prototype and of the full-size detector Energy Resolution FWHM [%] kev Peak position [ADC channels] Energy Resolution FWHM [%] Energy Resolution FWHM [%] Channel kev Channel 1335 kev Channel Peak position [ADC channels] Peak position [ADC channels] Channel Channel Channel Figure 6.2 Left: Energy resolutions FWHM of the 4 channels at the three energy lines of 137 Cs (662 kev) and 6 Co (1173 kev and 1335 kev). Right: peak positions (ADC channel) at the three energy lines measured as the centroid of the Gaussian fitting of the photo-peaks.

131 6.3 Characterization of the full-size camera Light yield estimation and preliminary energy calibration From the arguments of paragraph 3.5, the finite energy resolution of any detector may contain contributions due to the separate effects of charge collection statistics, electronic noise, variations in the detector response over its active volume, and drift in operating parameters over the course of the measurement. As already stated in paragraph 3.5, in a system consisting of a scintillator coupled to silicon photomultipliers, the main contributions to energy resolution are the statistical contribution and the intrinsic scintillator contribution. The energy resolution can be written as: ( E/E) 2 = δsc 2 + (2.355 ENF/P HE) 2 (6.2) A precise calculation of the intrinsic energy resolution can be made by the subtraction of the contribution of the photo-electron statistics to the energy resolution E/E that can be found after the Gaussian fitting of the full energy peaks of the measured spectra. The number of photoelectrons can be determined by relating the gamma peak to the single photo-electron peak. The single photo-electron peak can be identified by illuminating the SiPM array with a very weak source of pulsed light [49]. Unfortunately we did not have available the instrumentation for such measurement and we relied on data from literature. We considered 8% intrinsic energy resolution for LYSO crystal at 662 kev as reported in [62] and an ENF of 1.5 measured on Hamamatsu SiPM by [49]. Using the parameters found from the acquired spectrum of 137 Cs, equation 6.2 can be rewritten as: (.138) 2 = (.8) 2 + ( /P HE) 2 (6.3) From this formula, we found 655 photoelectrons at 662 kev, that results in a light yield of 99 PHE/MeV. The number of produced photons can be estimated taking into account the losses that happen during the conversion chain from visible light to charge that can be summarized as: Fill-factor: the active area of each SiPM is 3 3 mm 2, while the package dimensions of the device are mm 2. No light guides are used to focus the scintillation light to the SiPM active area: 5% of the light is loss in the dead-area of the SiPM.

132 18 Laboratory characterization of a prototype and of the full-size detector 6 55 y =.42x Energy [ch] Energy [kev] Figure 6.21 Energy calibration curve for one channel, resulting from the peaks of 137 Cs and 6 Co. Photon Detection Efficiency (PDE): at the wavelength of maximum emission of LYSO (42 nm), the PDE is about.5. Ballistic deficit: the time constant of the first stage of the electronics was set to 1 ns to prevent pulse pile up at high rates. This value is only 2.4 times the scintillator decay time (41 ns). The short duration of the pulses comes at the price of a reduced amount of photoelectrons integrated by the preamplifier. With our dimensioning the ballistic deficit is 53%. Considering all this sources of light loss, and the linear response of the SiPM for a low number of photons, we can estimate a light yield of 88 ph/mev. This value is 3.6 times the nominal value (32 ph/mev). This difference is not surprising considering the geometry of the crystal that was dimensioned to favor the spatial resolution at the expenses of the energy resolution. It must be noted that this is a first order estimation which is based on low energy spectra (662 kev) and does not take into account the variation of LYSO energy resolution with energy. Results obtained from spectroscopy with laboratory radiation sources allowed a first order energy calibration at low energies. The centroids of the Gaussian curves resulting from the fitting on the acquired spectra were plotted versus the energy of the source as shown in Figure For these energies the response of the detector is still linear and the linear regression can be found for a preliminary calibration of each channel. We observed a conversion factor of.42 ch/kev. If the SiPM arrays had a linear behavior, the dynamic range

133 6.4 Conclusions 19 would be about 1 MeV, sufficient to cover the prompt gamma spectrum. In real conditions, we expect a saturation of the SiPM response for the amount of light corresponding to prompt gamma energies (3 to 6 MeV). 6.4 Conclusions Results presented in this chapter encouraged the use of the camera for prompt gamma imaging. A polishing treatment on crystal surfaces guarantees a uniform response of the slab irradiated at different positions along its height. Measurements with a collimated source indicate that the slab geometry can provide sufficient spatial resolution on the horizontal axis. At the same time, tests were a useful tool to verify the correct operation of the camera both as a MCA analyzer for spectra acquisition and in counting mode for point spread function reconstruction. The count rate capability of the electronics was tested with a radiation emulator that reproduced an irradiation corresponding to a single energy line. Even if this case is too simplistic and far from the real situation of a continuous energy spectrum, the tests demonstrated that the minimum requirements of 8% efficiency for 1 MHz pulses are satisfied. The full-size camera was then mounted and fully characterized. The 4 channels were calibrated in order to give a spectral response which is independent on temperature. The average energy resolutions at 662, 1173 and 1335 kev are about 13%, 9% and 8%, respectively. The first order linear calibration revealed that an energy range of 1 MeV could be achieved.

134 11 Laboratory characterization of a prototype and of the full-size detector

135 Chapter 7 Experimental measurements of prompt gammas during proton irradiation In the present chapter we describe the tests of prompt gamma imaging with the designed detector in a slit camera system. We observe the influence of various parameters on the accuracy of the detection profile, irradiating an homogeneous target. Such parameters include the distance of the target from the beam, the beam energy, the energy window and the target composition. Measurements of the entrance point and of target shifts are presented as well. We investigate the effect of inhomogeneities by irradiating targets with cavities with a 2D map of pencil beams. Finally we present the very first results of profiles acquisitions during the delivery of a realistic treatment on an anthropomorphic phantom.

