Intravascular effect in velocity-selective arterial spin labeling: The choice of inflow time and cutoff velocity

www.elsevier.com/locate/ynimg NeuroImage 32 (2006) 122 – 128

Intravascular effect in velocity-selective arterial spin labeling: The choice of inflow time and cutoff velocity Wen-Chau Wua,* and Eric C. Wonga,b,* a

Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA

b

Received 12 September 2005; revised 17 February 2006; accepted 7 March 2006 Available online 19 May 2006

Velocity-selective arterial spin labeling (VS-ASL) tags spins on a basis of flow velocity, instead of spatial distribution that has been commonly adopted in conventional ASL techniques. VS-ASL can potentially generate tags that are very close to the imaging plane and whereby avoid the error source of transit delay (yt) variation independent of inflow time (TI). In practice, however, TI of VS-ASL should still be chosen with caution with respect to intravascular signal and cutoff velocity (V c). The presented study takes advantage of multiple TI and V c to systematically investigate the intravascular effect. Results demonstrate the presence of significant signal from large vessels in VS-ASL images for V c down to 4 cm/s. For perfusion measurement in human brain, low V c (<4 cm/s) is recommended. With V c = 2 cm/s, quantitative cerebral blood flow is 72.8 ml/100 ml/min, which is in agreement with the reported range using conventional ASL methods. In field strength of 3 T, numerical simulation shows that optimal signalto-noise ratio efficiency can be achieved with TR/TI = 2092 ms/1664 ms for single slice and 4493 ms/1404 ms for slab imaging. D 2006 Elsevier Inc. All rights reserved. Keywords: Arterial spin labeling; Magnetic resonance imaging; Velocityselective

Introduction During the past decade, arterial spin labeling (ASL) has been developed into a useful technique for measuring local tissue perfusion using magnetic resonance imaging (MRI) (Detre et al., 1992; Edelman et al., 1994; Kim, 1995; Kwong et al., 1995; Alsop and Detre, 1996; Ye et al., 1996; Wong et al., 1997), especially in respect of noninvasiveness and high temporal resolution. ASL

* Corresponding authors. Center for Functional MRI, University of California, San Diego, 9500 Gilman Drive, #0677, La Jolla, CA 92093, USA. Fax: +1 858 822 0605. E-mail addresses: [email protected] (W.-C. Wu), [email protected] (E.C. Wong). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter D 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2006.03.001

techniques magnetically invert or saturate the longitudinal magnetization of spins in arterial blood and use it as an endogenous tracer. The tag image is acquired after an inflow time (TI) that allows an enough amount of tagged blood to reach the slice of interest. Afterward, a control image is generated by repeating the experiment without tagging the blood. The two images are subtracted to produce the ASL difference image whose intensity is therefore proportional to the local perfusion. Conventionally, the tagging bands are spatially determined, which inevitably requires a transit time (yt) for tags to travel from the tagging region to the imaging plane. However, the yt variation arising from either vascular topography or disease-induced alteration has been reported to be the main error source in perfusion quantification using ASL in human brain (Alsop and Detre, 1996; Wong et al., 1997; Chalela et al., 2000). In clinical applications such as ischemic stroke, collateral circulation can increase yt to a value that is large enough in comparison with longitudinal relaxation time (T 1) of arterial blood and hence deteriorate the signal-to-noise ratio (SNR) (Wong et al., 1998) and make imaging impracticable. On the other hand, velocity-selective arterial spin labeling (VSASL) modulates the longitudinal magnetization of blood on a basis of its flow velocity (Wong et al., 2002; Duhamel et al., 2003) rather than spatial distribution. By incorporating a VS pulse train, only blood flowing above a cutoff velocity (V c) is tagged. Theoretically, VS-ASL is capable of generating tags very close to the region of interest by choosing small V c and thereby avoids the confounding error coming from yt (i.e. yt = 0). In addition, TI can therefore be fairly reduced while still providing sufficient SNR for ASL signal. In practice, however, TI of VS-ASL should be chosen with caution in consideration of intravascular signal and V c. When a large V c within the range of arteriolar flow velocity is used for imaging, the tagging region covers more upstream blood and a long TI is necessary for tags to reach capillary bed at the expense of SNR decrease. An improperly short TI, on the other hand, can bias perfusion by large vessel signal or, even worse, result in erroneous flow measurement. The phenomenon was briefly mentioned by Duhamel et al. (2003) but was never quantified. Recently, Wong et al. (in press) provided an overview

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Fig. 1. The modified VS pulse train. Tag (upper) and control (lower) acquisitions are interleaved.

of miscellaneous issues in VS-ASL, pointing out some important topics worthy of further investigation, such as directionality and intravascular effect. In this study, we systematically evaluate the interaction between V c and TI. The pseudo yt shortening caused by through plane vessels is demonstrated. The optimal TR/TI is then provided for low V c.

