Functional Magnetic Resonance Imaging of the Human Brain and Spinal Cord by Means of Signal Enhancement by Extravascular Protons

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1 Functional Magnetic Resonance Imaging of the Human Brain and pinal Cord by Means of ignal Enhancement by Extravascular Protons P.W. TROMAN, B. TOMANEK, K.L. MALIZA MR Technology Group, Institute for Biodiagnostics, National Research Council of Canada, 435 Ellice Avenue, Winnipeg, Manitoba R3B 1Y6, Canada ABTRACT: A review of functional magnetic resonance imaging (fmri) signal changes in spin echo image data is presented. pin echo fmri data from the human brain and spinal cord show a consistent departure from that expected with blood oxygen level dependent () contrast. tudies to investigate this finding demonstrate fmri signal changes of 2.5% in the spinal cord and 0.7% in the brain at 1.5 T, which is extrapolated to an echo time of zero. Consistent evidence of a non- contrast mechanism arising from a proton-density change at sites of neuronal activation is demonstrated. A mathematical model and physiological explanation for signal enhancement by extravascular protons is also presented Wiley Periodicals, Inc. Concepts Magn Reson Part A 16A: 28 34, 2003 KEY WORD: functional magnetic resonance imaging; blood oxygen level dependent; signal enhancement by extravascular protons; brain; spinal cord; human INTRODUCTION Received 19 eptember 2002; accepted 1 October 2002 Correspondence to: Dr. P.W. troman; Patrick.troman@ nrc.ca. Contract grant sponsor: Canadian Institutes of Health Research. Concepts in Magnetic Resonance Part A, Vol. 16A(1) (2003) Published online in Wiley Intercience ( com). DOI /cmr.a Wiley Periodicals, Inc. Functional magnetic resonance imaging (fmri) has been developed over the last decade, and it has become well established as a tool for studies of brain function. However, the basic mechanism giving rise to signal changes in MR image data upon a change in neuronal activity still presents some lingering questions. The sensitivity of fmri methods for detecting neuronal function in the human central nervous system requires an accurate model of the signal intensity changes that occur in MR image data. In the current model, the increase in the supply of oxygenated blood that occurs upon neuronal activation results in a net reduction of deoxyhemoglobin in the surrounding capillaries and vessels draining the region. Because deoxyhemoglobin is paramagnetic it reduces the 28

2 fmri OF HUMAN BRAIN AND PINAL CORD BY EEP 29 transverse relaxation times (T* 2 and T 2 ), and so a local reduction in its concentration results in a slightly higher MR signal intensity. Hence, the change in image contrast that occurs with a change in neuronal activity is known as blood oxygen level dependent () contrast. This model influences both the design of fmri experiments and data analysis methods. Although fmri has already been established as a useful tool and the relationship between image intensity changes and neuronal firing rates has been demonstrated (1), improvements in our understanding of how and why these signal changes occur will serve to further enhance the fmri method and our ability to interpret the data we obtain. The questions that still remain regarding fmri signal changes arise from the following apparent inconsistency. The model of signal changes presented by Menon et al. (2) has been proven for T* 2 - weighted data. It shows that the fractional signal changes (/) are an approximately linear function of the echo time (TE) with a slope equal to the change in the relaxation rate [(1/T* 2 )] upon neuronal activation, as follows: expte 1 T* 2 1 [1] Using a first-order approximation for the exponential term, this expression can be simplified to TE 1 T * 2 [2] In these expressions is the image intensity change between task and non-task conditions and is the image intensity during the non-task conditions. Equation [2] also applies to T 2 -weighted data but with a slope of (1/T 2 ). Bandettini et al. (3) also demonstrated that (1/T* 2 ) 3.5(1/T 2 ). In practice, however, T* 2 - weighted signal changes are not 3.5 times larger than T 2 -weighted signal changes but are instead usually about 2 times larger. pin echo signal changes are, in fact, larger than expected from this model of signal changes, even though the slope of the TE dependence is (1/T 2 ), as described above (4). The source of the discrepancy is often attributed to in-flow effects or diffusion of spins through inhomogeneous magnetic fields around blood vessels, because these effects can influence the observed signal changes in fmri (5). However, signal enhancement from fully relaxed blood flowing into the imaging volume can be reduced or even eliminated with the use of sufficiently long repetition times to allow full relaxation of all magnetization between successive acquisitions (6). ignal attenuation from diffusion effects is larger with T* 2 -weighted data than with T 2 -weighted data (7) because the 180 refocusing pulse reverses the dephasing that occurs in the first half of the spin echo. As a result, some rephasing of the spins can occur in the second half of the spin echo if the spin