Perfusion MR imaging with pulsed arterial spin-labeling: Basic ...

Perfusion MR Imaging With Pulsed Arterial Spin-Labeling: Basic Principles and Applications in Functional Brain Imaging YIHONG YANG Functional Neuroimaging Laboratory, Department of Psychiatry, Weill Medical College of Cornell University, New York, New York

ABSTRACT: Basic principles of the arterial spin-labeling perfusion MRI are described, with focus on a brain perfusion model with pulsed labeling. A multislice perfusion imaging sequence with adiabatic inversion and spiral scanning is illustrated as an example. The mechanism of the perfusion measurement, the quantification of cerebral blood flow, and the suppression of potential artifacts are discussed. Applications of the perfusion imaging in brain activation studies, including simultaneous detection of blood flow and blood oxygenation, are demonstrated. Important issues associated with the applications such as sensitivity, quantification, and temporal resolution are discussed. © 2002 Wiley Periodicals, Inc.

Concepts Magn Reson 14: 347–357, 2002

KEY WORDS: perfusion MRI; cerebral blood flow; arterial spin labeling; brain activation

INTRODUCTION Perfusion MR imaging with arterial spin-labeling (ASL) was introduced by Detre et al. (1), who demonstrated the mapping of cerebral blood flow (CBF) in Received 13 December 2001; revised 4 April 2002; accepted 12 April 2002 Correspondence to: Yihong Yang, Ph.D., Functional Neuroimaging Laboratory, Department of Psychiatry, Weill Medical College of Cornell University, 525 E. 68th St., Box 140, Room F-1306, New York, NY 10021. E-mail: [email protected] Contract grant sponsor: the Whitaker Foundation. Concepts in Magnetic Resonance, Vol. 14(5) 347–357 (2002) Published online in Wiley InterScience (www.interscience.wiley. com). DOI 10.1002/cmr.10033 © 2002 Wiley Periodicals, Inc.

rats by employing a combination of repeated saturation (or inversion) in the neck region and imaging in a brain slice. The perfusion technique has evolved into two major categories: 1) continuous labeling, in which the inflowing spins are tagged continuously at a labeling site and delivered to the imaging site until a steady-state is reached (2– 6); and 2) pulsed labeling, in which the spins in feeding arteries are tagged by a relatively short RF pulse (7–12). In continuous ASL techniques, spins in the carotid artery can be labeled for small animals (e.g., rats), while in humans the labeling site is usually a few centimeters below the imaging slice due to the long transit time in human brain. In pulsed ASL techniques, labeling can be placed on the spins on the inflowing side of the imaging slice (7, 12), or on the entire spins outside the 347

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Figure 1 (a) Positions of the imaging slice and of the labeling sites in pulsed ASL perfusion imaging. The labeling can be placed on the spins flowing into the imaging slice (upper), or on the entire spins outside the imaging slice (lower). (b) Schematic illustration of the labeling (inversion) of the spins in the arteries and the transit and trailing times for the labeled spins traveling from the labeling site to the capillary/tissue exchange site.

imaging slice (8, 9), as illustrated in Fig. 1a. Quantitative CBF measurement is achievable with ASL perfusion techniques by carefully addressing the potential confounds in the techniques. The major difficulties include the magnetization transfer effect, the uncertainty of transit time, the contribution of tagged arterial blood to the perfusion images, the water extraction fraction, and the imperfection of the slice (or slab) inversion profile, which could give rise to a significant over- or underestimate of CBF (4, 6, 10, 11, 13, 14, 17–19) (more details are discussed below). In the past, tremendous effort has been ap-

plied to suppress these potential artifacts for quantification of cerebral blood flow. ASL perfusion techniques have shown promise in the mapping of cerebral hemodynamics during brain activation (7, 8, 11, 20 –22). The reduced invasiveness compared to exogenous contrast administration allows repeated measurements within a study session and makes the techniques more applicable for brain functional studies with complex stimulation paradigms. Compared to relatively venous-weighted blood oxygenation level-dependent (BOLD) methods, the perfusion techniques may target signal changes more closely related to neuronal activity and provide quantitative CBF values for better data interpretation. With suppression of major artifacts, quantitative CBF values during brain activation have been obtained (4, 6, 11, 12). Recently, combined perfusion and BOLD images were used to measure cerebral metabolic rate of oxygen consumption (CMRO2) (23–25). These techniques may provide information for better understanding of the relationship between BOLD signal, blood flow, and oxygen consumption in the activated brain. In addition, ASL perfusion techniques have been developed for quantitative measurement of cerebral blood flow in animal studies (26, 27). In this article, the fundamental principles of ASL perfusion imaging are described, with focus on a representative pulsed ASL technique (flow-sensitive alternating inversion recovery, or FAIR), although several other strategies have been proposed for ASL perfusion imaging (7, 12). Applications of ASL perfusion imaging in functional brain studies, particularly the simultaneous detection of perfusion and BOLD signals, are demonstrated.

