Blood flow quantification of the human retina with MRI

Received: 11 March 2010, Accepted: 21 April 2010, Published online in Wiley Online Library: 22 September 2010

Blood flow quantification of the human retinawith MRINasim Malekia*, Weiying Daib and David C. Alsopb

The purpose of this study was to investigate the feasibility of measuring blood flow to the retina using arterial spinlabeling MRI, a quantitative, noninvasive tomographic technique. Blood flow imaging was performed in a single axialslice through both eyes of five healthy volunteers with no history of retinal diseases. The imaging was optimized tominimize the errors from motion and nonuniform magnetic fields caused by proximity to the sinuses. Keyhemodynamic factors for flow quantification, including arterial transit delay and the apparent decay time of thesignal, were estimated by repeated measurements with different arterial spin labeling timing. A clearly elevatedsignal, consistent with the anatomical location of the retina, was observed in all subjects. The measured blood flow toa 1 cmT 1.47 cm section of the retina, centered on the fovea, was 1.75W 0.54mL/mm2/min (total blood flow of261W 87mL/min). The arterial transit delay from a labeling plane 5 cm below the slice was 1137W 288ms. Theseresults establish the feasibility ofmeasuring blood flow to the retinawithMRI, and support the future characterizationof the healthy and diseased ocular circulation with this method. Copyright � 2010 John Wiley & Sons, Ltd.

Keywords: MRI; arterial spin labeling; arterial spin tagging; perfusion; hemodynamics; background suppression;quantification; blood flow; retina; choroid

INTRODUCTION

The retina is one of the most metabolically active tissues in thebody. The functional integrity of the retina relies on an adequatevascular perfusion level. The supply of nutrients to the retina,together with the removal of waste products, is achieved byblood flowing through two vessel systems – the inner retinal andchoroidal circulations – which feed the inner and outer layers ofthe retina, respectively. The inner retinal circulation primarilyfeeds the neural retina which sends impulses to the visual cortex,whereas the choroidal circulation feeds the retinal pigmentepithelium/Bruch’s membrane/photoreceptor complex, the siteof phototransduction. The choroidal blood flow is 10–15 timeshigher than the cortical blood flow.Alterations of ocular blood flow are associated with many of

the most prevalent eye diseases, including age-related maculardegeneration (1–3), diabetic retinopathy (4) and glaucoma (5). Indiabetic retinopathy and, perhaps, age-related macular degener-ation, there is an indication that blood flow or other vascularabnormalities may play a causal role. In other diseases, flowabnormalities may be a useful correlative indicator of underlyingpathology. For these reasons, the development of techniques forassessing hemodynamic parameters in the retina has been animportant priority for both clinical and research purposes.Although flow measurements in most organs have been

pioneered using nuclear medicine methods, and nuclear imagingnow permits the mapping of flow, the poor resolution of thesetechniques precludes the imaging of the extremely thin retina.The unique optical access of the retina, however, has encouragedthe development of photographic and, eventually, laser-basedtechniques for flowmeasurement. Techniques such as fluoresceinangiography and laser Doppler flowmetry are now widely used,and provide important information on vascular parameters.

The greatest success has been achieved with measurements ofthe inner retinal circulation [which feeds the inner (or anterior)retinal layers], as these vessels are the least obscured.Measurements of the choroidal blood flow [which feeds theouter (posterior) retinal layers], however, are less advancedbecause the retinal structures, overlying pigments and retinalvessels partially obscure it. Measures of perfusion are currentlyderived primarily from optical techniques which relate dye transitor velocity distributions to blood flow (4,5). The quantification offlow using these techniques requires a number of assumptions,whose validity has been debated. Because these methods requirean optical window and employ microscopic measures, theytypically scan only a small section of the retina and cannotcharacterize choroidal flow, except in the region of the fovealavascular zone.Although originally viewed as an anatomic imaging technique,

the flexibility of MRI has made possible the imaging of manydifferent forms of contrast, including a number of vascular