diffusion distance is not larger than the extent of the field inhomogeneity around the blood vessels. If diffusion is a significant contributing factor, the effect on the fractional signal changes in fmri will be larger at longer TEs and negligible at short TEs. Diffusion effects are therefore unlikely to explain the larger than expected fractional signal changes in spin echo fmri data. Another possible contribution to signal changes in spin echo fmri data is from changes in the effective T 2 values observed with asymmetric spin echo data (i.e., T 2 changes) (8). However, this is only true with asymmetric spin echo data when the center of k-space is not sampled at the center of the spin echo and can therefore be avoided, like in-flow effects. As a result, these common sources of artifactual signal changes can all be avoided, depend on MR data acquisition parameters, and thus cannot explain the consistently larger than expected signal changes in spin echo fmri data. The following discussion describes our attempts to understand the source of this apparent inconsistency in the accepted theory. EEP fmri tudies in pinal Cord The fact that the signal changes observed with spin echo fmri data can be larger than expected from the effect was clearly illustrated in functional imaging experiments of the human spinal cord (9, 10). These studies were carried out at 3 and 1.5 T and were based on comparisons of spin echo and gradient echo echo-planar imaging (EPI) data obtained from the cervical spinal cords of healthy human volunteers. The subjects performed a motor task with one hand or were subjected to sensory stimulation of the hand. At 1.5 T the gradient echo and spin echo data yielded very similar signal changes of % (mean D, n 17) and % (n 11), respectively, with a motor task. In order to understand this initially surprising result, spin echo fmri studies were carried out in the spinal cord at different TEs (11). Data were obtained with a single-shot fast spin echo (FE) method at 1.5 T with TEs of 36, 66, and 96 ms and a repetition time (TR) of 7stoavoid any contribution from in-flow effects. Fractional signal intensity changes were observed to be linearly dependent on the TE, as expected from theory. However, the zero-intercept value (i.e., the extrapolated signal change at TE 0) was significantly

3 30 TROMAN, TOMANEK, AND MALIZA and the T 2 values are specified as T 2 and T 2, respectively. Corresponding values during the task conditions are indicated with the prime () symbol. The MR image signal intensity during the task and non-task conditions of the fmri experiment is therefore given by the expressions nontask 0 exp TE T 2 0 exp TE T 2 [3] Figure 1 The fractional signal changes (/) observed in the cervical spinal cord as a function of echo time (TE). The data are average values from 15 healthy volunteers. The result of fitting with a nonlinear model ( ). The linear fitto data with TE 33 ms only (- - -). The error bars indicate the standard error of the mean. greater than zero and was % with a motor task and % with sensory stimulation of the palm. A more detailed study followed in which a fast spin echo method enabling shorter TEs was employed (12). The study was again carried out at 1.5 T, but this time we studied the lumbar spinal cord in healthy volunteers with a cold sensation applied to the lower leg. These changes from the earlier studies in the cervical spinal cord reduced the amount of motion and field fluctuations related to breathing that were encountered and eliminated task-related motion contributions and variations based on the amount of effort by the subject. Fast spin echo image data were obtained with an echo train length of 32 and a TR of 3 s, so that the total acquisition time was 12 s ( matrix, 12 cm field of view). Data were acquired with TEs ranging from 11 to 66 ms in 11 ms increments. The fractional signal intensity changes (/) were slightly (but significantly) nonlinear at short TEs (33 ms), as shown in Figure 1. At a TE of only 11 ms, the fractional signal change was observed to be %, but a linear fit to the data obtained with TE 33 ms yielded a zero-intercept value of 2.4%. task 0 exp TE T 2 0 exp TE T 2 [4] An iterative process to minimize the residual errors was written in IDL (Interactive Data Language, Research ystems Inc., Boulder, CO) and was used to estimate values that fit the measured data. This process yielded T 2 values of 172 9msforT 2, and ms for T 2 during the non-task periods. During the task periods the T 2 increased to ms, whereas T 2 remained constant ( 0.7%). The proton density of the longer T 2 compartment ( 0 ) remained at the same value during rest and activation (0.3%), whereas 0 increased by % upon neuronal activation. Therefore, the compartment underwent a change in T 2 only, as expected from the effect, whereas the compartment underwent a change in the proton-density only. We concluded that the proton-density change must occur in an extravascular water compartment, because the T 2 changes are known to occur within the blood and the two are occurring in separate water compartments that do not rapidly exchange water protons on the time scale of T 2. This effect was therefore termed signal enhancement by extravascular protons (EEP). By incorporating the constant values ( 0 0 and T 2 T 2 ), the mathematical model can be simplified and expressed as two terms describing primarily the and EEP effects, although the two effects are not completely separable: EEP [5] Mathematical Modeling In an attempt to explain the above observations we proposed a mathematical model comprising two water compartments denoted and, each with protondensity and T 2 values that are assumed to vary between task and non-task conditions of the fmri experiment (12). In the following description the signal intensity arising from each compartment during nontask conditions is denoted as 0 and 0 at TE 0, where 0 expte 1 T expte 1 T EEP 0 0 expte 1 T 2 [6] [7]