136 112 Experimental measurements of prompt gammas during proton irradiation 7.1 Prompt gamma acquisitions on PMMA targets Experimental setup Measurements were performed at the West German Proton Therapy Center Essen (WPE). The experimental setup is shown in figure 7.1. Proton pencil beams from 1 to 23 MeV were delivered along the axis of the cylindrical PMMA target. The target has a radius of 7.5 cm and a length of 2 cm or 4 cm according to the beam energy. The tungsten alloy collimator (16.96 g cm 3 with 9 % W,6 % Ni and 4 % Cu) was located 25 cm away from the beam axis, and 2 cm away from the camera. The collimator has 4 cm thickness, 63 slit angle, 6 mm slit width, 12 cm height and 16 cm length along the beam axis for each block. The camera and the collimator were centered at the expected beam range depth at each energy. Measurements with the closed collimator were also realized by joining the right-angled faces of the two tungsten blocks, resulting in a tungsten wall. For each acquisition, the number of protons delivered was recorded with a large parallel plate ionization chamber intercepting the beam Measured spectra and energy calibration The first objective of measurements was to perform accurate energy calibration at high energies (up to 6 MeV). We first irradiated a cylindrical aluminum target (4 cm radius) to observe the peaks resulting from the decay of 22 Na. 22 Na disintegrates predominantly to the 1275 kev level of 22 Na. The main transition (99.939%) has a maximum energy of 1393 kev and populates the 4123 kev level of Mg-24. This process is followed by two gamma rays in a cascade (2754 and 1393 kev) which lead through the 1368 kev level to the ground state of Mg-24. Due to the high transition energies internal pair formation takes place [63]. Figure 7.2 shows the acquired spectrum from a single channel. The energy is displayed on the x-axis as calculated according to the calibration with 6 Co and 137 Cs (see figure Energy peaks were identified thanks to the table of gamma emissions (table 7.1) of 22 Na. Two peaks and a weak bump are visible and they were interpreted thanks to the first order calibration at low energies discussed in The first peak corresponds to 1368 kev and the bump in the final part of the spectrum was interpreted as the 2754 kev peak. The second peak was reasonably explained as the sum of the 511 kev and 1368 kev peaks. All the other peaks listed in the table are not visible in the spectra. Spectra were then measured in the whole range of the ADC irradiating PMMA and water targets with a 1 MeV proton beam. Acquisitions were

137 7.1 Prompt gamma acquisitions on PMMA targets 113 Proton beam Tungsten Slit collimator Gamma camera 1 cm 25 cm 2 cm 8 cm Gamma camera Tungsten Slit collimator PMMA Target Figure 7.1 Top: schematic of the experimental results for prompt gamma imaging measurements. Bottom: photograph of the experimental setup for the test session at the WPE. The setup consists of a cylindrical PMMA target, a tungsten slit collimator and the gamma detector in the 25:2 configuration. realized during 18 s with a beam current at nozzle exit of about.3 na not to saturate the electronics operated in MCA mode, whose maximum rate is 5 khz. Measurements were realized in two steps: without collimation to acquire all the particles escaping the target and with the collimator closed, to isolate the uncorrelated contribution, mainly due to neutrons. Acquired spectra are plotted in figure 7.3, where the acquisitions with the collimator closed and without the collimator are depicted in green and blue, respectively. The subtraction of the two spectra is shown in figure 7.4. After this subtraction, the spectra include particles that reach the detector when the tungsten wall is absent, but not when it is present. These difference spectra take profit that photons are more absorbed than neutrons in tungsten to reinforce the proportion of gammas with respect to neutrons. The photon detection efficiency

138 114 Experimental measurements of prompt gammas during proton irradiation Counts 1 3 Counts Energy [kev] Energy [kev] Figure 7.2 Detector response to gamma emissions from an activated Aluminum target. On the left the whole spectrum is shown. On the right a zoom of the spectrum around the energy peaks of interest is presented. The energy peaks are identified by red bars. Table 7.1 Gamma Emissions of 22 Na Energy [kev] Photons per 1 disint. γ ± (11) γ4, 3 (Mg) 996(6).123(27) γ1, (Mg) 1368(5) (5) γ2, 1 (Mg) 2754(5) (8) γ3, 1 (Mg) 2869(5).24(3) γ4, 1 (Mg) 3866(5).56(7) γ3, (Mg) 4237(5).84(1) 1 7 PMMA 1 7 Water Counts / proton No collimator Collimator closed Counts / proton No collimator Collimator closed Energy [kev] Energy [kev] Figure 7.3 Spectra measured for 1 MeV protons without collimator and with the closed collimator for the PMMA target (left) and the water bottle target (right). of the thin LYSO slab is poor, nevertheless weak bumps in the spectra can be interpreted thanks to the list of nuclear de-excitation gamma rays reported in

139 7.1 Prompt gamma acquisitions on PMMA targets x Water PMMA Energy [kev] Figure 7.4 Subtraction between the spectra acquired without the collimator and the spectra acquired with the collimator closed for water and PMMA targets. Measured gamma peak energies are marked with a bar. Table 7.2 Energy and interpretation of the peaks in the spectrum at 1 MeV without collimator (based on Kozlovsky). Peak energy (MeV) 3.42 = = = Interpretation 12 C(p,p*) 12 C* 16 O(p,x) 12 C* 12 C(p,sp) 11 B* 19 O(p,p*) 16 O* [3]. Identified peaks are marked in figure 7.4 and listed in table 7.2. In the spectrum, single- and double-escape peaks are visible for the 4.44 MeV peak and the double-escape peak is visible for the MeV peak. It should be noted that the energy on the x-axis is displayed as calculated according to the linear calibration with 6 Co and 137 Cs, which is not ideal for measurements in the to 1 MeV energy range. This first order calibration helped in the identification of high energy peaks, but a new calibration was performed considering an exponential characteristic, that takes into account the saturation of SiPMs microcells with large amounts of light (see paragraph 3.3.3) according to: En(ch) = a(1 e ben(kev ) ) + c (7.1) The coefficients a, b and c were deduced by the experimental data. Figure 7.5 shows the energy calibration curve obtained using the points