Materials and methods Velocity-selective ASL Guilfoyle et al. (1991) first proposed that velocity selectivity can be accomplished with a spin-echo sequence consisting of 90- – 180- – 90- hard RF pulses in combination with flowsensitive gradients. In the presence of laminar flow, the longitudinal magnetization (M z) becomes a sinc function of velocity (Wong et al., 2002; Norris and Schwarzbauer, 1999), which VS-ASL utilizes as an approximation of the ideal velocity selectivity. The cutoff velocity can be expressed as: Vc ¼

p cyDG

ð1Þ

where c is the gyromagnetic ratio, G is the strength of flowsensitive gradients, y is the gradient duration and D is the time between gradients.

In this study, the 180- pulse was replaced by a pair of identical adiabatic 180- pulses (Conolly et al., 1991), together with the four gradient pulse scheme described by Reese et al. (2003) to further reduce the subtraction errors (Fig. 1) (Wong et al., in press). The parameters used in our implementation were as follows: D = 17.8 ms, y = 1.0 ms, gradient ramp length = 1.0 ms. The total duration of VS pulse train was 21.0 ms. The sech adiabatic pulses (b = 800, l = 6) were transformed into the shape of cos0.2(t). After a delay of TI allowing for the delivery of tags, single shot spin echo spiral images were acquired with flow weighting gradients that were adjusted to the same V c as the tag pulse. In other words, the VS-ASL signal only included blood that was tagged at velocities above V c, and then decelerated to a velocity below V c prior to imaging. In principle, the VS-ASL signal (DM, difference between control and tag images) was proportional to CBFITIIexp(TI/T 1b ), where CBF indicated cerebral blood flow and T 1b was the longitudinal relaxation time of blood. MRI experiments Imaging was performed on six healthy volunteers (four males, two females, age = 24 – 36 years) using a 3T GE EXCITE system. The protocol was approved by the Institutional Review Board at the University of California, San Diego. Experiments consisted of two parts. First, multiple TI values were used to measure inflow curves. Considering the directionality,

Fig. 2. Implementation of background suppression in VS-ASL pulse sequence. Two inversion pulses are used in this study.

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the flow-sensitive gradients were applied along three orthogonal directions separately. Three schemes could be used for this purpose: (a) sequential encoding, (b) direction looping and (c) segmented encoding. While scheme (a) was substantially affected by T2-related attenuation, scheme (b) was more subject to system instability and the switch of VS gradients between acquisitions brought about eddy current artifacts. As a result, segmented encoding was chosen in our experiment. Imaging parameters included: FOV = 24 cm, slice thickness = 7 mm (3 axial slices), in-plane matrix size = 64  64, TI = {600, 900, 1200, 1500, 1800} ms, V c = {2, 4, 8} cm/s, TR = 2500 ms, repetition = 120 (1 – 40, 41 – 80, 81 – 120 for x, y and z encoding, respectively). The second part of the experiment was to quantify perfusion. To improve the signal stability, background suppression (Garcia et al., 2004; St Lawrence et al., 2005; Ye et al., 2000) was applied by inserting two adiabatic nonselective inversion pulses between tagging pulses and image acquisition (Fig. 2). Tissues with T 1 values from 700 ms to 1600 ms were suppressed prior to imaging. The reason why background suppression was not used for measuring inflow curves was that the timing to apply suppression pulses had to be recalculated for each TI, which made the degree of suppression vary from one scan to another. Imaging parameters were as follows: V c = 2 cm/s, TR/TE/TI = 3000/15/1600 ms, 3 axial slices (7 mm in thickness), FOV = 22 cm, in-plane matrix size = 64  64, repetition = 90 (1 – 30, 31 – 60, 61 – 90 for x, y

