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In this study, a new arterial spin labeling (ASL) method with spatially nonselective labeling is introduced, based on the acceleration of flowing spins, which is able to image brain perfusion with minimal contamination from venous signal. This method is termed acceleration-selective ASL (AccASL) and resembles velocity-selective ASL (VSASL), with the difference that AccASL is able to discriminate between arterial and venous components in a single preparation module due to the higher acceleration on the arterial side of the microvasculature, whereas VSASL cannot make this distinction unless a second labeling module is used. A difference between AccASL and VSASL is that AccASL is mainly cerebral blood volume weighted, whereas VSASL is cerebral blood flow weighted. AccASL exploits the principles of acceleration-encoded magnetic resonance angiography by using motion-sensitizing gradients in a T2-preparation module. This method is demonstrated in healthy volunteers for a range of cutoff accelerations. Additionally, AccASL is compared with VSASL and pseudo-continuous ASL, and its feasibility in functional MRI is demonstrated. Compared with VSASL with a single labeling module, a strong and significant reduction in venous label is observed. The resulting signal-to-noise ratio is comparable to pseudo-continuous ASL and robust activation of the visual cortex is observed. Magn Reson Med 71:191–199, 2014. © 2013 Wiley Periodicals, Inc.
Arterial spin labeling (ASL) techniques can be used to quantify local tissue perfusion noninvasively [1, 2]. Conventional ASL methods tag arterial blood spins by saturation or inversion in a plane proximal to the imaging region. After a delay, the inflow time (TI), a label image is acquired. This TI is chosen approximately equal to the T1 of blood for cerebral perfusion imaging, representing a compromise between loss of the label due to longitudinal (T1) relaxation and a transport time long enough for the labeled blood to reach the microvascular bed . Subsequently, the sequence is repeated without labeling, thereby obtaining the so-called control image. Subtraction of the label image from the control image results in a perfusion-weighted image, which reflects solely the magnetization of the inflowing tagged spins without contamination from static tissue. Multiple interleaved averages of the label and control sequence are required to gain sufficient signal-to-noise ratio (SNR).
>A major confound of conventional ASL techniques is that a significant amount of label is lost because of T1-relaxation in the time it takes for the blood to flow from the labeling to the imaging plane, the so-called transit time. Furthermore, in several pathological brain conditions, because of slow or collateral flow the label relaxes almost completely before reaching the microvascular bed, leading to severe underestimation of cerebral blood flow (CBF). Even in normal volunteers the variation in transit time can be up to hundreds of milliseconds across a single slice .
Recently, a technique called velocity-selective ASL (VSASL) was introduced, in which spins are tagged based on flow velocity rather than spatial localization [5-7]. This enables labeling within the imaging region where perfusion is measured. By generating the label much closer to the capillaries, smaller and more uniform transit delays are obtained, and therefore VSASL can provide (semi) quantitative CBF maps even under slow and collateral flow conditions .
The first velocity-selective labeling module labels all spins that flow faster than the cutoff velocity (VC), irrespective of whether these are located in arterial or venous blood. Using only this labeling approach (which we will refer to as “single VSASL”) the signal is fundamentally cerebral blood volume weighted. The use of a second velocity-selective labeling module just before imaging (dubbed “dual VSASL”) will exclude the venous components, because accelerating spins will be suppressed . Furthermore, the VSASL signal is converted into a CBF-weighted signal. This approach suffers, however, from a reduced SNR by limiting the labeling to spins that decelerate to a velocity below VC before the second labeling module, as well as due to increased T2-relaxation and diffusion weighting (DW) because of the second labeling module.
More recently, it has been shown in magnetic resonance angiography that acceleration-encoded imaging can selectively image the arteries, without contamination from venous signal . Acceleration-dependent preparation differs from a velocity-selective approach in that it does not affect the magnetization from spins flowing at a constant velocity, but dephases spins that are accelerating or decelerating . In the vascular tree, the average velocity of the spins decreases from the arteries toward the capillaries, after which their average velocity increases only slightly while flowing to the veins. Pulsatility is known to be higher in the arteries than in the veins, providing a second origin for the differentiation between arterial and venous blood by using acceleration encoding. Moreover, the tortuosity of the vessels, and especially of the capillaries, is a third origin of labeling. When the vessel orientation changes with respect to the acceleration-encoding direction, there will be incomplete refocusing of the magnetization.