BASIC PRINCIPLES Perfusion is the amount of arterial blood delivered to a local volume of tissue per unit time, which is usually quantified as milliliter of blood per gram of tissue per second (ml/g/sec). Perfusion determines the effectiveness of the blood circulation to provide oxygen and nutrients to the tissue and to remove waste products from the tissue. Perfusion measurements provide information about tissue viability and function and are therefore of fundamental significance in medical research and clinical diagnostics. In particular, local perfusion changes in the brain reflect regional cerebral activity and metabolism and thus can be used as an index for mapping functional neuroanatomy (28).

PERFUSION MRI WITH PULSED ASL

Perfusion Model With Transit and Trailing Times

Solving Eq. [4], the amplitude of the difference image at time t is obtained as (11):

ASL perfusion imaging approaches use magnetically labeled arterial water as an endogenous tracer to obtain information about blood flow in the tissue. The labeling is usually accomplished by inverting (or saturating) the inflowing arterial spins with respect to the tissues of interest, as illustrated schematically in Fig. 1. A perfusion model describing the blood/tissue water exchange kinetics and the magnetization characteristics is needed to calculate blood flow from the measurements. The Bloch equation for tissue water including flow can be described as (1): dM共t兲 M 0 ⫺ M共t兲 ⫽ ⫹ Q关M a共t兲 ⫺ M v共t兲兴 dt T1

[1]

where M0 is the amplitude of the fully relaxed signal, Q is the cerebral blood flow, T1 is the longitudinal relaxation time of water in tissue, M(t), Ma(t), and Mv(t) are the magnetization of water in tissue, arterial blood, and venous blood, respectively. Assuming water is freely diffusible (Mv ⫽ M/␭), where ␭ is the tissue to blood partition coefficient, Eq. [1] can be rearranged as: dM共t兲 M共t兲 M 0 ⫺ ⫽ QM a共t兲 ⫹ dt T 1app T1

[2]

where T1app is the apparent longitudinal relaxation time defined as 1/T1app ⫽ 1/T1 ⫹ Q/␭. In FAIR perfusion imaging, pulsed arterial labeling is performed by comparing images preceded alternatively by a slice-selective inversion (labeling) or a nonselective inversion (control) pulse (8, 9). The difference of arterial blood magnetization between the labeled and control experiments is:

⌬M a共t兲 ⫽

冦

0, 0 ⱕ t ⬍ ␶a 2QM 0 exp共⫺t/T1a 兲, ␶a ⱕ t ⬍ ␶d ␭ 0, t ⱖ ␶d [3]

where ␶a and ␶d are arterial transit and trailing times (4, 14, 15), respectively (Fig. 1b), and T1a is the longitudinal relaxation time of arterial blood. Thus, the difference image between the labeled and control images, ⌬M(t), can be expressed as: d⌬M共t兲 ⌬M共t兲 ⫹ ⫽ Q⌬M a共t兲 dt T 1app

349

[4]

⌬M共t兲 ⫽ f 1 ⫽ 0, for 0 ⱕ t ⬍ ␶a M0

[5]

⌬M共t兲 1 ⫺R 1at ⫽ f 2 ⫽ ⫺2 䡠 Q/␭ 䡠䡠e M0 ␦R ⫻ 兵1 ⫺ e⫺␦R䡠共t⫺␶ a兲其, for ␶a ⱕ t ⬍ ␶d

[6]