and z encoding, respectively). The slices were prescribed to cover a chunk of ventricle CSF for purposes of calibration of blood longitudinal magnetization at equilibrium, and examination of CSF suppression. CSF suppression and flow quantification In the brain, CSF generally produces the largest subtraction errors from both diffusion and motion (Wong et al., 2002; Duhamel et al., 2003). While the diffusion sensitivity of the tag pulse train is characterized by the b value of the sequence, the sensitivity of coherent motion is characterized by V c. In this study, the longer separation of diffusion gradients in VS train incidentally makes b value smaller. When V c = 2 cm/s, the diffusion-related signal attenuation is 0.028% and 0.018% for CSF and brain tissue, respectively. The calculation is based on (1  exp((TRTI)/T 1)) I(1  exp(bD)) in which TR/TI = 3000/1600 ms, T1 = 3500 ms, D = 0.0025 mm2/s for CSF and T 1 = 1300 ms, D = 0.0008 mm2/s for non-CSF tissue (Clare and Jezzard, 2001; Le Bihan, 1995). The necessity of CSF suppression can be eliminated for Vc down to 2 cm/s with the tradeoff of greater T 2-related attenuation of the tagged magnetization. CBF was voxelwise quantified following the procedure proposed by Wong et al. (1998) and CSF was chosen as the reference. The proton density ratio of blood to that of CSF was measured from three

Fig. 3. VS-ASL images with different combinations of cutoff velocity (V c) and inflow time (TI). From left to right, TI = {600, 1200, 1800} ms. From top to bottom, V c = {2, 4, 8} cm/s.

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subjects (0.72 T 0.03) and 0.72 was applied to all subjects. The transverse relaxation times of blood and CSF were assumed 130 and 1000 ms, respectively. The longitudinal relaxation time of blood was 1664 ms (Lu et al., 2004). Data processing To extract pixels of interest, two masks were generated by thresholding the VS-ASL images obtained by TI = 1800 ms, V c = 2 cm/s and TI = 600 ms, V c = 8 cm/s (the signal from saggital sinus was excluded). While the former related to gray matter, the latter accounted for more arterioles in addition to gray matter, assuming that 1800 ms delay was enough for tags to reach capillary bed whereas most tags remained in arterioles within 600 ms. The rationale of this method is twofold. First, flow velocity is 1 – 2 cm/s in perforators (diameter = 30 – 50 Am) (Kobari et al., 1984). Second, in conventional ASL, the reasonable TI for tagged blood to reach capillary bed is 1100 – 1400 ms whereas noticeable intravascular signal has been reported as TI < 1000 ms (Edelman et al., 1994; Wong et al., 1997).

Results A representative set of VS-ASL images acquired with different combinations of TI and V c are shown in Fig. 3. Note the markedly different contrast between V c = 2 cm/s and V c = 8 cm/s. High V c along with short TI (bottom left) shows more large vessel trees (scattered bright spots) whereas low V c and long TI (top right) generate a perfusion map that better depicts gray matter. Fig. 4 shows the VS-ASL signal, averaged from all subjects, as a function of TI by applying the gray matter mask mentioned above to perfusion maps

Fig. 5. Intravascular effect on VS-ASL signal. The threshold of the mask including gray matter as well as arterioles is adjusted to generate different weightings of large vessel, marked by circle, triangle and square in ascending order. For V c = 4 and 8 cm/s, VS-ASL signal peaks earlier with the elevated weighting from large vessels. By contrast, no significant intravascular effect is found with V c = 2 cm/s.

of different V c. One notices that the signal with V c = 2 cm/s reaches its maximum as TI is about the T 1 of arterial blood which is 1664 ms at 3 T (Lu et al., 2004). On the other hand, the VS-ASL signals with V c = 4 and 8 cm/s peak at shorter TI values. In Fig. 5, VS-ASL signals are obtained by adjusting the weighting of large vessels. The circle represents data from all voxels within the mask containing both arterioles and gray matter. These voxels were further sorted based on signal intensity, where the triangle represents the 50% brightest and the square, the 20% brightest. For V c = 4 and 8 cm/s, the higher proportion of large-vessel voxels is included, the earlier VS-ASL signal peaks. By contrast, no significant difference is found with V c = 2 cm/s when VS-ASL signal is calculated over the subsets of voxels. Fig. 6 demonstrates VS-ASL images as well as their reference images. No observable CSF contamination was found by visual inspection. The diffusion-related signal attenuation of CSF is 0.028% whereas the gray matter VS-ASL signal is (0.64 T 0.02)% of the equilibrium gray matter intensity. The calculated mean CBF of gray matter is 72.8 T 4.0 ml/100 ml/min, in agreement with the range reported by conventional ASL methods (Wong et al., 1998; Yongbi et al., 2002; Alsop and Detre, 1996). Fig. 4. VS-ASL signal vs. inflow time (TI). A gray matter mask was used to extract pixels of interest. When V c = 2 cm/s, the signal peaked at a TI around the T1 of arterial blood as predicted. The maximum of signal was found 300 ms earlier with V c = 8 cm/s whereas V c = 4 cm/s reaches its peak value somewhere between 1200 ms and 1500 ms. Both V c = 4 cm/s and 8 cm/s show lower VS-ASL signals than V c = 2 cm/s. The error bars indicate the standard deviation of six subjects.