140 116 Experimental measurements of prompt gammas during proton irradiation 22 Energy [ch] Linear calibration Exponential calibration 3418 kev 2754 kev 517 kev kev kev 1335 kev 1173 kev Energy [kev] Figure 7.5 Comparison between the linear energy calibration performed with 137 Cs and 6 Co radiation sources and the exponential calibration performed with energy peaks resulting from activated aluminum and irradiated water target. identified in the different spectra. The solid line is the exponential characteristic that fits all the data, while the dashed line is the linear fitting of the first three points. As predicted, the exponential fitting of data is necessary to perform accurate calibration at the energies of interest. The calibration was performed independently for the 4 pixels, to take into account variations among the channels Data treatment for profiles acquisition After the energy calibration, the camera was switched to pulse counting mode of operation and two hardware thresholds were set to discard the events below 3 MeV and above 6 MeV. For each channel, the number of counts above the higher threshold was subtracted from the number of counts above the lower threshold and the profile reconstructed as the histogram of the totaled counts for each crystal slab. Most acquisitions were performed for 1 seconds in order to have excellent statistics for a much higher dose than in practice. This was made to observe the uniformity in disregard of statistical considerations. As reported in 6.3.2, the 4 channels responses are not identical to one another. A perfect uniformity could be reach only with a perfect energy calibration, which is very challenging

141 7.1 Prompt gamma acquisitions on PMMA targets x Collimator closed Raw profile Smoothed profile 7 x Collimator open Raw profile Smoothed profile Counts / proton Counts / proton Detector axis [cm] Detector axis [cm] Figure 7.6 Comparison between a profile before (blue line) and after (red line) smoothing. The profile was acquired with a beam energy of 16 MeV and with the collimator closed (left) and open (right). using spectra without well-defined peaks as the ones presented in figure 7.3. A correction by means of a uniformity map would require always having the exact same energy spectrum for the uniformity map than for the profile to be corrected and was not performed. A 2 mm Gaussian smoothing was applied to all profiles. This smoothing, in addition to removing statistical noise, was so far found to be the most practical solution for efficient uniformity correction. With this smoothing, no significant information is lost since the collimator geometric resolution is not better than 2 mm (see 5.3.2). Figure 7.6 shows the comparison between a profile before and after smoothing. On the left, an acquisition performed with the collimator closed is shown; on the right smoothing is applied to a profile acquired with the collimator open Profile accuracy The accuracy was evaluated with a different method with respect to the one described in section The accuracy calculation was based on the fact that at first order a range error results in a shift of the profile along the beam axis. To characterize the shape of a prompt-gamma profile, we use a profile with high statistics as a reference. For our experiment, the reference profile is a 1 s long acquisition where approximately 1 11 protons are delivered. In clinical practice, the reference profile would be a simulation. For clinical use, a variable of major interest is the accuracy that the camera could achieve for a given number of protons delivered to a dose spot. To gene-

142 118 Experimental measurements of prompt gammas during proton irradiation Counts/proton 1 x 1 6 x protons Counts/proton protons Counts/proton Detector axis [cm] protons protons Counts/proton Detector axis [cm] Detector axis [cm] Detector axis [cm] Figure 7.7 Detection profiles re-sampled for different number of protons. rate sample profiles with different levels of dose, we first rescaled the reference profile for different number of protons and then added Poisson noise as shown in figure 7.7. The Gaussian smoothing with 2 mm FWHM was applied both to the reference profile and to the noisy profiles. The range retrieval between the reference and the noisy curves was made on the basis of a root-squared difference minimization. The reference function was shifted along the camera axis with a step of.2 mm. For each shift of the reference profile we calculated the integral of the square root of the difference between the profile and the shifted reference profile. The best match is the one that minimizes this sum and the shift corresponding to this match is the shift between the two profiles. Ideally, in absence of noise, we should retrieve a shift of mm with any deviation corresponding to the error. For each level of dose, the retrieval was performed 1 times with different occurrences of Poisson noise, to obtain an high statistics. We calculated the standard deviation of the error distribution and considered 2σ as estimator of the precision of the system. Since the precision is proportional to the inverse of the square root of the number of protons, in the log-log graph precision versus number of protons

143 7.1 Prompt gamma acquisitions on PMMA targets Precision 2σ [mm] 1 2σ = 4 mm Number of gammas 1 x x x x x 1 9 Number of protons Mean counts per slab x x x x x 1 9 Number of protons Figure 7.8 Top: range retrieval precision versus the number of protons. Bottom: number of detected gammas versus the number of protons. shown in figure 7.8, the precision is a straight line with slope -1/2. To reach a practical conclusion for the clinical use of the camera, the accuracy has to be seen in relation to a realistic dose delivered to a spot of the treatment plan. The order of magnitude of protons per spot for the distal layer is around 1 8 and so we use as parameter for accuracy the number of protons needed to reach a precision (2σ) inferior to 4 mm Profiles at different beam energies To observe the influence of beam energy on the detection profile, we irradiated the target at therapeutic proton beam energies from 1 MeV to 23 MeV, which cover the desired application range of the system. For each energy, the target was shifted at the expected beam range (Table 7.3, data taken from [22]) along the beam axis. Measurements were performed at clinical beam currents of na, according to the energy of the beam. In figure 7.9 acquired detection profiles, normalized to the number of delivered protons, are plotted. For a constant number of incident protons, the quality of the profiles deteriorates at high energies due to the less favorable signal to noise ratio. It is clearly visible that the baseline (relative to the uncorrelated contributions) increases with the energy, while the peak is reduced and the profile is less sharpen. The main reason of this degradation of profile shape is that the neutron flat contribution increases quicker than the photon correlated