(wileyonlinelibrary.com) DOI:10.1002/nbm.1564

Research Article

* Correspondence to: N. Maleki, P.A.I.N. Group, Brain Imaging Center, McLeanHospital, 115 Mill Street, Belmont, MA 02478, USA.E-mail: [email protected]

a N. Maleki

N. Maleki, Department of Psychiatry, McLean Hospital and Harvard Medical

School, Boston, MA USA

b W. Dai, D. C. Alsop

W. Dai, D. C. Alsop, Department of Radiology, Beth Israel Deaconess Medical

Center and Harvard Medical School, Boston, MA, USA

Abbreviations used used: ASL, arterial spin labeling; CASL, continuous

arterial spin labeling; PCASL, pulsed-continuous arterial spin labeling; POBF,

pulsatile ocular blood flow; ROI, region of interest; SSFSE, single-shot fast spin

echo.

NMR Biomed. (2010) 24: 104–111 Copyright � 2010 John Wiley & Sons, Ltd.

104

parameters. Some of the earliest MRI approaches to flowmeasurement employed tracers containing rare nuclei, such as19F or 17O, which could be detected on the basis of their signalfrequency (6–8). The low sensitivity of these approaches hasimpeded their advance, however. More successful approaches toblood flow imaging with MRI are those that employ the signalfrom protons in water, which are present in a very highconcentration. One such approach is based on the injection of acommonly used, Food and Drug Administration-approved,magnetic contrast agent, gadolinium-diethylenetriamine pen-taacetic acid (Gd-DTPA) (9). In tissues with a blood–brain barrier,the agent remains in the vasculature, but can also affect the tissuesignal by perturbing the magnetic field. The quantification offlow with this technique is analogous to fluoroscein angiography,except that, typically, the microvascular concentration ismeasured and a deconvolved clearance curve is generated onthe basis of the image intensity in a feeding artery (10). Althoughthis technique has been very successful in brain studies, itsapplicability to retinal blood flow measurement is questionablebecause the retina is at the edge of a large signal intensitygradient between fat and vitreous. Very small movements canoverwhelm the vascular effects under study.An alternative technique for MRI blood flow measurement is

the arterial spin labeling (ASL) method (11). ASL employs thespatial selectivity of MRI to saturate or invert the spins of thehydrogen nuclei of blood before they enter the tissue of interest.If sufficient time is allowed for the labeled blood to flow into thetissue, a small intensity change in an MR image of the tissue willbe observed. Because the water of blood readily diffuses acrossthe blood–brain barrier, the label acts as a diffusible tracer, atype of tracer with excellent properties for quantifying flow. Awell-developed theory for quantifying flow with ASL has beendescribed (8–11), and blood flow values in the brain have beenvalidated with microspheres in animals (12) and with positronemission tomography in humans (13). Although ASL perfusionmeasurements can be quite sensitive to motion, the use ofbackground suppression (14) can greatly reduce the contrastbetween fat and vitreous, and thus the corresponding motion-induced errors. During the development for neurologic appli-cations of background-suppressed ASL (11,15), Alsop and Detre(16) had previously observed that flow to the retina was readilydetectable in their blood flow images. Functional perfusionimaging of the human retina using flow-sensitive alternatinginversion recovery ASL has also been reported (17).The goal of this study was to develop a quantitative tomo-

graphic technique for the measurement of total blood flow to theretina (inner retinal plus choroidal blood flow) using noninvasiveASL MRI in humans. An optimized technique was used tocharacterize the blood flow signal, and total blood flow to thechoroid and retina was quantified using multiple delay times, 3-Timaging and array coil reception.

EXPERIMENTAL DETAILSImaging

Studies were performed on a GE 3.0 Tesla EXCITE MR system (GEHealthcare Technologies, Waukeshau, WI, USA) with a recei-ve-only, eight-channel array head coil and a body transmit coil.Five healthy subjects with no history of retinal abnormalities wererecruited following a protocol approved by the local institutionalreview board, and all subjects gave written informed consentafter explanation of the nature and possible consequences of thestudy, according to the tenets of the Declaration of Helsinki.An approximately axial image slice passing through the

