Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling

Purpose To determine whether sacrificing part of the scan time of pseudo-continuous arterial spin labeling (PCASL) for measurement of the labeling efficiency and blood T1 is beneficial in terms of CBF quantification reliability. Methods In a simulation framework, 5-minute scan protocols with different scan time divisions between PCASL data acquisition and supporting measurements were evaluated in terms of CBF estimation variability across both noise and ground truth parameter realizations taken from the general population distribution. The entire simulation experiment was repeated for a single-post-labeling delay (PLD), multi-PLD, and free-lunch time-encoded (te-FL) PCASL acquisition strategy. Furthermore, a real data study was designed for preliminary validation. Results For the considered population statistics, measuring the labeling efficiency and the blood T1 proved beneficial in terms of CBF estimation variability for any distribution of the 5-minute scan time compared to only acquiring ASL data. Compared to single-PLD PCASL without support measurements as recommended in the consensus statement, a 26%, 33%, and 42% reduction in relative CBF estimation variability was found for optimal combinations of supporting measurements with single-PLD, free-lunch, and multi-PLD PCASL data acquisition, respectively. The benefit of taking the individual variation of blood T1 into account was also demonstrated in the real data experiment. Conclusions Spending time to measure the labeling efficiency and the blood T1 instead of acquiring more averages of the PCASL data proves to be advisable for robust CBF quantification in the general population

Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI

The arterial input function (AIF) plays a crucial role in estimating quantitative perfusion properties from dynamic susceptibility contrast (DSC) MRI. An important issue, however, is that measuring the AIF in absolute contrast-agent concentrations is challenging, due to uncertainty in relation to the measured (Formula presented.) -weighted signal, signal depletion at high concentration, and partial-volume effects. A potential solution could be to derive the AIF from separately acquired dynamic contrast enhanced (DCE) MRI data. We aim to compare the AIF determined from DCE MRI with the AIF from DSC MRI, and estimated perfusion coefficients derived from DSC data using a DCE-driven AIF with perfusion coefficients determined using a DSC-based AIF. AIFs were manually selected in branches of the middle cerebral artery (MCA) in both DCE and DSC data in each patient. In addition, a semi-automatic AIF-selection algorithm was applied to the DSC data. The amplitude and full width at half-maximum of the AIFs were compared statistically using the Wilcoxon rank-sum test, applying a 0.05 significance level. Cerebral blood flow (CBF) was derived with different AIF approaches and compared further. The results showed that the AIFs extracted from DSC scans yielded highly variable peaks across arteries within the same patient. The semi-automatic DSC–AIF had significantly narrower width compared with the manual AIFs, and a significantly larger peak than the manual DSC–AIF. Additionally, the DCE-based AIF provided a more stable measurement of relative CBF and absolute CBF values estimated with DCE–AIFs that were compatible with previously reported values. In conclusion, DCE-based AIFs were reproduced significantly better across vessels, showed more realistic profiles, and delivered more stable and reasonable CBF measurements. The DCE–AIF can, therefore, be considered as an alternative AIF source for quantitative perfusion estimations in DSC MRI.</p

Absolute quantification of perfusion by dynamic susceptibility contrast MRI using Bookend and VASO steady-state CBV calibration: a comparison with pseudo-continuous ASL.

Dynamic susceptibility contrast MRI (DSC-MRI) tends to return elevated estimates of cerebral blood flow (CBF) and cerebral blood volume (CBV). In this study, subject-specific calibration factors (CFs), based on steady-state CBV measurements, were applied to rescale the absolute level of DSC-MRI CBF

Pseudocontinuous arterial spin labeling reveals dissociable effects of morphine and alcohol on regional cerebral blood flow

We have examined sensitivity and specificity of pseudocontinuous arterial spin labeling (PCASL) to detect global and regional changes in cerebral blood flow (CBF) in response to two different psychoactive drugs. We tested alcohol and morphine in a placebo-controlled, double-blind randomized study in 12 healthy young men. Drugs were administered intravenously. Validated pharmacokinetic protocols achieved minimal intersubject and intrasubject variance in plasma drug concentration. Permutation-based statistical testing of a mixed effect repeated measures model revealed a widespread increase in absolute CBF because of both morphine and alcohol. Conjunction analysis revealed overlapping effects of morphine and alcohol on absolute CBF in the left anterior cingulate, right hippocampus, right insula, and left primary sensorimotor areas. Effects of morphine and alcohol on relative CBF (obtained from z-normalization of absolute CBF maps) were significantly different in the left putamen, left frontoparietal network, cerebellum, and the brainstem. Corroborating previous PET results, our findings suggest that PCASL is a promising tool for central nervous system drug research

Partial volume correction in arterial spin labeling perfusion MRI: A method to disentangle anatomy from physiology or an analysis step too far?

The mismatch in the spatial resolution of Arterial Spin Labeling (ASL) MRI perfusion images and the anatomy of functionally distinct tissues in the brain leads to a partial volume effect (PVE), which in turn confounds the estimation of perfusion into a specific tissue of interest such as gray or white matter. This confound occurs because the image voxels contain a mixture of tissues with disparate perfusion properties, leading to estimated perfusion values that reflect primarily the volume proportions of tissues in the voxel rather than the perfusion of any particular tissue of interest within that volume. It is already recognized that PVE influences studies of brain perfusion, and that its effect might be even more evident in studies where changes in perfusion are co-incident with alterations in brain structure, such as studies involving a comparison between an atrophic patient population vs control subjects, or studies comparing subjects over a wide range of ages. However, the application of PVE correction (PVEc) is currently limited and the employed methodologies remain inconsistent.In this article, we outline the influence of PVE in ASL measurements of perfusion, explain the main principles of PVEc, and provide a critique of the current state of the art for the use of such methods. Furthermore, we examine the current use of PVEc in perfusion studies and whether there is evidence to support its wider adoption.We conclude that there is sound theoretical motivation for the use of PVEc alongside conventional, ‘uncorrected’, images, and encourage such combined reporting. Methods for PVEc are now available within standard neuroimaging toolboxes, which makes our recommendation straightforward to implement. However, there is still more work to be done to establish the value of PVEc as well as the efficacy and robustness of existing PVEc methods