⌬M共t兲 ⫽ f 3 ⫽ f 2共t ⫽ ␶ d兲䡠 e ⫺R1䡠共t⫺␶d兲, for t ⱖ ␶d M0

[7]

where R1 ⫽ 1/T1, R1a ⫽ 1/T1a, and ␦R ⫽ R1a ⫺ R1. Tissue perfusion (Q) can then be calculated from Eqs. [5–7] if ␶a, ␶d, R1, and R1a are known. It is worth mentioning that the perfusion model can also be derived from the tracer kinetic theory (29). Based on the perfusion model, MR signals in different types of tissues (e.g., gray and white matter), in different physiological states (e.g., at rest and during activation), and at different field strengths can be estimated. As an example, the signal intensity in the difference image (⌬M) as a function of inversion time (TI) for gray and white matter is shown in Fig. 2a. CBF values in gray and white matter were assumed to be 65 and 25 ml/100g/min, respectively, for the calculation (11, 17). Typical T1 values for the two types of tissues at 1.5 T (0.9 for gray matter and 0.5 for white matter) (30) were used for the plots. Transit and trailing times were assumed to be 0.65 and 2.05 s, respectively, based on recent studies (18, 31, 32). It is shown in the figure that perfusion signals in the gray matter are 2–3 times greater than in white matter, due primarily to the higher blood flow in gray matter. This results in different contrast-to-noise ratios (CNRs) in gray and white matter and leads to different uncertainty levels in the CBF measurements for the two tissues. Figure 2b shows the perfusion signals at rest and activated states in gray matter. It is well known that CBF increases during increased brain activity (28). The CBF values used for the plots were 65 ml/100g/ min (rest) and 120 ml/100g/min (activation) (31). Transit and trailing times were assumed to be 0.65 and 2.05 s at rest and 0.54 and 1.80 s during activation, based on an activation study with a sensorimotor stimulation paradigm (31). It is worth noting that the sizable changes of transit and trailing times during brain activation can affect blood flow quantification if the changes are not taken into account. Simulation studies have been performed to examine the potential

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retical prediction (34). It is anticipated that the perfusion signal at 7 T (T1 ⬃1.9 s) (35) would be approximately 50% greater than at 1.5 T. In addition, signalto-noise ratios (SNRs) in the control (nonslabselected) and labeling (slab-selected) images increase superlinearly with field strength, although the reduced T *2 at higher fields could affect the SNR adversely. Nevertheless, ASL perfusion imaging should be advantageous at high fields with the increased perfusion contrast and better SNR in the raw images (control and labeled). The perfusion model can be simplified considerably when ␶a ⫽ 0 and ␶d ⫽ ⬁. In fact, transit time can be reduced by employing better inversion pulses with sharp edges, such as FOCI (frequency offset-corrected inversion) adiabatic pulses (38, 39). Trailing time can be increased with a body coil for inversion, although a separate coil is usually needed to receive signals since the sensitivity of body coils are poor. Transit and trailing times can be measured from a set of perfusion images acquired at different TI values by least-square fitting of the perfusion image intensities to the perfusion model described above (11, 31).

Implementation of ASL Perfusion Imaging

Figure 2 Perfusion signals (⌬M) estimated from the perfusion model with arterial transit and trailing times. (a) Perfusion signals in gray and white matter at 1.5 T. (b) Perfusion signals in gray matter at rest and during activation. (c) Perfusion signals in gray matter at the field strengths of 1.5, 3, and 7 T.

errors in CBF measurements caused by ignoring the times or the changes of the times during brain activation (31). It has been shown that a significant underestimation of CBF would be introduced if the times were not taken into account (␶a/␶d ⫽ 0/⬁). Furthermore, an overestimation or underestimation of CBF would be caused (depending on the TI value) by using the times at resting state (␶a/␶d ⫽ 0.65/2.05) to calculate CBF during activation (␶a/␶d ⫽ 0.54/1.80). In the TI range (1.0 –1.8 s) typically used for CBF measurement, an error of 10 –30% would be introduced. Perfusion signals at different magnetic fields (1.5, 3, and 7 T) are plotted in Fig. 2c. The signal increase at higher fields is primarily due to the elongated T1. It has been shown experimentally that the perfusion signal increased around 30% at 3 T (T1 ⬃1.3 s) (33) compared to 1.5 T (T1 ⬃0.9 s), confirming the theo-