Discussion Conventional ASL techniques spatially position the tagging band to upstream arteries and acquire images at the territories fed by them. One technical consideration is the imperfect slice

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plane vessels flush tags quickly without substantial transit delay and exchanging with tissue spins. V c = 4 cm/s exhibits a similar but less prominent trend whereas no measurable difference is observed by adjusting the weighting of large vessels as V c = 2 cm/s. Duhamel et al. (2003) and Wong et al. (in press) both briefly mentioned the intravascular signal but never quantitatively evaluated the interaction between V c and TI. Our experiment, on the other hand, systematically inspected the flow velocity range in arterial branches and arterioles (V c = 2, 4, 8 cm/s) and demonstrated the existence of intravascular effect at least down to V c = 4 cm/s. CSF contamination and perfusion quantification

Fig. 6. VS-ASL image (lower row) and its reference image (upper row). No observable CSF contamination is found by visual inspection. The calculated CSF effect is o4.4% of VS-ASL signal. One can see the choroid plexus as a hyperintense signal within the ventricle in VS-ASL images.

profile and a gap is inserted between the tagging area and the slice of interest. Transit delay (yt) hence emerges to allow for the delivery of tags from the tagging region to the imaging plane. However, yt has been known to vary with location (Wong et al., 1998), physiological status (Buxton et al., 1998; Yang et al., 2000; Wu et al., 2005) and diseases (Chalela et al., 2000), which cause errors in both qualitative and quantitative perfusion measurement using ASL. In contrast, VS-ASL tags spins referring to flow velocity. In principle, yt is zero as cutoff velocity (V c) is chosen to be small enough that the targeted arterioles or capillaries are already inside the imaging plane and thereby circumvent the nuisance of yt variation. The scenario deviates, however, if high V c is used and the tagged blood originates from the arterial trees outside the slice to be imaged.

Low V c is usually achieved by increasing the amplitude of flow encoding gradients, which simultaneously increases diffusion weighting. Ideally, the VS-ASL difference signal comes from the signal modulation of inflowing blood spins. In practice, however, significant CSF artifacts can exist in VS-ASL images for V c up to at least 2.8 cm/s (Wong, 2004). Simple inversion recovery (Duhamel et al., 2003) and a more time-efficient T2-FLAIR-based strategy (Wong, 2004) have been proposed to serve this purpose. Utilizing a pair of identical 180- adiabatic pulses in this study, longer separation of diffusion gradients in VS train incidentally makes b value smaller, which eliminates the necessity of CSF suppression for even lower V c with the tradeoff of greater T2related attenuation of the tagged magnetization. Experimental data demonstrated satisfactory perfusion maps without observable CSF contamination as V c = 2 cm/s. The quantitative CBF is 72.8 ml/100 ml/min (V c = 2 cm/s) and agrees with the previously reported values (Alsop and Detre, 1996; Wong et al., 1998; Yongbi et al., 2002). SNR efficiency As mentioned, the quantification of ASL perfusion fairly relies on a good estimate of yt, which is usually unknown and can vary by several tenths of a second across a single image

Intravascular effect On the premise of steady flow, the time at which VS-ASL signal reaches its maximum can be calculated by: flDM ðTIÞ fl ðTI I expðTI=T1b ÞÞ ¼ 0 ¼ flTI flTI

ð2Þ

and TIDMmax = T 1b . The experimental data with V c = 2 cm/s demonstrate conformity with the theoretical prediction and suggest the absence or insignificance of yt. On the other hand, the VS-ASL signals with V c = 4 and 8 cm/s peak at smaller TI values. This seems to contradict the fact that high V c tags more upstream arterial trees and hence needs a longer yt for tag delivery. As a matter of fact, the observation can be explained by the intravascular effect from large vessels. In Fig. 5, VS-ASL signals are obtained by adjusting the mask threshold for different weighting of large vessels. When V c = 8 cm/s, the higher proportion of large-vessel voxels is included, the earlier VS-ASL signal peaks because through-

Fig. 7. Apparent flow. In conventional ASL, the estimated yt can be either longer or shorter than the actual yt. In VS-ASL, an inappropriately high V c tags the arterial trees outside the imaging slice, i.e. yt > 0 (dash-dot line). When V c is smaller than a threshold, the tagged blood resides in the slice of interest (yt = 0) and flow measurement is independent of TI (solid line).