optic nerve heads was prescribed graphically on the basis of thelocalizer image. Images were acquired using a two-dimensionalhalf-Fourier single-shot fast spin echo (SSFSE) sequence. Thisimaging sequence is much less affected by the nonuniformmagnetic fields in the orbits caused by air in the nearby sinusesthan is the echoplanar imaging sequence most often used forbrain blood flow imaging. Imaging parameters were as follows:field of view, 24 cm; matrix, 96� 96; bandwidth, 20.83 kHz; slicethickness, 10mm. The linear ordered partial k-space acquisitionused six extra echoes for a total echo train length of 54. The echospacing was 5.2ms. As T2 decay during the echo train can causeblurring, the resolution in the right/left direction is probably lessthan the nominal resolution of 2.5mm. A long TR of 7000ms wasselected to minimize any effects of the inversion pulses on bloodmagnetization for the next repetition, and a minimum effectiveTE of 36.5ms was chosen to minimize the T2 contribution to thesignal intensity.A recently developed strategy for continuous labeling with a

repeated series of short pulses (pulsed-continuous arterial spinlabeling, PCASL) was employed (18). Labeling was performed inan axial plane, 5 cm beneath the level of the optic nerve, for aduration between 500 and 2000ms. This location labels bloodin the carotid and other arteries below the Circle of Willis.Background suppression was numerically optimized for eachpost-labeling delay (19). As the background suppression qualitysuffered if the labeling duration was much longer than thepost-labeling delay, we chose to optimize for a labeling durationequal to the post-labeling delay. A schematic drawing of thetiming of labeling and background suppression pulses is shownin Fig. 1, and the exact timing used for different post-labelingdelays is given in Table 1. Image pairs (label and control) wereacquired at post-labeling delays of 0.5, 0.75, 1, 1.25, 1.5 and 2.5 s.The pairs were repeated 20 times to improve the signal-to-noiseratio by averaging. The scan time per post-labeling delaywas 4.6min, and the total scan time for each subject wasapproximately 28min.To avoid systematic errors as a result of subject fatigue towards

the end of the experiment, the order of data acquisition forvarious delays was reversed for every other subject. At the end of

Figure 1. The pulse sequence timing diagram of the background-suppressed pulsed-continuous arterial spin labeling (PCASL) sequence used for retinal

perfusion imaging. t is the labeling duration and w is the post-labeling delay.

NMR Biomed. (2010) 24: 104–111 Copyright � 2010 John Wiley & Sons, Ltd. View this article online at wileyonlinelibrary.com

BLOOD FLOW QUANTIFICATION OF THE HUMAN RETINA WITH MRI

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the study, two images were acquired with all the labeling andbackground suppression pulses turned off. The average of thesetwo images was used to normalize the signal for blood flowquantification and to provide greater anatomic information.To minimize systematic errors resulting from eye movements,

the volunteers were asked to fixate on a fixation target and blinkonly during the silent periods of the sequence (20). (The MRIscanner makes audible sounds during the labeling and imagingperiods.) The synchronization of blinking with the noise andsilence pattern of the imager was practiced with the subjectsprior to data acquisition.All imaging data were saved as raw echo intensities and were

transferred to a Linux workstation for reconstruction and analysis.Images for each coil of the eight-channel phased array coil werereconstructed offline with custom tools developed in the IDLprogramming environment. The data for each coil were averagedfor all the repetitions, and the resulting average was phasecorrected. Close to optimal combination of the complex coilimage data was achieved by the sum of squares of individual coilimages weighted by the coil sensitivity ratios derived fromsmoothing the non-background-suppressed image by a 9� 9Gaussian filter (21). This method decreased the bias as a result ofthe rectification of the negative noise contributions in thereconstructed blood flow images.

Blood flow quantification and analysis

Blood flow-related signal intensity was averaged across regions ofinterest (ROIs) drawn manually around the blood flow signalintensity at the retinal level and in a region of the cerebellumcontaining mostly gray matter (Fig. 2). A rectangular ROI between1 and 1.5 cm in length along the retina (based on the perceivedextent of the perfusion signal in each subject), 5mm in width and10mm deep (imaging slice thickness) was manually defined,centered on the region of brightest blood flow signal intensity inthe 1.5-s post-labeling delay images. ROIs were defined similarlyfor both eyes. After definition of the retinal ROIs, they wereoverlaid on the reference anatomical image to confirm thelocation at the posterior edge of the eye. They were also overlaidon short post-labeling delay images to verify that the apparentlarge arterial signal in these images was outside of the regions.These arterial signals, apparent by their bright, linear signal andrapid decay with post-labeling delay, tended to be posterior tothe ROIs. At our resolution, we cannot exclude smaller arterialvessels, such as the retinal artery, from the ROI. The cerebellar ROIwas drawn at the posterior boundary of the right cerebellum. ThisROI is probably dominated by gray matter, but somewhite mattermay be included in the region.

