Detector. * All clinical images are courtesy of. University, Jerusalem. Ami Altman, Ph.D., and Raz Carmi Ph.D., CT BU, PHILIPS Healthcare

Transcription

1 AD Dual-Energy alenerg CT Based on A Double Layer Detector * All clinical images are courtesy of Hadassah Medical Center, The Hebrew University, Jerusalem Ami Altman, Ph.D., and Raz Carmi Ph.D., CT BU, PHILIPS Healthcare

2 Content 1. The double-layer detector principle and operation 2. Advantages and drawbacks of the Double-Layer approach 3. Material Decomposition method 4. The Double-Layer Energy spectra compared to 80/140 kvp spectra 5. The Effect of large noise in the Low_E image on material decomposition 6. Spectral resolving power and simulated results to compare various Dual-Energy CT method 7. Decomposing specific materials from mixtures, and quantitative Iodine maps 8. Clinical applications and results 2

3 The Double-Layer Detector, Principle and Operation A mm side-looking photodiode array shielded by a 1.0-mm Tungsten layer X-Rays Coming from top mm optical glue Inter-Layer Filter mm reflecting paint Y Top Scintillator, 1.0 mm Bottom Scintillator: 2-mm GOS ~50% ~50% Low Energy Raw data + High Energy Raw data E1 image E2 image X 1. For optimal performance the effective atomic number of the top scintillator is small without sacrificing light output (better than GOS) 2. Top Scintillator thickness has been optimized for best energy separation and low-energy image noise 3. The thin filter material and thickness has been optimized to attenuate < 3% of the intensity entering the detector, and yet, significantly increase the energy separation. 4. Bottom scintillator is GOS, the thickness of which set to absorb 99.5% of the High-Energy spectrum (note that light collection is sideways) = Weighted combined Raw data CT image 3

4 Main Advantages Advantages and Drawbacks of The Double Layer Approach 1. Simultaneous and equi-directional sampling of the scanned body in the 2 energy bands 2. Enables both projection-based and attenuation-space (image-space) material decomposition 3. The high energy tail at the Low-Energy Spectrum, enables low-noise at the Low-Energy images even for large patients. This has a significant advantage in the material spectral decomposition, compensating for the larger overlap between the two spectra (see next slides) 4. Enables a single-source dual energy CT with unlimited FOV for both axial and spiral scans, at all protocols. 5. Can work in a conventional CT mode by multiplexing (analog MUX) the two layers at each detection pixel 6. Very simple side-looking photodiode arrays that enable any expansion of the detector array at all directions 7. Work at normal CT dose, with a potential for significant dose reduction (high light output of front scintillator) Drawbacks: 1. Energy overlap is larger than scanning with two kvp values due to the High-Energy tail at the Low-Energy Spectrum (80/140). However, this has also an advantage, as explained in (2) above 2. Requires more readout channels, and one more layer of scintillators, adding to DAS cost (partially compensated by simpler and inexpensive photodiode arrays) 4

5 Material Analysis Method With Dual Energy Spectral CT, Attenuation Space NOTE that the attenuation coefficient (at CT energy range) is linear with the density (concentration) for a specific effective atomic number and energy (away from K-Edge) μ Z, E 3 Z Z A ρ + B 3 E E ρ 1. On a µ-space map, each material, characterized by its effective atomic number, is represented along a straight line, the angle of which depends on its effective Z for a given energy set 2. Angular difference between the representing lines of two specific materials with given atomic number depends on the mean-energy difference between the two spectra 3. The statistical line width, namely, the distribution of points along it, depends on the separate spectra image noise, as well as on the overlap between the two spectra. Basically, an effective atomic number spectrometer μ E-Low (HU) Z eff _1 > Zeff_2 > Zeff_3 Z eff _1 Z eff _2 Z eff _3 Conventional CT Image µ_e_l Low (HU) zoom Iodine Calcium water Water (E_low & E_high = 0 HU) μ E-High (HU) µ_e_high (HU) A phantom with different concentrations of Calcium and Iodine contrast agent 5

