Influence of the cardiac cycle on velocity selective and acceleration selective arterial spin labeling

Purpose: In this study, the influence of the cardiac cycle on the amount of label produced by a velocity-selective (VSASL) and acceleration-selective arterial spin labeling (AccASL) module was investigated.Methods: A short-PLD sequence was developed where a single VSASL- or AccASL-module was preceded by pCASL labeling to isolate the arterial blood pool. ASL subtraction was performed with label/control images with similar cardiac phase and time-of-measurement, followed by retrospective binning in 10 cardiac phase bins. ASL signal variation over the heart cycle was evaluated and tested for significance using a permutation test.Results: VSASL and AccASL showed significant arterial signal fluctuations over the cardiac cycle of up to similar to 36% and similar to 64%, respectively, mainly in areas containing large arteries. pCASL also showed significant signal fluctuations, of up to similar to 25% in arteries. Raw label/control images confirmed that the observed signal fluctuations were caused by the amount of label produced during the cardiac cycle, rather than inflow-effects, because the raw images did not all show equal cardiac phase dependence. No significant effects of the cardiac cycle were found on the gray matter ASL-signal.Conclusion: Significant influence of the cardiac cycle on the generated label was found for spatially nonselective ASL-sequences. Hence, to become independent of the cardiac cycle, sufficient averages need to be taken. Alternatively, these findings could be highly interesting for the purpose of quantifying pulsatility more distally in the vascular tree.Cardiovascular Aspects of Radiolog

Three-dimensional gradient and spin-echo readout for time-encoded pseudo-continuous arterial spin labeling: influence of segmentation factor and flow compensation

Purpose To monitor the complete passage of the labeled blood through the vascular tree into tissue and improve the quantification of ASL maps, we evaluated the effect of 3D gradient and spin-echo (GRASE) readout segments on temporal SNR (tSNR) and image blurriness for time-encoded pseudo-continuous arterial spin labeling and the effect of flow-compensation gradients on the presence of intravascular signal.Methods Fifteen volunteers were scanned using time-encoded pCASL with 2D EPI and single-segment, two-segments, and three-segments 3D-GRASE readouts with first-order flow compensation (FC) gradients. Two-segments 3D-GRASE scans were acquired with 25%, 50%, 75%, and 100% of full first-order FC. Temporal SNR was assessed, and cerebral blood flow and arterial blood volume were quantified for all readout strategies.Results For single-segment 3D GRASE, tSNR was comparable to 2D EPI for perfusion signal but worse for the arterial signal. Two-segments and three-segments 3D GRASE resulted in higher tSNR than 2D EPI for perfusion and arterial signal. The arterial signal was not well visualized for 3D-GRASE data without FC. Visualization of the intravascular signal at postlabeling delays of 660 ms and 1060 ms was restored with FC. Adequate visualization of the intravascular signal was achieved from 75% of FC gradient strength at a postlabeling delay of 660 ms. For a postlabeling delay of 1060 ms, full-FC gradients were the best option to depict intravascular signal.Conclusion Segmented GRASE provided higher effective tSNR compared with 2D-EPI and single-segment GRASE. Flow compensation with GRASE readout should be carefully controlled when applying for time-encoded pCASL to visualize intravascular signal.Cardiovascular Aspects of Radiolog

Combining T-2 measurements and crusher gradients into a single ASL sequence for comparison of the measurement of water transport across the blood-brain barrier

Purpose Arterial spin labeling can be used to assess the transition time of water molecules across the blood-brain barrier when combined with sequence modules, which allow a separation of intravascular from tissue signal. The bipolar gradient technique measures the intravascular fraction by removing flowing spins. The T-2-relaxation-under-spin-tagging (TRUST) technique modulates the TE to differentiate between intravascular and extravascular spins based on T-2. These modules were combined into a single time-encoded pseudo-continuous arterial spin labeling sequence to compare their mechanisms of action as well as their assessment of water transition across the blood-brain barrier.Methods This protocol was acquired on a scanner with 9 healthy volunteers who provided written, informed consent. The sequence consisted of a Hadamard-encoded pseudo-continuous arterial spin labeling module, followed by the TRUST module (effective TEs of 0, 40, and 80 ms) and bipolar flow-crushing gradients (2, 4, and infinity cm/s). An additional experiment was performed with TRUST and a 3D gradient and spin-echo readout.Results Gradients imperfectly canceled the intravascular signal, as evidenced by the presence of residual signal in the arteries at early postlabeling delays as well as the underestimation of the intravascular fraction as compared with the TRUST method. The TRUST module allowed us to detect the transport of water deeper into the vascular tree through changes in T-2 than the used crusher gradients could, with their limited b-value.Conclusion Of the implemented techniques, TRUST allowed us to follow intravascular signal deeper into the vascular tree than the approach with (relatively weak) crusher gradients when quantifying the transport time of water across the blood-brain barrier.Neuro Imaging Researc

On the ability to exploit signal fluctuations in pseudocontinuous Arterial Spin Labeling for inferring the major flow territories from a traditional perfusion scan

Neuro Imaging Researc

Simultaneous acquisition of perfusion image and dynamic MR angiography using time-encoded pseudo-continuous ASL

Neuro Imaging Researc

Water/fat separation for self-navigated diffusion-weighted multishot echo-planar imaging