The aim of this study is to introduce a new ASL method, which is able to image brain perfusion without contamination from venous or cerebral spinal fluid (CSF) signal, based on the principles of acceleration-encoded magnetic resonance angiography. The use of such an acceleration-dependent preparation module for ASL is demonstrated in healthy volunteers. This new method, referred to as acceleration-selective ASL (AccASL), is examined with different cutoff acceleration encodings, obtained by varying the motion-sensitizing gradients (MSGs). In addition, AccASL is compared with VSASL and a conventional spatially selective ASL method, and the feasibility of AccASL in functional MRI (fMRI) is demonstrated.
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In this study, we have proposed acceleration selection in ASL for labeling the arterial blood compartment within the imaging region without contamination from venous blood or CSF, and this sequence was successfully demonstrated in healthy volunteers to obtain resting-state perfusion maps as well as for fMRI.
By using a method with labeling not based on the spatial position of the spins, but on their acceleration, it was possible to label in the same plane as imaging, similar to VSASL. This creation of the label closer to the capillaries provides shorter and more uniform transit delays compared with traditional ASL, which makes this method theoretically suitable to use under slow or collateral flow conditions. This could also enable the use of shorter postlabeling times, resulting in a higher SNR, because there would be less loss of label through relaxation before it arrives in the microvasculature. This should, however, be confirmed by further research. Compared with conventional ASL, where the label is created by inversion of the magnetization, the use of saturation leads to a lower signal difference between the label and control condition, leading to a SNR penalty of a factor-of-two similar to VSASL.
The origin of the label in the blood created by AccASL is the result of at least three different processes. First, the flow velocity in the vessels is not constant, but is fluctuating because of the cardiac cycle. Acceleration-dependent preparation dephases the flowing spins magnetization that are accelerating or decelerating and a pulsatile flow has both of these properties. This characteristic was used previously in magnetic resonance angiography to achieve a good artery–vein separation, because blood flow in arteries is known to be more pulsatile than in veins . Second, the general distribution of blood flow velocities over the cerebral vasculature is known to decrease for smaller vessels [25, 26]. In general, closer to the capillaries, the vasculature branches with vessels becoming smaller in diameter, but with the total surface area becoming larger, resulting in a lower blood velocity. Therefore, as the blood flows from the arterial compartment to the capillaries the blood will on average decelerate, whereas it will accelerate when flowing into the venous compartment. Third, the tortuosity of vessels, for example, at bifurcations of vessels or due to branching, but especially at the level of the capillaries, can also be a source of labeling in AccASL. When the directionality of the vessels changes with respect to the acceleration-encoding gradient direction, there will not be (complete) refocusing. Because of the structure of the capillary bed, more label is created compared with VSASL, which cannot be targeted to this region, as there is no laminar flow present . All these three processes are introducing some cerebral blood volume weighting instead of the signal being only CBF-weighted, and further research should be performed to further study the specific hemodynamic contrast that is imaged by AccASL.
However, AccASL was shown to enable effective labeling of a large part of the arterial vasculature as proven by a similar SNR when compared with pCASL. The ASL signal intensity in GM was found to be comparable to pCASL and significantly higher compared with single and dual VSASL. Even though AccASL and VSASL both create label in the imaging plane, based on blood flow characteristics, it appears that more label is created with AccASL. Moreover, the signal maximum of the multi-TI measurements with AccASL and single VSASL is observed at the first time point, which indicates that the signal is specifically cerebral blood volume weighted, with filters of |A|>AC and |V|>VC, respectively. Also was demonstrated that at shorter postlabeling delay times more label was present in the GM of the ASL maps acquired with AccASL compared with single VSASL. This could make it feasible to reduce the postlabeling delay and thereby improve the time resolution, although future studies should prove this. Furthermore, the GM signal intensity also remained high at the later time points, proving that the label was indeed created in the arterioles and the microvasculature.