144 12 Experimental measurements of prompt gammas during proton irradiation Counts / proton Counts / proton Counts / proton Counts / proton x MeV x 1 6 x 1 6 Detector axis [cm] 138 MeV Detector axis [cm] 177 MeV Counts / proton x MeV Detector axis [cm] Detector axis [cm] Detector axis [cm] x 1 6 x MeV 4 23 MeV Detector axis [cm] Counts / proton Counts / proton Counts / proton x MeV x 1 6 Detector axis [cm] 194 MeV Detector axis [cm] Figure 7.9 Detection profiles for therapeutic proton energies. contribution when the beam energy is raised. Moreover, the greater neutron yield at high beam energy increases the production of photons by neutrons interacting in the tungsten collimator as already verified with simulations [4]. For each energy we found the precision for different levels of dose with the method described in The log-log plots are presented in figure 7.1. The accuracy for each energy is plotted in figure At the maximum energy (23 MeV) protons guarantee a mean error inferior to 4 mm, going down to 1 MeV this number decreases by a factor of 5. Results show that a

145 7.1 Prompt gamma acquisitions on PMMA targets 121 Table 7.3 from [22]. Projected range in PMMA for therapeutic proton energies. Data taken Beam energy (MeV) Range in PMMA [cm] Precision [mm] mm.3 x MeV MeV Precision [mm] 4 mm 1.4 x x x x x x 1 9 Number of protons 1 x x x x x 1 9 Number of protons Precision [mm] mm 138 MeV.5 x 1 8 Precision [mm] mm.6 x MeV 1 x x x x x 1 9 Number of protons 1 x x x x x 1 9 Number of protons Precision [mm] MeV 4 mm.8 x 1 8 Precision [mm] MeV 4 mm.9 x x x x x x x x x x x 1 9 Number of protons Number of protons Precision [mm] MeV 4 mm 4 mm Precision [mm] 23 MeV x x x x x x x x x x x x 1 9 Number of protons Number of protons Figure 7.1 Precision for different levels of dose. The number of protons needed to achieve a 4 mm precision is marked with a red line. higher number of protons is needed to reach the desired accuracy as the beam energy increases Profiles at different distances from the target During measurements with the first slit camera prototype exploiting the Hi- CAM camera and presented in paragraph 4.1, the distance between the beam axis and the center of the collimator was kept constant to 15 cm. In this second

146 122 Experimental measurements of prompt gammas during proton irradiation x 1 Number of protons to reach 4mm precision Beam Energy [MeV] Figure 7.11 Number of protons needed to reach a 2σ precision of 4 mm for different beam energies. For comparison to the order of magnitude of a therapeutic spots, this number was divided by 1 8. prototype, the distance was set to 25 cm for clinical reasons. The consequence of a larger distance is the diminution of the counting statistics: the count rate is inversely proportional to the square of the distance. We can observe the effect of distance on the detection profiles in figure We compared profiles in the 25:2 geometry to acquisitions where the collimator was placed 22 cm away from the target, keeping the 4:5 geometrical ratio between the collimatordetector distance and collimator-target distance. As expected, the count rate is higher in the 22:17.6 geometry, but seems that the ratio between the peak and the baseline is the same. On the right column of figure 7.12, we rescaled the profiles acquired in the first configuration for a factor of 1.2 at 1 and 16 MeV and 1.4 for 23 MeV and, after rescaling profiles are pretty coincident. This result suggests that increasing the distance between the camera and the target represents a good method for count rate reduction with almost no deterioration of the profile s shape.

147 7.1 Prompt gamma acquisitions on PMMA targets 123 x MeV 22 : 17.6 geometry x MeV Counts / proton : 2 geometry (1) Counts / proton.6.4 x Detector axis [cm] Detector axis [cm] x MeV x MeV Counts / proton : 17.6 geometry 25 : 2 geometry (1) Counts / proton x Detector axis [cm] Detector axis [cm] Counts / proton x MeV 22 : 17.6 geometry 25 : 2 geometry (1) Detector axis [cm] Counts / proton x MeV x Detector axis [cm] Figure 7.12 Detection profiles at 1, 16 and 23 MeV for with the collimator 25 and 22 cm far from the beam axis. On the right, the shapes of the profiles are compared by rescaling the profiles acquired in the 25:2 geometry.

148 124 Experimental measurements of prompt gammas during proton irradiation Counts/proton Counts/proton Counts/proton x to 2 MeV Detector axis [cm] x 1 7 x to 5 MeV 7 to 8 MeV Detector axis [cm] Counts/proton Counts/proton Counts/proton x Detector axis [cm] x Detector axis [cm] x to 3 MeV 5 to 6 MeV 8 to 9 MeV Counts/proton Counts/proton Counts/proton x Detector axis [cm] x Detector axis [cm] 9 x to 4 MeV 6 to 7 MeV 9 to 1 MeV Detector axis [cm] Detector axis [cm] Detector axis [cm] Figure 7.13 Detection profiles measured at 1 MeV with different energy windows. The red line is relative to the acquisition with the collimator open and the green line is the difference between the acquisition with the collimator open and the acquisition with the collimator closed Profiles with different energy windows The optimal energy range of 3-6 MeV had been determined after a simulation study [4], where a decomposition in energy groups of 1 MeV of the photonsimulated detection profile was applied. According to the results of simulations [4], photons below 1 MeV are not correlated with the range, but higher energies, mainly produced by primary protons along the beam path and not much affected by scattering before leaving the target, have a fluence correlated with the beam range. In particular, the 4-5 MeV photons gives the most interesting contribution. To verify the results of this simulation study, we acquired profiles in 9 energy windows from 1 MeV to 1 MeV by steps of 1 MeV with beam energies of 1 MeV, 16 MeV and 23 MeV, which are the lower, the intermediate and the higher energies of the clinical range. The results are shown in figures 7.13, 7.14 and 7.15 in which red lines indicate the acquisitions with the collimator