4 fmri OF HUMAN BRAIN AND PINAL CORD BY EEP 31 Table 1 Average ignal Intensity Changes Detected at 3 T with Healthy ubjects (GE, TE 30 s) (GE, TE 12 s) EEP (E, TE 22 s) All active pixels Two-hand motor task (n 12) % % % Visual stimulation (n 6) % % % 100 Pixels with highest T scores Two-hand motor task (n 12) % % % Visual stimulation (n 6) % % % The subjects were performing a two-hand finger touching task or observing a checkerboard pattern alternating contrast at 8 Hz. The results shown are averaged over all pixels identified as being active (T values higher than the correlation threshold) and for only those pixels with the 100 highest T values with each method. In these expressions we have also included the terms (1/T 2 ) (1/T 2 1/T 2 ) and (1/T 2 ) (1/ T 2 1/T 2 ). Equation [6] is very similar to the usual expression given in Eq. [1], and these two expressions become identical if 0 is negligible or (1/T )issufficiently large and the TE is within the typical range used for fmri studies. Equation [7] is dominated by the fractional proton-density change in the faster relaxing water compartment (). The T 2 values of the more slowly relaxing compartment (, 172 ms at rest and 200 ms during the task conditions) correspond to T 2 values of blood at 1.5 T with the oxygenation increasing from approximately 80% at rest to 85% during the task condition (13), thus representing the signal changes. The faster relaxing component showed a small increase in proton density of 5.6% with no change in T 2 values; as we concluded, it describes the EEP signal changes. EEP fmri tudies in Brain Confirmation that the EEP effect also occurs in the brain was obtained with a study carried out at 1.5 and 3 T with healthy volunteers subjected to a visual stimulus (4). As with the spinal fmri, data were again acquired with spin echo and gradient echo EPI with a range of TEs, and fractional signal changes were plotted as a function of the TE. The slopes of linear fits to the data were consistent with those reported by others (3, 14) and had values of and s 1 for (1/T* 2 ) and (1/T 2 ), respectively, at 1.5 T. At 3 T these values were and s 1, respectively. The ratio between (1/T* 2 ) and (1/T 2 ) was larger than 3.5 as expected from the model, and we also observed the roughly linear dependence on field strength as expected (3). However, the zero-intercept values were significantly greater than zero for the spin echo data with values of and % at 1.5 and 3 T, respectively. Conversely, gradient echo data did not have zero-intercept values that were significantly greater than zero ( and %, respectively). These results demonstrate that the positive zero-intercept value also occurs in the brain when spin echo fmri is used and confirms that the non- contribution exists as in the spinal cord. The zero-intercept values observed in the spinal cord, however, are roughly 3 times larger than those observed in the brain. This observation provides a clue to the source of the EEP signal changes and confirms that the positive zero-intercept values cannot be due to in-flow effects, diffusion, steady-state effects, or artifactual signal changes. These four factors do not depend on whether the signal is acquired from the brain or spinal cord but rather on the imaging method and acquisition parameters. Thus, the much larger zero-intercept values observed in the spinal cord cannot be attributed to the acquisition parameters or imaging method, instead reflecting physiological properties and possibly relating to the fact that the blood spinal cord barrier is more permeable to many substances than the blood brain barrier (15, 16). Further support for the theory that water crosses the blood vessel walls to cause an increase in the local extravascular water content is provided by positron emission tomography (PET) studies (17, 18). Experiments with radiolabeled water showed that upon tactile stimulation, an increase in the amount of extravascular tracer was observed in the somatosensory area of the brain corresponding to the hand. These studies also showed an increase in the amount of intravascular tracer slightly more downstream. This finding supports the theory of EEP, which requires an increase of intravascular pressure, and so would have to occur in the capillaries and arterioles. It may not occur in the more compliant venules and veins where the pressure is not expected to be increased, and it is the primary site of the signal changes.