6 Double-Layer Detector - Energy Spectra With / Without 35-cm Water Absorber dn/d de dn/d E Energy Windows Obtained In A Double Layer CT Detector From a 140 kvp X Ray Tube, Air Only <E_Low >= 63 kev Δ<E>=31 kev <E_High >= 94 kev X Ray Energy (kev) Spectrum_Low_E Spectrum_High_E Low and High Energy Spectra, 35 cm Water Absorber <Low_E>=75keV Δ<E>=26 kev <High_E>=101 kev The drawback becomes an advantage: 1. The high-energy tail in the Low_E spectrum, enables good IQ (low-noise), even for large patients. 2. Compare with 600 mas 80 kvp scans on adults, where images are very noisy, reducing significantly tissue & material separation X Ray Energy (kev) Spectrum_E_low Spectrum_E_high 6

7 Compare With Dual kvp, 80 VS. 140 kvp Spectral Difference (No extra filter on 140 kvp beam) 140 VS. 80 kvp Spectra in Air dn/de (# #/kev) <E_low>=53 kev Δ<E>=18 kev <E_high>=71 kev The CT image noise, for the same mas, obtained in the 80 kvp image, with 35-cm water cylinder, is 9 times larger than that of the 140 kvp image!! X-Ray Energy (kev) 140kVp_Specrum 80kVp_Specrum 80 VS 140 kvp Spectra - 36-cm Water dn/de (#/k kev) <E_low>=61 kev Δ<E>=27 kev <E_high>=88 kev ALSO: A reasonably-seemed protocol of 200mAs at 140 kvp + 650mAs at 80 kvp would still result in 3 times more noise in the 80 kvp image (for 35-cm water cylinder). This would reduce severely the material separation capability X-Ray Energy (kev) 140kVp_Specrum 80kVp_Specrum 7

8 The Effect of Higher Noise in The Low-Energy Image 10 mm/l Iodine, SD=10 HU both E_Low and E_High; Gaussian fit 12 to the noise: Separation is possible Equivalent concentration of Ca to get the same HU 70 mm/l I di in Iodine i Water Low HU 1040 E High HU E 10 mm I, I SD=15 HU E E_Low, Low =10 HU E E_High; High; Gaussian fit to the noise: 10 mm/l Iodine in Water Separation is almost impossible mm/l I 8 Iodine Ca Low HU E HighE HU 10 mm I This is why in any Tube-Based Dual Energy CT, CT one might be forced to use 100/140 kvp instead of 80/140 kvp (a use of filter on the high kvp, improves the poor spectral separation of the 100/140 kvp combination.) Water 8

9 Spectral Resolving Power An Objective Measure of the Material - Decomposition Quality in Dual-E CT Following conventions in 2D mass spectroscopy, and in a 10 combined Mass-TOF spectroscopy, we define a Spectral Resolving Power Low E HU High E HU Thus fit to the data from a standard phantom (with low concentrations of Iodine and Calcium (see previous slide), Two 2D Gaussian functions: Than the Spectral Resolving power is defined: RESOLVING_ POWER= 2D (Gaussian#1 A+ B U Gaussian# 2) Profile Line A B Where A and B are the non overlapped volumes of the two Gaussian functions, and the denominator is the total t volume of the union of the the two Gaussian functions This takes in account all relevant factors: Image Noise, Mean Energy Difference, patient size, spectra overlap, Mean Energy of each spectrum etc. Note that the resolving power 1 9

10 1. Dual-Energy methods: Simulations and Comparison Conditions (GEANT4 [GATE] full CT Simulation) i. Double-Decker Brilliance geometry and detector sizes with X-DFS, 2320 views, Single-Slice CT, axial 360-deg, scans 250 mas, 140 kvp ii. Dual-Source CT has been simulated using 2 scans with Brilliance geometry and detector sizes with X-DFS, 2320 views, Single-Slice CT, axial 360-deg, with 130 mas at 140 kvp and 670 mas at 80 kvp (Note that the dose per mas at 80 kvp is ~5.2 times less than in 140 kvp). Dual source CT has been simulated with and without a Tin (Sn) filter (0.35 mm thick). iii. kvp Switching has been simulated with the same Brilliance geometry and parameters as above, Using 1/8 scheme (1 view of 80 kvp every 8 views of 140 kvp), which is one of the best modes to overcome the sampling sparsity, with 130 mas at 140 kvp and 670 mas at 80 kvp (No Tin filter has been used) iv. Photon Counting (for reference) 150 mas (this the equivalent dose to ~250 mas in Current Integration), 2 Energy Windows with no overlap has been used. Same geometry and conditions as above 2. Phantoms i. 20-cm Water Cylinder with 4 test tubes as shown in slide 8 ii. 36-cm Water Cylinder with the same 4 test tubes 10