149 7.1 Prompt gamma acquisitions on PMMA targets 125 Counts / Proton Counts / Proton Counts / Proton x Detector axis [cm] x x to 2 MeV 4 to 5 MeV Detector axis [cm] 7 to 8 MeV Counts / Proton Counts / Proton Counts / Proton x x x to 3 MeV Detector axis [cm] 5 to 6 MeV Detector axis [cm] 8 to 9 MeV Counts / Proton Counts / Proton Counts / Proton x Detector axis [cm] x Detector axis [cm] 8 x 1 3 to 4 MeV 6 to 7 MeV 9 to 1 MeV Detector axis [cm] Detector axis [cm] Detector axis [cm] Figure 7.14 Detection profiles measured at 16 MeV with different energy windows. The red line is relative to the acquisition with the collimator open and the green line is the difference between the acquisition with the collimator open and the acquisition with the collimator closed. open and the green lines the difference between this acquisition and the one with the collimator closed. It is clear from the graphs that a good profile was acquired in the 2 3, 3 4, 4 5 and 5 6 energy ranges, while at higher energies the profiles start to degrade. In particular, observing the green profiles, where the contribution of photons is corrected for the neutron background, it is evident a more favorable peak to baseline ratio in the 3 6 energy range. The number of protons needed to reach a 4 mm precision was quantified for the pertinent energy windows (from 2 to 6 MeV). Results are displayed in figure For all the three beam energies we obtained the best accuracy with the 3 to 4 energy window, but good values were found also in the 2-3 range, which was not included in the 3-6 MeV range that we usually adopt. According to these results, we might consider including counts between 2 and 3 MeV to improve the statistics, at the expenses of a less sharpen profile due to the high baseline level.

150 126 Experimental measurements of prompt gammas during proton irradiation x to 2 MeV x to 3 MeV 8 x to 4 MeV Counts/proton Counts/proton Counts/proton Detector axis [cm] x Detector axis [cm] x to 5 MeV 7 to 8 MeV Counts/proton Counts/proton Counts/proton Detector axis [cm] x Detector axis [cm] x to 6 MeV 8 to 9 MeV Counts/proton Counts/proton Counts/proton Detector axis [cm] x Detector axis [cm] 8 x to 7 MeV 9 to 1 MeV Detector axis [cm] Detector axis [cm] Detector axis [cm] Figure 7.15 Detection profiles measured at 23 MeV with different energy windows. The red line is relative to the acquisition with the collimator open and the green line is the difference between the acquisition with the collimator open and the acquisition with the collimator closed. Number of protons to reach 4mm precision x 1 1 MeV 16 MeV 23 MeV 2 to 3 3 to 4 4 to 5 5 to 6 Energy window [MeV] Figure 7.16 Accuracy for 1, 16 and 23 MeV for 4 different energy windows.

151 7.1 Prompt gamma acquisitions on PMMA targets 127 Tungsten Slit collimator Proton beam Gamma camera 25 cm 2 cm 8 cm Figure 7.17 Top view of the setup for the measurement of the entrance point Measurement of the beam entrance in the target The current design of the slit camera was optimized to detect the penetration depth of the proton beam. However, a second prompt gamma camera could be centered with the expected entrance point of the beam in the patient to measure the shift for the entrance point. With this additional camera, a range shift could be interpreted correctly if it results from a movement of the patient with respect to his position in the treatment plan. To evaluate the accuracy in the determination of the entrance point, the PMMA target was moved to have the lateral face aligned with the collimator aperture as shown in figure Results are shown in figure 7.18, in which the comparison between the fall-off profile and the entrance point profiles is presented for 1 MeV, 16 MeV and 23 MeV. The number of protons needed to reach a 4 mm precision is 1.4, 3.5 and , much higher with respect to the ones that we obtained for the fall-off acquisitions. This was a predictable result because the current design of the slit camera was optimized to detect the penetration depth of protons and, if we want to add a second camera for the measurement of the entrance point, we would need a new specific design. Prompt gammas are adequately suited to the measure of the Bragg peak position in the patient as their high energies give them the possibility to leave the patient, even for deep-seated tumors. This is not really an advantage for the measurement of the entrance point and other cheaper modalities would deserve consideration. A possible option is the optical tracking of the location of the surface of the patient in the treatment room.

152 128 Experimental measurements of prompt gammas during proton irradiation 8 x MeV Distal fall-off Entrance Counts / Proton Detector axis [cm] Counts / Proton 9 x MeV 8.5 Distal fall-off Entrance Detector axis [cm] x MeV 12 Distal fall-off Counts / Proton Entrance Detector axis [cm] Figure 7.18 Detected profiles centered on the entrance point in the target. A comparison with the distal fall-off acquisition is shown in red Range control An experiment was conducted with beam energies of 1 MeV, 16 MeV and 23 MeV (beam currents of 1.85, 5.6 and.58 na), to test the range control capability of the camera. In these conditions, the target was moved along the beam axis to emulate a range shift in 9 different positions ( 1, 2, 3, 5, 7, 1, 15, 2 mm) with respect to the central one ( mm). The detection profiles at different positions of the target are shown in figure The ac-

153 7.1 Prompt gamma acquisitions on PMMA targets 129 counts/proton 7 x MeV mm -1 mm -2 mm -3 mm -5 mm -7 mm -1 mm -15 mm -2 mm Detector axis [mm] counts/proton x MeV mm -1 mm -2 mm -3 mm -5 mm -7 mm -1 mm -15 mm -2 mm 6 counts/proton Detector axis [mm] 3.8 x MeV mm -1 mm -2 mm -3 mm -5 mm -7 mm -1 mm -15 mm -2 mm Detector axis [mm] Figure 7.19 Detection profiles measured at 1 MeV, 16 MeV and 23 MeV as the target is moved along beam axis to induce the detection of range shifts by the camera. quisitions were made for large doses ( , and incident protons respectively). The ability of the camera to detect millimeter shifts is visible by eye inspection especially at 1 MeV and 16 MeV, where