5 32 TROMAN, TOMANEK, AND MALIZA Figure 2 (a) An averaged activation map for 12 subjects showing consistent regions of activity (TE 30) in red and EEP activity in blue, which is green where it overlaps the activity. ubjects performed a finger touching task with both hands. Brighter colors indicate greater numbers of subjects with activity at that pixel. lices span from z 32 mm (top left) to z 54 mm (bottom right). (b) The averaged activation map for 6 subjects showing consistent regions of activity (TE 30) in red and EEP activity in blue, which is where it overlaps the activity. ubjects observed a checkerboard pattern alternating at 8 Hz. Brighter colors indicate greater numbers of subjects with activity at that pixel. lices span from z 14 mm (top left) to z 14 mm (bottom right). In order to test the hypothesis that the EEP effect in the brain is related to the hemodynamic changes that occur with changes in neuronal activity, fmri studies were carried out with proton-density weighted spin echo EPI at 3 T. In the same studies, fmri data were acquired with conventional methods (gradient echo EPI, TE 30 ms) and with reduced sensitivity (gradient echo EPI, TE 12 ms). EEP fmri data were acquired with spin echo EPI with a TE of 22 ms. Common to all acquisitions, the field of view was set at 25 cm, a matrix was acquired, a 5 mm slice thickness with 16 contiguous slices to span almost the entire brain was maintained, and a 5 s TR and a flip angle of 90 were used. Experiments were carried out with the subjects performing a two-hand finger touching task and with visual stimulation provided by a checkerboard pattern alternating contrast at 8 Hz. The results of these studies demonstrated consistent areas of activity with all three methods, and the signal changes are listed in Table 1 for all active pixels and for only the 100 pixels with the highest T values with each method. The analyses of only active pixels identified in common with the and EEP methods yielded similar results. Areas of activity identified with fmri with a short TE of 12 ms fell within the regions identified with a TE of 30 ms, as expected. On the other hand, EEP fmri did not demonstrate areas that overlapped appreciably with the regions. Average activity maps comparing conventional and EEP fmri are shown in Figure 2(a,b). The EEP areas overlapped with only 3% of the active pixels detected with fmri at a TE of 30 ms and were mostly in adjacent areas. These results again confirmed that the EEP signal changes cannot be attributed to residual sensitivity and that regions of activity identified with the two methods are not precisely the same. A comparison of and EEP fmri results from a single subject is shown in Figure 3. The areas of activity identified with EEP correspond closely to expected areas of increased neuronal activity with the stimuli applied. The relative locations of and EEP areas of activity also correspond well with those identified in PET studies as areas of increased intravascular tracer volume and Figure 3 The areas of activity identified in a single subject performing a two-hand finger touching task. The fmri data obtained with gradient echo EPI (TE 30 ms) yielded the areas shown in red to yellow, whereas data obtained with spin echo EPI (TE 22 ms) yielded the areas of activity shown in green. lices span from z 50 to 56 mm and the T-score threshold was 2.6 (corresponding to p 0.01). Data were analyzed with PM99 (A tatistical Parametric Mapping) (20).