11 Few Results Obtained From GEANT4 (GATE) Simulations * Method Spectral Resolving Power: 20-cm Phantom (10 mm/l I) Spectral Resolving Power: 36-cm Phantom (10 mm/l I) Comments Dual-Source 0.61 ± ± kvp image noise is a serious 80;140 kvp with Tin filter Same dose for all Same dose for all limitation it ti in Medium-large patients; t methods methods Hard to apply to gated\tagged CCTA; Limited FOV Dual-Source 0.42 ± ± 0.02 Energy separation is low ~19 kev with 100;140 kvp with Tin filter the Tin filter Double-Decker Detector 1-mm Top Scintillator mm Tin 2-mm GOS Fast kvp Switching 80;140 kvp (no filter) 0.54 ± ± 0.02 All modes are possible for FOV up to 500mm 0.41 ± ± 0.02 Cardiac questionable; Sparse sampling affects both IQ and material decomp.; Tin filter cannot be used, poor energy separation Fast kvp switching 100;140 kvp 0.22 ± ± 0.02 Almost useless without a filter Photon Counting CdTe, CdZnTe Energy windows only; Assuming 10% energy resolution, and no rate limit *Attenuation & Beam Hardening corrections have been applied for all methods (See R. Carmi, A. Altman, G. Naveh MIC IEEE 2005) 11

12 µ E1 (HU) Z1 µ E1 X 1 α 1 E1 1 β W 1 E2 α β Iodine + Carbon Iodine Calcium Carbon 2.3% Materials Decomposition (e.g. Contrast Agents) in Mixtures 0% 6.3% µ E2 Z2 µ E2 (HU) Iodine Calibration: 100% 3 CT image % % 15.4% 100% 0% 1. Any material concentration varies along the specific material spectral line (water at the origin in HU scale) 2. Image locations with 2-material mixtures of Z1 and Z2 (easily generalizeable to more than 2 materials) can be quantified easily through simple vector calculations r r r = α + β 3. Add adaptive diffusion filter and proper statistical noise analysis to refine material separation (assuming Gaussian noise in the spectral map) Iodine Image Carbon Image X 1. Accurate quantification of Iodine contrast agent in Iodine+Carbon Mixtures 2. Carbon-based polymer mixed with Clinical Iodine Contrast (Ultravist) have been used 3. Measured in the Dual-Layer CT using a 25-cm Plexiglas phantom diameter, with inserts 12

13 Dose/Noise Effect on Material Decomposition Iodine images Energy Map 800 mas The same phantom, different scan dose 50 mas 15 mas 13

14 Clinical Images, Obtained with A Dual-Layer Detector Spectral CT 1. A Philips Brilliance-64 with a Double-Layer Detector operates routinely in Hadassah Medical Center, at the Hebrew University in Jerusalem. 2. Dual Energy scans are performed at 140 kvp with conventional dose, 250 mas for all protocols 3. All images are courtesy of Hadassah MC, and Dr. Jacob Sosna, Head of the CT unit there. 140 kv 250 mas Separation line HU of E1 H 2 O Iodine Calcium HU of E2 1. Iodine-tagged blood well separated from blood-vessel calcifications and bones 2. Soft-tissue (muscles) are well separated even from lowconcentrated Iodine regions 3. Different materials / tissues are overlayed with colors on the anatomic image Soft tissue separation from Iodine contrast and from bones: Soft Tissue Iodine-tagged Blood Spectral Analysis Map Calcium & Bones Fat HU of E1 Iodine Calcium Conventional CT Image Spectral CT Image, Dual-E Soft tissue HU of E2 14

15 Virtual Non Contrast Image Generation (for algorithms & methods see L. Goshen, A. Altman & R. Crami MIC2008 IEEE) 250 mas 250 mas 15