154 13 Experimental measurements of prompt gammas during proton irradiation Counts/proton x 1 7 Reference profile ( mm) Shifted profile Detector axis [cm] Figure 7.2 Example of the shift retrieval method. The reference profile (solid blue line) is shifted along the x axis (dashed blue lines). The retrieved shift is found for the position along the x axis that minimizes the error between the acquired profile (red line) and the shifted reference profile MeV 16 MeV 23 MeV Detection profile shift [mm] Proton beam range shift [mm] Figure 7.21 Detection profile retrieved from the acquisition for each position of the target along the beam axis for pencil beams of 1, 16 MeV and 23 MeV. all profiles are distinguishable one from another. The exact shift was calculated for high doses using the mm profiles as the reference. Figure 7.2 illustrates the shift retrieval method. The reference profile (solid blue line) is shifted along the x-axis (dashed blue line) by steps of.2 mm and the root mean square difference between the two profiles calculated

155 7.1 Prompt gamma acquisitions on PMMA targets 131 for each step. The position for which the difference is minimized is the retrieved shift. Results are plotted in figure The x-axis represents the expected shift, i.e. the position of the target with respect to the central position, while the y-axis represents the retrieved shift. At 1 MeV the plot is pretty linear, while at 23 MeV the shift of the fit of the detection profile underestimates the actual position. This is due to the fact that for great shifts, the detection profile is distorted and the reference profile consequently does not match the detection profile and this effect is more evident for high energies Comparison between measured profiles and simulations We compared the profiles acquired at 1, 16 and 23 MeV with Monte Carlo simulations which were performed with the code MCNPX version 2.5. [4]. For a better comparison, an acquisition with the collimator closed was made to detect the uncorrelated contribution. This acquisition was then subtracted from the acquisition with the collimator open, to isolate the correlated contribution. Profiles measured with the camera centered at the expected range depth for 1, 16 and 23 MeV pencil beams are shown in figure The 1 s acquisitions were normalized to the number of protons delivered that is equal to at 1 MeV, at 16 MeV and at 23 MeV. In the left column, the smoothed and normalized acquisitions acquired in the open and closed collimator configurations are shown. On the same graphs, the simulations are depicted with light colors. Measurements and simulations show very nice agreement at 1 MeV in both collimator configurations. Simulations and measurements are in worse agreement at 16 MeV and 23 MeV, especially if we consider the acquisition with the collimator open, that includes both the correlated contribution due to prompt gammas and the uncorrelated contribution. From this comparison we can conclude that the simulation overestimates the prompt gamma signal, while the number of neutrons and uncorrelated events is quite similar to the detected one. Further analysis was performed after subtracting the uncorrelated contribution from the open collimator acquisition and the results are presented in the right column of figure 4.2. The simulations were scaled for a factor.91,.76 and.74 at the three energies to compare the shape of profiles. After rescaling, simulations and profiles show relatively good agreement, especially in the fall-off region and at low energy.

156 132 Experimental measurements of prompt gammas during proton irradiation Counts / proton Counts / proton Counts / proton 8 x 1 7 simulation measurement measurement x 1 7 simulation simulation measurement simulation measurement 1 MeV 16 MeV collimator open Detector axis [cm] collimator closed Detector axis [cm] collimator open collimator closed x 1 7 simulation measurement simulation measurement 23 MeV collimator open collimator closed Counts / proton Counts / proton 6 x MeV: collimator open - collimator closed simulation+.91 measurement Detector axis [cm] x MeV: collimator open - collimator closed simulation Detector axis [cm] x MeV: collimator open - collimator closed simulation measurement Detector axis [cm] Detector axis [cm] Figure 7.22 Detection profiles measured with the camera centered at the expected range depth of 1 MeV, 16 MeV and 23 MeV pencil beams. On the left are shown the profiles acquired with the collimator open and closed and the respective simulation. On the right the profiles acquired with the collimator open are subtracted from the uncorrelated contribution. The simulations are scaled to fit the acquisitions.

157 7.1 Prompt gamma acquisitions on PMMA targets Determination of the event rate The objective of the measurements described in this paragraph was the determination of the actual event rate in one slab as a function of the beam current. The calculation is based on the fact that the event rate is proportional to the beam current. At 23 MeV, three profiles were acquired at very low beam currents (25, 96 and 334 pa) and we verified that the number of acquired events grows linearly with the current, so that, in this conditions, the efficiency is around 1% and pile-up effect is negligible. Figure 7.23 shows the recorded rate for a single channel versus the beam current for events in the 3-6 MeV energy range (green line) and above 3 MeV (blue line). According to table 4.1, we expected a rate of 38 khz/na/slab at 23 MeV for a single slab, considering an hardware threshold of 3 MeV. The application of a linear fitting to acquired data results in a rate of 2 khz/na/slab, which is about 2 times lower than the predicted one. As already observed in section 7.1.1, we observed that the simulations overestimate the number of emitted gammas, especially at 23 MeV. The reason of this disagreement has not been yet understood. 7 6 > 3 MeV 3-6 MeV 5 Count rate [Hz] Beam current [pa] Figure 7.23 Event rate recorded by a single slab as a function of the beam current at the nozzle. The beam energy was 23 MeV. On the right axis, the expected rate of events belonging to the whole spectrum is reported. Measured rates for growing beam currents are plotted in figure 7.24 and are compared to the expected rates (red line), which are calculated from the linear fitting of data of figure The vertical axis on the left represents the rate of events in the 3-6 MeV energy window, while the axis on the right refers to the events of the whole spectrum and was obtained rescaling the number of counts in the 3-6 MeV by the ratio between the total number of counts in