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plane (Wong et al., 1997). With the existence of yt, CBF can be expressed as: CBFðyt Þ ¼

DM ðTIÞ : M0b I ðTI  yt Þ I expð TI=T1b Þ

ð3Þ

The apparent flow can be calculated by taking the ratio between CBF(yt) and CBF(0). Fig. 7 shows the effect of 100 ms yt variation on apparent flow. If tagged blood arrives 100 ms earlier than expected without a well-defined temporal bolus width, quantitative error is about 5% in the commonly used TI range (1000 – 2000 ms) and can be up to 40% as an inappropriately short TI is chosen. Only when yt is correctly estimated can correct flow be measured independent of the TI used for imaging (solid line). One advantage of VS-ASL is its potential for measuring perfusion without the uncertainty of yt. An inappropriately high V c, however, can lead to nonzero yt and underestimated CBF (dash-dot line). On the premise of sufficient SNR and a properly chosen V c, TI and TR can be reduced to increase temporal resolution if continuous perfusion maps are of interest. VS-ASL with low V c provides promise to this requirement, e.g. applications in functional MRI. The optimal TI and TR are calculated by maximizing SNR efficiency:   TIeTI=T1b 1  eTR=T1b pffiffiffiffiffiffiffi ðsingle slice or small number or slicesÞ TR ð4Þ   TIeTI=T1b 1  eðTRTIÞ=T1b pffiffiffiffiffiffiffi ðslab imagingÞ TR

ð5Þ

where T 1b = 1664 ms. On condition of single slice or small number of slices, TR/TI = 2092 ms/1664 ms gives the optimal SNR efficiency considering tags flowing from outside of imaging region. For slab imaging, we assume that the inflow tags have been in the imaging region for the past TRs, i.e. inflow tags have been excited by the latest control image. The optimal SNR efficiency is found at TR/TI = 4493 ms/1404 ms. To circumvent the inflow effect, a global saturation pulse can be applied right after image acquisition.

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nonmonotonically decelerating flow can produce a transition zone where blood is partially tagged during the tagging process, and partially excited during the imaging process. Although a sufficient TI can make the overall bolus size insensitive to the shape of the velocity selectivity profile, transition band does limit the spatial localization of the signal to the target tissue (Wong et al., in press). Two common concerns about VS-ASL are (a) the extremely slow moving tags that never reach the voxel of interest; (b) the discontinuous tag bolus due to directional dependence. Both influences can be mitigated by choosing a low V c that generates tags already in imaging slice, i.e. yt = 0. According to our results, a V c < 4 cm/s is recommended. VS-ASL signal is comprised of blood that flows at velocities above V c as tagging is applied and then decelerates to a velocity below V c prior to imaging. The assumptions are largely considered valid in arterial flow, regardless of pulsatility. In general, venous flow accelerates. If the flow velocity is faster than V c during the tagging process, it will still be above V c at image acquisition. As a result, the blood is not imaged. However, deceleration can happen when blood merges into large veins, which commonly results in enhancement of the sagittal sinus.

Conclusion Systematic evaluation of the interaction between TI and V c in VS-ASL is presented. Significant signal from large vessels exists in VS-ASL images for V c down to at least 4 cm/s. With high V c, intravascular effect of through plane vessels and the nonzero yt of tags complicate the data interpretation. Low V c (<4 cm/s) is recommended for quantitative measurement of tissue perfusion.

Acknowledgments The authors wish to thank Karam Sidaros and Elizabeth Yoder for helpful input in the development of VS-ASL, and acknowledge the support of the NIH (R01 EB002096).

Technical considerations References The main advantage of VS-ASL over conventional ASL is its independence of yt when V c is properly chosen. Therefore, VSASL has the potential in volume imaging and perfusion measurement of slow flow or long yt. In these applications, conventional ASL methods suffer from the variation and elongation of yt, which leads to erroneous quantification. However, VS-ASL usually has lower SNR due to its tagging strategy. Signal stability can be significantly improved by background suppression. The kernel of VS-ASL, sinc-shaped modulation of longitudinal magnetization vs. velocity, is based on the assumption of laminar flow, which is true in most primary vessels in vivo but not necessarily valid in capillary network. When the vessel size shrinks to a degree accompanied by circuitous routes, flow becomes more plug-like and hence sets a lower limit to the choice of V c. In human brain, flow velocity in penetrating arterioles is 1 – 2 cm/s (Kobari et al., 1984), in which laminar flow still dominates the flow pattern and VS tagging is feasible. Another issue is the bolus profile of tags and tagging efficiency. Either the imperfect velocity selectivity or the existence of

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