The signals in each ROI as a function of post-labeling delaywere fitted to models for signal as a function of blood flow,post-labeling delay and arterial transit time. A single-compart-ment model (22) was used to model the blood flow to the retina,in which the observed signal is considered to come from awell-mixed tissue compartment with intra- and extravascularwater in perfect communication. Single-compartment modelsprovide reasonable fits and quantification values for gray matterin the brain, although more sophisticated models including avascular compartment are often considered (23). The assumptionof a single, well-mixed compartment for the choroidmay bemoresuspect, because of the very high flow rates and unique structureof the choroid. As key fundamental parameters for more complexmodeling of the retinal and choroidal blood flow, such as T1 of theretina and choroids, choroidal permeability to water and meantransit time for outflow in the choroid, are unknown, we chose touse the simple single-compartment model and to examine theresults for signs of error. In particular, poor mixing and rapidoutflow of venous magnetization would tend to greatly shortenthe apparent T1 value of tissue in the fit. For the single-compartment model, the continuous arterial spin labeling (CASL)difference signal (label – control), DM, can be expressed by thefollowing equation:

DM ¼ � 2M0fa

lR1e�dR1a emin d�w;0ð ÞR1�emin d�w�t;0ð ÞR1

h i[1]

Table 1. Optimized timing of the pulses for background suppression for post-labeling delays ranging from 500 to 2500 ms

Delay(ms)

Labeling(ms)

Nonselective post-labeling inversionpulses (ms before imaging)

Selective prelabeling inversionpulses (ms before imaging)

Saturation pulse(ms before imaging)

500 500 94.22 295.01 346.63 479.96 1020.02 1833.51 2685.63 3080.44750 750 20 91.5 287.77 729.99 1520 2580.79 3216.66 3243.091000 1000 20 125.19 405.8 980 2020 3615.09 5288.7 5979.991250 1250 20.01 151.49 511.45 1229.59 2520 4463.43 5815.02 5835.271500 1500 20.01 170.62 600.83 1480 3020 4969.21 5959.88 59802500 2000 107.47 459.47 1169.87 2480 4520 5939.98 5959.98 5980

Figure 2. Anatomic axial image of a slice passing through the optic

nerve heads corresponding to the blood flow images in Fig. 4. Also shownare the regions of interest in the retina of both eyes and gray matter of the

cerebellum.

View this article online at wileyonlinelibrary.com Copyright � 2010 John Wiley & Sons, Ltd. NMR Biomed. (2010) 24: 104–111

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where M0 is the equilibrium brain tissue magnetization, f is theretinal blood flow, l is the blood–tissue water partition coeffi-cient, R1a is the longitudinal relaxation rate of blood, a is theinversion efficiency, R1 is the longitudinal relaxation rate of retinaltissue in the absence of blood flow, d is the transit time from thelabeling region to the tissue compartment (exchange time), t isthe labeling duration and w is a post-labeling delay introducedbetween the end of the labeling pulse and image acquisition inorder tominimize the transit time artifacts (23); themin() functionreturns the smaller of its two arguments.We assumed a labeling efficiency of 0.85; however, as inversion

pulses used for background suppression also attenuate the ASLsignal, an additional loss of efficiency of 75% was considered inthe flow quantification (24). l is the brain–blood water partitioncoefficient, which is a measure of the ratio of water in the tissueand the blood. We assumed an average brain value of 0.9 g/mL(25). Although l for the retina is uncertain, most neural andvascular tissues have l between 0.8 and 1 (25), and so the errorshould not be extreme. We also used R1a¼ 0.67 s�1 (26). Thesignal intensity was normalized to the intensity of the vitreousin an unsuppressed reference image. The water density of thevitreous is close to 100%, and so it serves as a reference for thesensitivity to water. By fitting the measured DM data to thismodel, f, d and R1 were estimated. Blood flow to the cerebellargray matter ROI was also calculated for comparison.Fitting was performed using a Levenberg–Marquardt algor-