158 134 Experimental measurements of prompt gammas during proton irradiation x 1 5 x Measured rate Expected rate MeV count rate [Hz] MHz Total count rate [Hz] Beam current [na] Figure 7.24 Event rate between 3 and 6 MeV recorded by a single slab as a function of the beam current at the nozzle at 23 MeV. Blue line indicates the measured rate and red line is the linear regression based on the first three measured points. the spectrum of figure 7.3 and the events between the thresholds. As already stated, simulations overestimate the rate, and the rate of 1MHz for the events of the whole spectrum is expected for beam currents of 6 na. The graph shows that, at high currents, the observed rate is no more proportional to the current, meaning that the counting efficiency starts to decrease with the current. Differently from the results shown in section 6.2, where a single energy line was given as the input of the counting system, in these conditions, the pulses belong to a continuous spectrum and they have different amplitudes. In our counting system, based on a double threshold discrimination, the dead-time is the time-over-threshold of the pulse and it is therefore dependent on its amplitude. In the measurement conditions, the simple paralyzable model described in cannot be applied because there is no univocal dead-time. Nevertheless, the system shows a paralyzable behavior because it reaches a maximum in the count rate. Acquired profiles at the beam currents of figure 7.24 are plotted in figure Each profile is normalized to the beam current and to the time of the acquisition. Blue profiles are the acquisitions, after normalization and without any correction while red profiles were obtained by calculating the number of expected counts according to the linear regression of figure In a condition of 1% efficiency, normalized profiles should be coincident for each beam current. However, as expected from results in figure 7.24, the counting efficiency starts to decrease at about 4 na. Profiles in red are the expected profiles, considering for each channel the expected rate found with the linear regression of

159 7.1 Prompt gamma acquisitions on PMMA targets Counts / s / na Counts / s / na Counts / s / na 2 15 Counts / s / na Counts / s / na Counts / s / na na.96 na.334 na.942 na Detector axis Detector axis Detector axis Detector axis na 4.45 na 5.75 na Detector axis Detector axis na 12.9 na na Detector axis Detector axis Detector axis Counts / s / na Counts / s / na Counts / s / na Counts / s / na Counts / s / na Counts / s / na na Detector axis na Detector axis Figure 7.25 Acquired profiles at different beam currents at 23 MeV. Profiles are normalized to the beam current and to the time of the acquisition. Profiles after the correction for the expected input rate at each current are depicted in red while raw profiles are represented in blue. figure 7.24.

160 136 Experimental measurements of prompt gammas during proton irradiation Delivery of a 2D map on targets with inhomogeneities Range uncertainty is increased by tissue inhomogeneities and a slit camera will make sense if it can control the beam range in inhomogeneous tissues. A simple experiment was made to observe the effect of inhomogeneities in the PMMA target. For this purpose, we delivered a 2D map of 49 points on a 6 6 cm 2 square, with a proton beam of 1 MeV. The pencil beam was moved from the bottom right position (close to the camera) to the top left point (far from the camera) as depicted in figure For each delivered map we acquired 13 intermediate profiles of 5 µs. The sample time was chosen to be able to distinguish subsequent spots. Spot 49 To the camera Spot 1 Figure 7.26 Schematic of the 49 points of the 2D map delivered on the target. The first point of the map is close to the camera and the last point is far from the camera. The section of the cavity is also reported. The target has now a cylindrical 5 cm diameter core. In this way we have some pencil beams traversing the full target and the remaining which pass through the cavity. For the first acquisition, the core was filled with PMMA dishes in order to have a homogeneous target. After that, we remove a PMMA element to produce a cavity: the configuration was 5.13 mm PMMA followed by 1.7 mm cavity as shown in figure The remaining length of the target was filled with PMMA. During the delivery of the 2D map, we expect a decreasing number of counts with the time, because the beam first scans a region of the target close to the camera and then far from the camera. The measured time structure is shown in figure 7.28, where each point is the number of counts acquired by the camera within the 3-6 MeV energy window during the intermediate 5 µs profile. On the bottom of the same figure, a detail of the acquisition where the spots are distinguishable is presented.

161 7.1 Prompt gamma acquisitions on PMMA targets mm 5.13 mm Beam Air cavity Beam Figure 7.27 Detail of the target used for irradiation with a 2D map. The target core was composed of 5.13 mm PMMA, 1.7 mm air cavity and PMMA up to the total length of the target Counts [a.u.] Time [a.u.] 2 Counts [a.u.] Time [a.u.] Figure 7.28 Total number of counts acquired by the camera within the 3-6 MeV energy window along the time of the delivery of the 2D map. The figure on the bottom is a detail of the figure on the top: separation between spots is visible. The x-axis indicates the number of the intermediate profile of 5 µs.

162 138 Experimental measurements of prompt gammas during proton irradiation x 1 Top Counts [a.u.] Detector axis [cm] x 1 Center Counts [a.u.] Full target Target with cavity Detector axis [cm] x 1 Bottom Counts [a.u.] Detector axis [cm] Figure 7.29 Comparison between profiles acquired with the full target (blue) and the target with the cavity (red) in three different spots of the map. It is evident that the two spots out of the cavity are similar for the full target and the empty target, while the profile acquired with the spot in correspondence of the cavity is shifted. In figure 7.29 the comparison between the acquisition with the full target and the target with the cavity is presented. On the right column, the spot position in the map is highlighted in red. The graphs on the top and on the bottom refer to two points of the map out of the cavity. In both cases, the