6 fmri OF HUMAN BRAIN AND PINAL CORD BY EEP 33 increased extravascular tracer. Detailed analyses of the contrast to noise ratio (CNR) were also carried out and demonstrated that the EEP CNR can equal or exceed that obtained with fmri. Considering the contrast as the peak signal change from baseline during stimulation periods and the noise level as the standard deviation of the signal during the first nontask period, the CNR values determined with a twohand finger task were 7.5 and 10.4 for and EEP, respectively. With visual stimulation the respective CNRs were 6.9 and 9.9, respectively. The results were similar when only the pixels with the 100 highest T values were included. For the two-hand motor task these analyses yielded CNR values of 7.0 and 6.8 for and EEP, which were 5.2 and 6.1, respectively, with visual stimulation. These findings confirm that EEP signal changes can be detected in the brain concomitant to neuronal activation and that they are not in origin. Moreover, previous studies of EEP signal changes in the spinal cord and results of PET studies provide strong support for the hypothesis that the EEP signal changes arise from an increase in extravascular water, primarily around capillaries and precapillary arterioles. This model of the EEP signal changes can account for the fact that areas of activity are adjacent to those identified with and that average areas of activity are much more localized. This also corresponds well with the results of PET studies (17, 18), which have clearly identified areas of increased extravascular radiolabeled water tracer at sites of neuronal activity in somatosensory areas of the brain. CONCLUION The work we have carried out has provided very strong evidence that there is indeed a non- contribution to signal changes in spin echo fmri data, arising from changes in the extravascular water content at sites of neuronal activation. We therefore termed the effect EEP. Others have also suggested that there may be such a contribution to fmri signal changes (19). However, the fmri data we obtained in the spinal cord demonstrated that the EEP effect is 3 times larger than that observed in the brain and enabled us to confirm its existence. PET studies also corroborate this conclusion (17, 18). The benefits of EEP fmri lie in the fact that the method is based on a spin echo acquisition with a short TE. Although the signal intensity changes detected with EEP are slightly lower than with, the signal to noise ratio of the image data is higher, resulting in an equal or higher CNR. The inherent lower sensitivity of spin echo methods to field inhomogeneities makes EEP fmri less sensitive to imperfections in shimming or susceptibility differences. As a result, fmri studies may have substantially higher quality with EEP contrast in areas such as the frontal lobe, temporal lobes, midbrain, or other areas that typically present difficult shimming. In addition, EEP may demonstrate more precise spatial localization to areas of neuronal activity because it likely only shows capillaries and arterioles where the intravascular pressure is increased, rather than areas of draining veins. The drawback of EEP fmri is that it is not expected to provide physiological information about the oxygen metabolism of neural tissue in the brain, as do data. However, EEP may be able to provide other information about the fluid balance across the blood brain barrier and identify areas of altered blood brain barrier permeability and changes in intravascular pressure. ACKNOWLEDGMENT We gratefully acknowledge the support of the Canadian Institutes of Health Research and thank Ms. V. Krause, Dr. U. N. Frankenstein, Ms. J. Lawrence, Ms. A. Bergman, and Ms. A. Allman for helpful input to this work. REFERENCE 1. Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A. Neurophysiological investigation of the basis of the fmri signal. Nature 2001; 412: Menon R, Ogawa, Tank DW, Ugurbil K. 4 Tesla gradient recalled echo characteristics of photic stimulation-induced signal changes in the human primary visual cortex. Magn Reson Med 1993; 30: Bandettini PA, Wong EC, Jesmanowicz A, Hinks R, Hyde J. pin echo and gradient echo EPI of human brain activation using contrast: A comparative study at 1.5 T. NMR Biomed 1994; 7: troman PW, Krause V, Frankenstein UN, Malisza KL, Tomanek B. pin echo versus gradient echo fmri with short echo times. Magn Reson Imaging 2001; 19: Gati J, Menon R, Ugurbil K, Rutt BK. Experimental determination of the field strength dependence in vessels and tissue. Magn Reson Med 1997; 38: Bandettini PA, Wong EC. Magnetic resonance imaging of human brain function. Principles, practicalities, and possibilities. Neurosurg Clin N Am 1997; 8: Yacoub E, Duong T, Adriany G, Kim G, Ugurbil K,

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