ithm implemented in the MATLAB (MathWorks Inc., Natick, MA,USA) programming language. Values of combined retinal andchoroidal blood flow derived from the fits do not compensate forthe small thickness of the retina relative to the ROI. The retina isapproximately 250mm thick in the center, and the thicknessdecreases to approximately 120mm at the periphery (27). Thesedimensions were well below our imaging voxel size (10� 2.5�2.5mm3). Correction for this partial volume effect would require a

measure of the retinal volume within the ROI, which would bevery difficult to obtain with MRI. However, retinal blood flow isoften estimated in units of mL/mm2/min, and conversion to theseunits is readily achieved with our data. We used the relationship:

fh iROI l t sð Þr ¼ 1000 afh iROI l sð Þwhere the angled brackets indicate averaging over the ROI, f isthe flow in mL/g/min, r is the density of the retina, here assumedto be 1 g/mL as for brain (25), af is the area flow in mL/mm2/min,and l, t and s are the right–left length, anterior–posteriorthickness and axial slice thickness of the ROI, respectively. Thisequation neglects the slight curvature of the retina over theextent of the ROI. Flow to the cerebellum in the brain wasquantified in mL/100 g/min because the perfused cerebellum isfully resolved.

RESULTS

All subjects successfully completed the scanning session. A signalat the posterior of the vitreous with a dependence on the post-labeling delay, consistent with blood flow, was successfullyvisualized in all subjects. An example image series for one subjectis shown in Fig. 3. The combination of spatial location anddependence on post-labeling delay provide strong support forthe blood flow-related nature of the signal.Specifically, ASL images at longer delays (1250, 1500 and

2500ms) are clearly consistent with blood flow to the retina. Alsoapparent in Fig. 3 is the observation that the blood flow signal isbrightest near the center, in a region at the most posterior extentof the vitreous. The brightness of the perfusion and its locationare consistent with this area being the fovea. Occasionally

Figure 3. Single-slice perfusion images through the orbits and inferior brain obtainedwith the background-suppressed pseudo-continuous arterial spin

labeling (ASL) technique. Blood flow-sensitive images 1–6 correspond to post-labeling delays of 500, 750, 1000, 1250, 1500 and 2500ms, respectively. Theperfusion signal consistent with blood flow to the retina dominates the orbital signal (box) in the later delay images. The inferior temporal poles (middle

of image) and the cerebellum (bottom of image) are also clearly seen.



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apparent in the ASL subtraction images at short post-labelingdelay were linear structures connecting the brain and the retina.These were probably parts of the ophthalmic artery still cont-aining some labeled blood. The ASL signal in the left and right eyeof another subject is plotted as a function of the post-labelingdelay in Fig. 4. The rate of decay of the tracer, as shown in Fig. 4,was comparable with that in the cerebellum.A key to the successful imaging of blood flow to the retina

in vivowas the use of background suppression. All of the imagingwas performed with seven inversion pulses, whose timing wasoptimized to produce a very small signal from static tissue.Inflowing labeled blood was minimally attenuated by themultiple inversion scheme (24). The measured residual back-ground signal was consistent with a high level of backgroundsuppression.The level of background suppression is a function of the

post-labeling delay, labeling duration and the tissue. Figure 5summarizes the average percentage of static tissue signal leftafter suppression for vitreous and periorbital fat. In no situationwas the suppressed static tissue signal greater than 2% of theunsuppressed signal.

Fitting of the ASL signal change in the retina as a function ofthe time delay after labeling provided the arrival time of thenoninvasively labeled blood and the T1 decay rate. Theseparameters permitted the calculation of the absolute blood flowper unit area (Table 2). In studies of the brain, T1 is oftenmeasuredseparately but, as we lacked sufficient spatial resolution to resolvethe retina, the relaxation rate (1/T1) needed to be inferredfrom the decay rate, and was found to be 0.75� 0.14 s�1. Thequantification results are summarized in Table 2. The flow to theretina was found to be 1.75� 0.54mL/mm2/min (total bloodflow of 261� 87mL/min). In addition, the flow was found to be87.8� 31mL/100 g/min in the cerebellum, consistent with manyearlier studies (14,23,28). The arterial transit delays from alabeling plane 5 cm below the eye were 1137� 288 and 1098�217ms for retina and cerebellum, respectively.