163 7.1 Prompt gamma acquisitions on PMMA targets x Counts [a.u.] Detector axis [cm] Figure 7.3 Profiles acquired during the delivery of column of the 2D map on a target with a half cavity inside. Profiles relative to the points within the cavity are shifted with respect to the ones in the full PMMA. Measured shift [mm] y x 5 6 z 7 Figure 7.31 cavity. Retrieved shift for the 49 points of the map for the target with the full pencil beam passed through a homogeneous material and almost no differences are visible between the two profiles. The central plot is relative to the central point of the map. The effect of the inhomogeneity is a shift of the profile for the target with the cavity. This shift can be intuitively explained by the fact that the beam range in the inhomogeneous target is longer, due to the absence of material. We then replaced the cavity with an half cavity as presented in the scheme on the right of figure 7.3. The graph in figure 7.3 shows the superposition of profiles of a column of the map. Profiles from the points in the cavity are shifted with respect to the ones acquired from the points in the full PMMA. The retrieved shift for each profile of the map, using the full target acquisi-

164 14 Experimental measurements of prompt gammas during proton irradiation 12 Measured shift [mm] y x 5 6 z 7 Figure 7.32 cavity. Retrieved shift for the 49 points of the map for the target with the half tion as a reference are shown in figure 7.31 and 7.32, for the full cavity and the half cavity, respectively. The shape of the cavity can be identified by visual inspection and the two surfaces show a maximum of about 1 mm (which is the length of the cavity along the beam axis) corresponding to the points of the map where the pencil beam travels through the cavity. 7.2 First results toward clinical applications Experimental setup Measurements presented in this paragraph are the first step toward the use of the camera during patients treatments. The experiment was conducted at the IBA proton therapy facility in Prague. Differently from the measurement described in the previous paragraph, the camera was integrated into a trolley, including the tungsten collimator and lateral shielding as in figure The trolley allows movements of the camera in the three directions x, y and z and a 36 rotation of the whole system (collimator plus gamma detector) along the y axis. In addition, the detector can be moved from 12 cm up to 2 cm from the collimator.

165 7.2 First results toward clinical applications 141 Prompt gamma detector Figure 7.33 Photograph of the trolley positioning system. A detail of the collimatordetector system is presented in the picture on the left Influence of target composition Up to now, we acquired profiles irradiating a PMMA target for consistence with the simulation study by which the slit camera was dimensioned [4]. We now analyze the effect of the target composition on profiles. In table 7.4, the elemental composition of PMMA and water are compared to various standard human tissues [23]. The materials are given in order of decreasing oxygen to carbon mass fraction ratio. Hydrogen, carbon and oxygen are the only elements with a mass fraction greater than the 5%. The only exceptions are calcium and phosphorus in bone. In most tissues, but also in water and PMMA, the hydrogen mass fraction is 1%. Adipose tissue is comparable to PMMA, due to a 6% mass fraction of carbon, while soft tissues, muscles, brain grey and white matters, liver and lung tissues are closer to water thanks to more than 7% mass fraction of oxygen. The influence of target composition was investigated by replacing the core of the cylindrical PMMA target with inserts of different materials as shown in figure 7.34, where the core was filled with a material with properties similar to bone. We compared PMMA, water and materials with the same composition of fat and bone. Profiles were acquired at 16 MeV and the camera was aligned

166 142 Experimental measurements of prompt gammas during proton irradiation Table 7.4 Elemental compositions of PMMA, water and various standard human tissue from ICRU ([23]). Elemental mass fraction [%] Tissue H C N O Na Mg P S Cl K Ca Fe Water Lymph Lung tissue Blood Liver tissue Skeletal muscle Soft tissue Brain tissue Skin tissue Cortical bone Breast tissue PMMA Adipose tissue Figure 7.34 Setup for profiles acquisition with a bone target. at the expected range according to the target composition, taking into account the impact that the target composition has on the penetration depth. The detection profiles are illustrated in figure PMMA and fat have more carbon than oxygen and show lower baseline and peak values. In bone and water, carbon is replaced by oxygen and we can therefore observe higher values of peak and baseline.

167 7.2 First results toward clinical applications x 1 3 Counts/proton 2.5 Bone Water PMMA Fat Detector axis [cm] 4 Figure 7.35 Detection profiles for target with different composition for proton beams of 16 MeV. Bone, water, PMMA and fat are compared. Figure 7.36 Setup for the test session. A base-of-skull treatment plan was delivered to an anthropomorphic phantom Acquisitions of realistic treatment delivered on an anthropomorphic phantom Finally we applied a realistic treatment to an anthropomorphic phantom. The phantom was placed on the treatment bed as shown in figure 7.36 and realistic base-of-skull PBS (Pencil Beam Scanning) treatment delivered. The collimator was placed 15 cm far from the central beam axis and the camera 12 cm far from

168 144 Experimental measurements of prompt gammas during proton irradiation Table 7.5 Energy layers with the corresponding number of spots and interaction depth in water for the base-of-skull treatment. Layer number Energy [MeV] Number of spots Interaction Depth [g/cm 2 ] Figure 7.37 Dose distribution from the base-of-skull treatment plan on the CT of the anthropomorphic phantom. Pencil beam 1 (left) and 2 (right) were selected for illustration purposes and are depicted in red lines. Their range are 8.6 and 7.7 cm, respectively. the collimator. The position of the camera along beam axis was chosen so that the few first layers are within the field of view. The treatment is composed by 23 layers, but for our experiment we measured the delivery of the 9 first layers with a.5 ms sample period in order to be able to identify the successive pencil beams within each layer in the acquired data. The treatment plan delivered is summarized in table 7.5, where, for each energy layer, the energy, the number of spots and the interaction depth in water are reported. For each case, a 1-fraction treatment (2 Gy) was delivered, as well as the full treatment at once (6 Gy) in order to get high statistics for offline analysis. Figure 7.37 shows the dose distribution from the treatment on th CT: pencil beams 1 (left) and 2 (right) were selected for illustration purposes and are