The basic elements of ASL perfusion imaging sequence include spin inversion, image acquisition, and crusher gradients for suppressing artifacts. Multislice perfusion measurement can be achieved by fast image scanning in multiple sections after the inversion (labeling). Single-shot echo-planar imaging (EPI) and spiral imaging techniques are usually chosen for image acquisition due to their rapid scanning speed. Spiral imaging may have additional advantages such as shorter acquisition window (allowing for more slices per labeling), shorter echo time (for better SNR), and relative insensitivity to motion artifacts (36). Other fast imaging sequences such as RARE (rapid acquisition with relaxation enhancement) and HASTE (half-Fourier single shot turbo spin-echo) have been employed to ASL perfusion imaging as well. Adiabatic inversion pulses (37) are commonly employed for spin inversion due to their excellent inversion profiles and their insensitivity to RF inhomogeneity (when the RF intensity reaches a threshold). Recently, a type of improved adiabatic inversion pulse, FOCI (38), has been implemented in ASL perfusion imaging to improve the slab inversion profile (39). Figure 3 shows a comparison of inversion profiles of a hyperbolic secant (HS) pulse and a FOCI pulse, obtained from a Bloch equation-based simulation. It is evident that the FOCI inversion profile has much sharper edges, which would reduce transit time,


Figure 3 A comparison of inversion profiles of a hyperbolic secant (HS) pulse and a FOCI pulse obtained from a Bloch equation-based simulation.

as mentioned above, as well as minimize subtraction errors near the edges. In principle, other types of inversion pulses can also be used in ASL perfusion imaging, as long as they have good inversion profiles. Bipolar crusher gradients are often used in ASL imaging to suppress signals contributed from arteries that pass through the imaging slice but do not supply capillaries (“nonfeeding” arteries) (11, 17). Without these suppression gradients blood flow will be overestimated in ASL imaging techniques. As an example, Fig. 4 illustrates a recently developed quantitative, multislice ASL perfusion imaging technique (11, 39). Multislice perfusion measurement is accomplished by a combination of a pulsed arterial spin labeling and fast spiral scanning (40, 41). A FOCI inversion pulse (combined with slab selection gradients) is used for alternating slab-selective and nonslab-selective inversion, followed by an inversion time (TI) delay and a multislice image acquisition. Bipolar gradients are applied after each excitation pulse to suppress signals from intra-arterial spins.

Quantitative Measurement of CBF Blood flow quantification could be affected by a number of potential artifacts in ASL perfusion techniques, including the magnetization transfer effect (particularly in continuous ASL with single coil), the uncertainty of transit time, the contribution of tagged arterial blood to the perfusion images, the fraction of water extraction, and the imperfection of inversion profiles (4, 6, 10, 11, 14, 17–19). These artifacts could result in significant over- or underestimation of CBF. Issues with regard to transit/trailing time uncertainty and inversion profile imperfection have been dis-

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Figure 4 Pulse sequence for multislice ASL perfusion imaging. An adiabatic inversion pulse is used for labeling inflowing arterial spins, followed by an inversion time (TI) and a multislice image acquisition using spiral scanning. Alternating slab-selective and nonslice-selective inversion are performed and crusher gradients are applied between each excitation pulse and image acquisition for suppressing signals from interarterial spins.

cussed above; in this section we focus on discussion of the other factors. Magnetization transfer effect (13), caused by offresonance RF irradiation used for spin labeling, decreases the steady-state longitudinal magnetization of water protons in brain tissue. This effect has been a concern with continuous ASL techniques, where the RF irradiation is applied for long periods (on the order of a few seconds). To suppress the effect, a control experiment using an off-resonance RF irradiation with an opposite frequency offset are needed (2, 5, 14). The magnetization transfer effect is much less in pulsed ASL techniques due to the significantly shorter inversion time. In continuous ASL techniques this problem can be circumvented by using two coils, one placed on the neck to tag arterial blood while another is used to acquire images. This approach has been used in rats and humans (15, 16), although there are concerns about potential confounds caused by long transit time and technical difficulties to implement the method. The contribution of tagged arterial blood to the perfusion images can be suppressed by bipolar gradients after each excitation pulse, as suggested in several studies (11, 17). The crusher gradients generate first-order gradient moment at the time of signal acquisition and the resulting velocity-dependent phase shifts lead to loss of intra-arterial signal because of the steep radial flow gradients across the arterial lumen. Perfusion experiments showed that the signal intensity in gray matter was artificially high without the crusher gradients, particularly in brain areas with non-