16 Dual Energy Images Advanced Iodine Perfusion Maps, Tissues/Material Decomposition Main Procedure: 1800 Noise Level Estimate Raw energy map 1800 Noise Removal, preserving Spectral Map information Noise free energy map Estimate of Material Response Vector Iodine Map Generation Iodine Color Map A tiny lung nodule detected on an Iodine-map image a b (b), obtained with a PHILIPS Dual-Energy CT Note that on the conventional CT Image (obtained simultaneously during the same scan), the Lung- Nodule looks as a normal Iodine-Tagged d blood vessel Conventional CT Spectral Iodine Maps Conventional CT Iodine Image A detected non-perfused Lung Nodule (Tumor) 16

17 Towards Prepless CT Colonoscopy with Dual-Energy CT Nominal Virtual-Colonoscopy scan protocol and dose a b The colon is partially filled with stool and both thiodine and Barium contrast agents c d Corrupted colon wall Non-cleansed residuals Electronic cleansing with dual-energy analysis Conventional-CT electronic cleansing with high and low HU thresholds only 11 17

18 Towards Prepless CT Colonoscopy with Dual-Energy CT (cont.) Compare Mode Conventional Electronic Cleansing Dual Energy Electronic Cleansing Bowel is still full of stool 18

19 Towards Prepless CT Colonoscopy with Dual-Energy CT (cont.) Conventional Electronic Cleansing Dual Energy Electronic Cleansing A false polyp caused by residual stool 19

20 Quantifying Composites of Tissues Mixtures, Soft-Plaque Characterization Vulnerable Plaque in Carotids Purple indicates high lipidic component in plaque Calcification Lumen Soft Plaque 20

21 Kidneys Stones Identification and Quantification + Brushite + + Calcium Oxalate monohydrated = Brushite Cystine + Urique acid Uric Acid In-Vivo Kidneys Stone analysis, using a Calibration Phantom 21

22 Simultaneous Multi-Phase Imaging Using Contrast Agents Mix, injected in Separate times 1. Plaque-induced NWZ Rabbits, through cholesterol-rich diet 2. Early injection of targeted Iodine-Loaded nano-particles contrast agent, highly up-taken by Macrophages (N1177 NPC, developed and manufactured by NanoScan Imaging, g, Lansdale, PA) 3. Late injection (hours) of Gd Contrast-Agent (Magnevist 280) 4. Scanning to image simultaneously both plaque and lumen 22

23 Demonstrating Material separation: Iodine vs. bone + gadolinium A) N1177 (iodine) + gadolinium. Scan: 4 hours after N1177 injection and immediately after gadolinium injection B) Material separation with dual-energy spectral analysis shows the differentiation between iodine to gadolinium and bone A B bone and gadolinium iodine Gadolinium contrast material in the heart Gadolinium contrast material in the heart Iodine nanoparticles contrast material in the spleen Iodine nanoparticles contrast material in the spleen Note that the spleen is rich with Macrophages! 23

24 A) N1177 (iodine nanoparticles) Scan: 2 hours after injection A A first example showing possible plaque in the aorta B) N1177 (iodine) + gadolinium. C) Material separation with dual-energy Scan:4 hours after N1177 spectralanalysis analysis shows the differentiation injection and immediately between iodine in the soft plaque and after gadolinium injection gadolinium in the aorta lumen B C 139 HU Iodine nanoparticles captured in soft plaque. Max. intensity after 2 h, reducing after 4 h soft plaque (iodine) Gadolinium enhancement of the aorta lumen - can help in areas where the lumen walls are less clear 122 HU 134 HU gadolinium bone and gadolinium iodine 24

25 A Second Example, Soft-Plaque Imaging Simultaneously with The Lumen A) N1177 (iodine nanoparticles) Scan: 2 hours after injection A B) N1177 (iodine) + gadolinium. C) Material separation with dual-energy Scan: 4 hours after N1177 spectral analysis shows the differentiation injection and immediately between iodine to gadolinium and bone after gadolinium injection B C Possibly some captured iodine inside plaque in the aorta walls bone bone bone and gadolinium iodine iodine nanoparticles concentrated in the spleen iodine nanoparticles concentrated in the spleen Possibly some captured iodine inside plaque in the aorta walls and gadolinium enhancement of the aorta lumen probably: plaque / lumen (iodine / gadolinium) differentiation 25 25

26 Philips Healthcare,