Focusing on the venous signal, the AccASL maps of the multi-TI measurements showed a decreasing signal intensity in the sagittal sinus up to 2.5–3 s postlabeling, whereas for single VSASL a high signal in the sagittal sinus was visible at all postlabeling delay times. Therefore, it appears that only a small signal is created in the venous compartment. This showed that an efficient elimination of venous signal can be accomplished with AccASL: no significant difference in ASL signal in the sagittal sinus was measured between AccASL, dual VSASL, and pCASL at a postlabel delay of 1600 ms, while venous contamination was clearly present in the image acquired with single VSASL. Nevertheless, elimination of the venous signal can be achieved with VSASL by the use of a second labeling module, applied just before imaging. For AccASL a waiting period is not required in order to exclude signal from the venous compartment, because labeling is based on the acceleration/deceleration during the labeling encoding module of typically 30–50 ms, while dual VSASL requires 1.0–1.5 s between two velocity-selective labeling modules to allow the spins to decelerate below VC. Additionally, the use of two labeling modules enables quantification of VSASL, because the temporal width of the labeling function is fixed, i.e., the amount of label created is being controlled. However, the use of a second labeling module in dual VSASL will also diminish the ASL signal by reduction of the labeling bolus by the second velocity-selective labeling module. Although elimination of the venous signal with AccASL was comparable to that using dual VSASL, in GM the ASL signal was significantly higher for AccASL. In future, the use of a second labeling module in AccASL should be examined to determine if this could make a valuable contribution to the quantification of the AccASL signal.
In AccASL and both VSASL sequences the same background suppression pulses were used. Nevertheless, the CSF signal was of comparable intensity for AccASL, pCASL, and dual VSASL, whereas it was higher for single VSASL. Therefore, the amount of CSF contamination is determined not only by the background suppression but also by the labeling sequence. A greater amount of CSF was apparently labeled with single VSASL.
The fMRI study showed that AccASL is able to detect hemodynamic changes associated with neuronal activation. An increase of ∼30% in signal during the visual stimuli was observed compared with the baseline ASL signal during rest. ASL methods are in general considered more suitable than BOLD for studying slow variations in brain function over periods greater than a minute, because ASL shows stable noise characteristics over the entire frequency spectrum [28, 29]. Furthermore, ASL-based fMRI has been advocated over BOLD because of improved localization. Vascular space occupancy (VASO) techniques, which are also cerebral blood volume weighted, improve localization of the activated regions during stimulation in fMRI, although at the cost of a lower SNR .The great advantage compared to conventional ASL techniques, which create label proximal to the image plane, is that with AccASL the label is generated in the same region as where the neuronal activation is located, so the label is created closer to the region where the local blood flow is altered. AccASL has therefore the potential to increase the temporal resolution of fMRI techniques based on hemodynamic imaging sequences. As the tagging is spatially nonselective, arterial transit time is not a limitation for anatomical coverage.
An artifactual contribution of the AccASL signal is caused by DW, because the MSGs of the labeling module also introduce diffusion sensitivity into the labeling process. The diffusion sensitivity of the sequence is characterized by the b-value and scales with the same parameters that determine the AC, but whereas the AC scales linearly with G and δ, the b-value scales quadratically. By varying the gradient parameters, the same AC can be obtained with different b-values and thus different contaminations by DW. Table 1 indicates how much change in signal intensity due to the use of MSG could theoretically be attributed to DW. To calculate contribution of the DW to the signal, the following formula was used: S/So=exp(−bD), in which S is the average signal in GM during the label condition, So is the average signal in GM during the control condition, b is the b-value corresponding to the gradient parameters, and D=0.0008 mm2/s for in GM [31-34]. The results from this calculation are shown in Figure 3. In this study, a maximum of 9% difference of the ASL signal was observed because of DW, which is within acceptable limits, except for the lowest AC with a b-value of 22.7 m/s2, where a 34% difference in ASL signal can be attributed to DW. Similar DW was found for AccASL when compared with VSASL .
In conclusion, the use of an acceleration-dependent preparation module for ASL with spatially nonselective labeling was demonstrated to be able to image brain perfusion without contamination from venous and CSF signal.