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feeding arteries (11, 17). However, with appropriate suppression of these artifacts quantitative cerebral blood flow can be obtained. Most perfusion models assume that water is a freely diffusible tracer and that water exchange between capillaries and brain tissues is instantaneous. However, there is evidence that this assumption is not valid under conditions of high blood flow rates (42). It has been demonstrated in H15 2 O PET experiments that restricted water exchange led to underestimation of CBF values at high flow rates (43). The relationship between water extraction E(Q) and blood flow Q can be described as E(Q) ⫽ 1 ⫺ exp(⫺P 䡠 S/Q), where P is the capillary permeability and S is the capillary surface area (42). A noninvasive method has been developed to estimate the water extraction fraction (44). Efforts have been made to assess the effect of restricted water exchange on blood flow quantification (18, 19). With further characterization of the influence of water extraction fraction on blood flow measurement it might be possible to account for the factor and make the perfusion measurement more accurate (44). Due to the confounding factors in ASL perfusion techniques it is important to compare CBF values obtained from ASL techniques with those determined from a “gold standard” approach. Studies on rats showed that CBF values in gray matter measured with ASL techniques were consistent with the values obtained from iodoantipyrene autoradiography and radioactive microsphere approaches (45, 46). A study on human brain (47) showed that for a “cortical strip” region-of-interest (ROI) CBF values measured from an ASL technique were not statistically different from the values determined from H15 2 O PET. However, for a central white matter ROI, CBF values from the ASL method were significantly underestimated compared to the values obtained from H15 2 O PET.

Temporal and Spatial Resolution Temporal resolution is usually low in current ASL perfusion techniques because the perfusion image is obtained from a subtraction of two raw images, resulting in a temporal resolution at least double that of the raw images. Additional time duration (TI) is required for inverted spins to recover, leading to a typical temporal resolution of 4 – 8 s in ASL perfusion imaging. This poor temporal resolution using existing techniques makes event-related functional study (48, 49) almost impossible. Recently, several pulsed ASL techniques with improved temporal resolution have been suggested (50 –53). Strategies such as “intertrial subtraction” and “stimulus shifting” were employed to substantially increase temporal resolution in ASL

perfusion imaging and to facilitate perfusion-based event-related brain activation studies (52). Temporal resolution of 0.5–1.0 s has been achieved for ASL perfusion imaging and event-related functional brain studies on human brain have been demonstrated using these techniques (51–53). In addition, a pseudo-continuous ASL technique has been demonstrated to measure CBF changes during activation on rats, with temporal resolution on the order of 0.1 s (50). In-plane spatial resolution in ASL imaging depends on the image acquisition technique employed. Single-shot fast scanning techniques (e.g., EPI and spiral) are commonly used for minimizing fluctuations between scans. In-plane resolution of these fast imaging techniques is usually 3– 4 mm. Spatial resolution can be increased by using multishot EPI or spiral scanning or more conventional imaging techniques, with the precaution that temporal resolution might be reduced and motion artifacts might be more prominent.

APPLICATIONS IN FUNCTIONAL BRAIN IMAGING In recent years ASL perfusion imaging techniques have been successfully used for cerebral activation studies (7, 8, 11, 20 –22). The mechanism underlying detection of brain activation is that increased cerebral activity is accompanied by local changes in CBF, as demonstrated by PET studies (28, 54). In perfusionbased studies, as in BOLD functional imaging, a series of images is acquired while subjects perform specific tasks. Activation studies with visual and sensorimotor paradigms (7, 8, 11, 20 –22), as well as with cognitive paradigms (55), have been carried out using ASL perfusion techniques. With suppression of the major artifacts, quantitative CBF values during increased brain activity can be obtained. The increases in CBF during activation varied from 30 –90%, depending on the activation paradigms (7, 8, 11, 20 –22), and in general were consistent with the CBF values observed in PET studies (54). Compared to BOLD methods, which are relatively venous-weighted, the perfusion techniques target signals closer to the capillaries and tissues and may therefore be more closely related to neuronal activity. In addition, the quantitative CBF measurement provides a physiologically and biophysically more meaningful parameter for better data interpretation. Recently, perfusion and BOLD signals have been detected simultaneously (10, 21, 52, 56 –58) and the combined perfusion and BOLD images have been used to measure cerebral metabolic rate of oxygen consumption (CMRO2) (23–25).


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Figure 5 An example of brain activation experiments with simultaneous detection of perfusion and BOLD signals. Temporal resolution was improved using intertrial subtraction and stimulus shifting. A sensorimotor stimulus paradigm was employed in the study. (a) Activation maps obtained from the perfusion and BOLD signals (t ⬎ 4.2; P ⬍ 0.01). (b) Temporal responses of the perfusion and BOLD signals in the activated regions.

Sensitivity of Detecting Brain Activation Sensitivity of ASL perfusion techniques is inherently low because the perfusion-related signal is small

(⬍1%) and ASL techniques require image subtraction to obtain blood flow information. In brain activation studies, another subtraction is needed to compare blood flow changes between rest and activation states.