DISCUSSION

The feasibility of measuring total blood flow to the retina usingASL MRI has been shown in this study. Using a microsphere-derived measurement of flow in monkeys (29), near the fovea,flow values of 6.49mL/min/mm2 for choroidal flow and 0.28mL/min/mm2 for inner retinal flow have been reported. Far fromthe fovea, the inner retinal flow drops off to 0.04mL/min/mm2.In another study using fluorescent microspheres (30), a totalchoroidal blood flow of 917� 281mL/min was reported in threemonkeys (two Cynomolgus and one Rhesus), with a peak flow of10mL/min/mm2 at the fovea, rapidly dropping to 1–2mL/min/mm2 at a radius of approximately 5mm. Both studies report amarked concentration of microspheres in the central macula anda much reduced density in the periphery, consistent with thespatial distribution in our study. Interestingly, such centralconcentration is not observed in rabbits (30), who have an areacentralis with a much lower cone density than that of the humanfovea. Employing pulsatile ocular blood flow (POBF) tonometrytechniques, several authors have reported mean POBF valuesbetween 444 and 803mL/min in normal human subjects (31–33).As the flow per unit area number is unique to imaging

measures of the retina, it is desirable to relate this measure toother measures of retinal flow. We observed a flow of 1.75�0.54mL/min/mm2 with this MR technique, averaged across a10mm� 14.7mm region of the retina centered on the fovea.

Figure 4. Average arterial spin labeling (ASL) signal in regions of interest in the left and right eye of a volunteer vs the post-labeling delay time,

corresponding to the retinal regions of interest and the cerebellar region of interest shown in Fig. 2.

Figure 5. Percentage of the residual static background signal remainingfollowing background suppression. Bars show means. Error bars show

95% confidence intervals of the means.


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Assuming the entirety of the flow to the retina was contained inour ROI, the total flow would be 261� 87mL/min. This low limiton total flow is reasonably consistent with other measures of totalocular blood flow. As ASL is widely used to image resolved tissues,such as the brain, it is also instructive to convert to the moretraditional flow per unit mass units used for such measures. Theaverage weight of the human retina (obtained from autopsy) isapproximately 326mg (34). Dividing the total flow value by thismass gives approximately 80.1mL/100 g/min. The flow of theretina is highly peaked near the fovea, however. Measurements inprimates suggest a flow approximately 14 times higher in the fewmillimeters near the fovea (35).As we did not resolve the thickness of the retina, care must be

taken in interpreting differences over time or between subjectswith this measure. First, the physiology and pathology of theretinal circulation and choroidal circulation may differ, and wecannot resolve these differences with our current resolution.In addition, we cannot distinguish changes in flow per gram oftissue from changes in the thickness of the retina itself. Our use ofarea flow is similar to the use of cerebral perfusion in dementiawithout correction for gray matter atrophy. Resolving the thick-ness of the retina, at least with anatomic imaging, as has beenperformed in animals (36), would certainly help to address theseconcerns, but would probably require additional work on motionsensitivity and sequences.Certainly, improvements to our method could yield greater

information on flow and flow distribution. The ability to fullyresolve and measure the flow variation across the fovea and tomeasure the optic nerve head blood flow would require a spatialresolution of approximately 1–2mm. This would be challenging,but potentially achievable. An even greater challenge would beto resolve the retinal and choroidal flow contributions. This wouldrequire a spatial resolution of approximately 10 times better.Although such studies have been reported in small animals athigh field (20), achieving such resolution in the awake humanmay be difficult.Our inability to separate retinal and choroidal flow, and the

much higher normal level of choroidal flow, raise important issuesabout the interpretation and application of this technique. Inparticular, oxygen extraction is very low in the choroidalcirculation (35), suggesting that a reduction in choroidal flow

need not impair oxygen delivery and metabolic activity of theretina. The degree to which choroidal flow must be reduced inorder to affect retinal health and function, and how frequentlythis occurs in clinical syndromes, will require further study.Despite the high flow and limited distribution volume within

the retina, no evidence for rapid outflow was observed in thedynamics of the ASL signal. Our single-compartment modelprovides a good fit to the experimental data (Fig. 4). In addition,the fitted retina T1 relaxation rate of 0.72 s�1 is similar to that ofbrain (Table 2). High outflow would primarily appear as ashortening of T1, but substantial shortening present in thealready long fitted T1 value of the retina is unlikely. However, asthe T1 value of the retina is unknown, distinguishing T1 diffe-rences from outflow is difficult, as the signal changes resultingfrom changes in either T1 or outflow are quite similar for a widerange of post-labeling delays.The results suggest thatmixing within the retinal compartment

and the exchange of water across the basement membrane aresufficient to retain ASL label in the retina. As the dynamic datashowed little evidence for delayed arrival, and the outflow wassmall, continuous ASL with delays of approximately 1250msshould enable the quantification of the blood flow.These results provide convincing evidence for the feasibility of

measurements of blood flow to the retina using MRI. A number oftechnical and validation steps clearly remain. The optimizationof imaging with special coils for imaging the eye, reduction ofslice thickness and improved motion reduction strategies,perhaps employing MR-compatible eye-tracking systems, areall possible. Validation in animal models, or by modulatingblood flow with challenges, is also needed. Recently, retinotopicactivation of the cat retina (37) and robust retinal blood flowchanges in the rat retina evoked by physiological stimuli (20) havebeen reported using the ASL technique. Nevertheless, imagequality is sufficient to consider the potential uses of the methodin research and clinical practice.The transit times measured in our study were from the labeling

location in the carotid arteries to the retina. Labeling of theophthalmic arteries with a more coronal labeling plane should befeasible, although restrictions on the pulse sequence employeddid not permit its use in our study. In normal subjects, the delayfrom the carotids to the ophthalmic artery appears to be short,

Table 2. Quantitative hemodynamic estimates for the relaxation rate (R1), flow ( f ) and transit delay (d) in the left (L) and right (R)retinal regions of interest (ROIs) and the cerebellar ROI

Retina Cerebellum

R1 (s�1) f (mL/mm2/min) d (s) R1 (s

�1) f (mL/100 g/min) d (ms)

1 L 0.81 1.95 1.403 0.75 72 1.203R 0.88 2.23 1.263

2 L 0.84 2.15 0.879 0.80 102 0.882R 0.75 1.79 0.892

3 L 0.64 0.8 1.399 0.62 56 1.378R 0.67 1.04 1.277

4 L 0.6 1.43 1.46 0.71 135 1.151R 0.65 1.55 1.311

5 L 0.73 2.39 0.781 0.70 72 0.875R 0.7 1.91 0.705

Average� SD 0.75� 0.14 1.75� 0.54 1.137� 288 0.72� 0.06 87.8� 31 1.098� 0.217



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but it may be more problematic in patients. Coronal labelingshould be considered to minimize this delay.Compared with most optical techniques, MRI is an expensive

and cumbersome method. The use of MRI to measure blood flowwill be limited to those applications in which the capabilities areunique or other forms of MRI are already indicated. Techniquesfor measuring retinal oxygenation (38) and vascular permeability(39) with MRI may complement the blood flow measure. BecauseASL MRI uses a diffusible tracer, water, to quantify flow, thequantitative values are arguably less suspect than methodsbased on vascular measures. At a minimum, the quantification ofblood flowwith ASL is based on very different measurements andassumptions than optical methods, and so comparison of ASLMRI with optical methods may provide an insight into the validityof the assumptions employed (40). The absence of absolutevalues of reference measures of total retinal blood flow inhumans emphasizes the potential value of the MRI technique.Finally, ASL MRI may provide improved measurement of choroidalblood flow across the entire retina because the retinal vasculaturedoes not obscure or confuse the MRI measurement.In conclusion, the imaging and quantification of blood flow

to the retina with contrast-free MRI is feasible in humans. Thistechnique may provide a unique window for the study of retinalblood flow control and pathology.

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Blood flow quantification of the human retina with MRI