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In general, perfusion CNR is lower than BOLD CNR in brain activation studies (10, 11, 23), although the CNR difference of the two techniques depends on a number of factors, including perfusion/BOLD methodologies and image acquisition parameters. In a typical activation study, a time series of images (containing dozens of perfusion images) is collected over several minutes and the data are averaged to reach sufficient CNR for detecting activated brain areas. Compared to BOLD imaging, however, the pair-wise subtraction in ASL perfusion imaging reduces artifacts caused by head movement and instrumental instability during scanning. In addition, perfusion CNR can be significantly improved at higher fields due to elongated T1 of brain tissues and increased SNR in the raw (control and labeled) images. A recent study comparing perfusion signals at different field strengths showed that the perfusion CNR at 3 T was 2–3 times better than at 1.5 T (34).

Simultaneous Measurements of Blood Flow and Blood Oxygenation Perfusion and BOLD signals can be measured simultaneously in a single scan session using pulsed ASL imaging techniques (10, 21, 52, 56 –58). Perfusion signal is obtained by labeling the in-flowing spins in arteries, while BOLD contrast is achieved by effective transverse relaxation (T *2 ) weighting. From a series of ASL images acquired with alternating control and labeling, perfusion and BOLD signals can be obtained by subtracting or adding the control and labeled images, respectively, in the same data sets. Simultaneous detection of perfusion and BOLD signals has a number of advantages, including efficient acquisition of two functional images and minimization of temporal and spatial variations in the two signals. Furthermore, with improved temporal resolution (50 –53) and simultaneous CBF and BOLD detection the perfusion impulse-response function (IRF) during brain activation can be characterized and compared directly to the BOLD response. An example of simultaneously measured perfusion and BOLD activation maps with a sensorimotor paradigm is shown in Fig. 5a. The perfusion and BOLD signals are shown in Fig. 5b. The functional experiment was performed at 1.5 T with a finger movement paradigm cued by video instructions for precise task onset times (52). The task was performed for a duration of 2 s with an interstimulus interval of 14 s. Temporal resolution of the perfusion imaging was 1 s using intertrial subtraction and stimulus shifting. This experiment demonstrated the feasibility of simultaneous measurement of CBF

and BOLD signals with high temporal resolution for characterizing the hemodynamic responses during brain activation. The shape of the perfusion response curves was generally similar to the BOLD curves, with an initial delay and rising phase (⬃4 s) followed by a peak (3– 4 s) and then a drop-off period (4 –5 s). However, the perfusion response curve rises slightly prior to and drops earlier than the BOLD curve. The maximum perfusion signal change in the sensorimotor study was ⬃48% and the maximum BOLD signal change was ⬃0.92%.

CONCLUSION This article has delineated the fundamental principles of perfusion imaging techniques using pulsed arterial spin-labeling. A perfusion model for pulsed ASL imaging has been described in detail to illustrate the mechanism of perfusion measurement. Implementation of a multislice perfusion imaging sequence with adiabatic inversion and spiral scanning has been illustrated. Important issues in ASL perfusion techniques such as quantification of CBF, suppression of potential artifacts, perfusion CNR, and temporal and spatial resolution were discussed. The utility of perfusion imaging techniques in brain activation studies, including simultaneous perfusion/BOLD detection, has been demonstrated.

ACKNOWLDGEMENTS The author thanks Drs. Joseph A. Frank, Jeff H. Duyn, Martin N. Yonbi, Frank Q. Ye, and Alan C. McLaughlin at the National Institutes of Health and Drs. David A. Silbersweig, Emily Stern, and Tracy Butler at the Weill Medical College of Cornell University for helpful discussions.

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BIOGRAPHY Yihong Yang received his Ph.D. degree in Biophysics from the University of Illinois at Urbana-Champaign in 1995. His Ph.D. studies were on magnetic resonance diffusion imaging and spectroscopic imaging, under the supervision of Professor Paul C. Lauterbur, the founder of magnetic resonance imaging. He was a postdoctoral fellow (1995– 1998) at the National Institutes of Health, developing functional MRI techniques for brain activation studies. In 1998 he joined the Functional Neuroimaging Laboratory at the Weill Medical College of Cornell University as an Assistant Professor. His research interests include MR perfusion imaging, BOLD imaging, diffusion tensor imaging, and MR spectroscopy.