The purpose of this study was to develop a self-navigation strategy to improve scan efficiency and image quality of water/fat-separated, diffusion-weighted multishot echo-planar imaging (ms-EPI). This is accomplished by acquiring chemical shift-encoded diffusion-weighted data and using an appropriate water-fat and diffusion-encoded signal model to enable reconstruction directly from k-space data. Multishot EPI provides reduced geometric distortion and improved signal-to-noise ratio in diffusion-weighted imaging compared with single-shot approaches. Multishot acquisitions require corrections for physiological motion-induced shot-to-shot phase errors using either extra navigators or self-navigation principles. In addition, proper fat suppression is important, especially in regions with large B0 inhomogeneity. This makes the use of chemical shift encoding attractive. However, when combined with ms-EPI, shot-to-shot phase navigation can be challenging because of the spatial displacement of fat signals along the phase-encoding direction. In this work, a new model-based, self-navigated water/fat separation reconstruction algorithm is proposed. Experiments in legs and in the head–neck region of 10 subjects were performed to validate the algorithm. The results are compared with an image-based, two-dimensional (2D) navigated water/fat separation approach for ms-EPI and with a conventional fat saturation approach. Compared with the 2D navigated method, the use of self-navigation reduced the shot duration time by 30%–35%. The proposed algorithm provided improved diffusion-weighted water images in both leg and head–neck regions compared with the 2D navigator-based approach. The proposed algorithm also produced better fat suppression compared with the conventional fat saturation technique in the B0 inhomogeneous regions. In conclusion, the proposed self-navigated reconstruction algorithm can produce superior water-only diffusion-weighted EPI images with less artefacts compared with the existing methods. </p

Arterial spin labeling signal in the CSF: implications for partial volume correction and blood-CSF barrier characterization

For better quantification of perfusion with arterial spin labeling (ASL), partial volume correction (PVC) is used to disentangle the signals from gray matter (GM) and white matter within any voxel. Based on physiological considerations, PVC algorithms typically assume zero signal in the cerebrospinal fluid (CSF). Recent measurements, however, have shown that CSF-ASL signal can exceed 10% of GM signal, even when using recommended ASL labeling parameters. CSF signal is expected to particularly affect PVC results in the choroid plexus. This study aims to measure the impact of CSF signal on PVC perfusion measurements, and to investigate the potential use of PVC to retrieve pure CSF-ASL signal for blood-CSF barrier characterization. In vivo imaging included six pCASL sequences with variable label duration and post-labeling delay (PLD), and an eight-echo 3D-GRASE readout. A dataset was simulated to estimate the effect of CSF-PVC with known ground-truth parameters. Differences between the results of CSF-PVC and non-CSF-PVC were estimated for regions of interest (ROls) based on GM probability, and a separate ROI isolating the choroid plexus. In vivo, the suitability of PVC-CSF signal as an estimate of pure CSF was investigated by comparing its time course with the long-TE CSF signal. Results from both simulation and in vivo data indicated that including the CSF signal in PVC improves quantification of GM CBF by approximately 10%. In simulated data, this improvement was greater for multi-PLD (model fitting) quantification than for single PLD (similar to 1-5% difference). In the choroid plexus, the difference between CSF-PVC and non-CSF-PVC was much larger, averaging around 30%. Long-TE (pure) CSF signal could not be estimated from PVC CSF signal as it followed a different time course, indicating the presence of residual macrovascular signal in the PVC. The inclusion of CSF adds value to PVC for more accurate measurements of GM perfusion, and especially for quantification of perfusion in the choroid plexus and study of the glymphatic system.Radiolog

Regularized joint water-fat separation with B-0 map estimation in image space for 2D-navigated interleaved EPI based diffusion MRI

Purpose To develop a new water-fat separation and B-0 estimation algorithm to effectively suppress the multiple resonances of fat signal in EPI. This is especially relevant for DWI where fat is often a confounding factor. Methods Water-fat separation based on chemical-shift encoding enables robust fat suppression in routine MRI. However, for EPI the different chemical-shift displacements of the multiple fat resonances along the phase-encoding direction can be problematic for conventional separation algorithms. This work proposes a suitable model approximation for EPI under B-0 and fat off-resonance effects, providing a feasible multi-peak water-fat separation algorithm. Simulations were performed to validate the algorithm. In vivo validation was performed in 6 volunteers, acquiring spin-echo EPI images in the leg (B-0 homogeneous) and head-neck (B-0 inhomogeneous) regions, using a TE-shifted interleaved EPI sequence with/without diffusion sensitization. The results are numerically and statistically compared with voxel-independent water-fat separation and fat saturation techniques to demonstrate the performance of the proposed algorithm. Results The reference separation algorithm without the proposed spatial shift correction caused water-fat ambiguities in simulations and in vivo experiments. Some spectrally selective fat saturation approaches also failed to suppress fat in regions with severe B-0 inhomogeneities. The proposed algorithm was able to achieve improved fat suppression for DWI data and ADC maps in the head-neck and leg regions. Conclusion The proposed algorithm shows improved suppression of the multi-peak fat components in multi-shot interleaved EPI applications compared to the conventional fat saturation approaches and separation algorithms.Neuro Imaging ResearchRadiolog

Validation of the estimation of the macrovascular contribution in multi-timepoint arterial spin labeling MRI using a 2-component kinetic model

Purpose In this paper, the ability to quantify cerebral blood flow by arterial spin labeling (ASL) was studied by investigating the separation of the macrovascular and tissue component using a 2-component model. Underlying assumptions of this model, especially the inclusion of dispersion in the analysis, were studied, as well as the temporal resolution of the ASL datasets. Methods Four different datasets were acquired: (1) 4D ASL angiography to characterize the macrovascular component and to study dispersion modeling within this component, (2) high temporal resolution ASL data to investigate the separation of the 2 components and the effect of dispersion modelling on this separation, (3) low temporal resolution ASL dataset to study the effect of the temporal resolution on the separation of the 2 components, and (4) low temporal resolution ASL data with vascular crushing. Results The model that included a gamma dispersion kernel had the best fit to the 4D ASL angiography. For the high temporal resolution ASL dataset, inclusion of the gamma dispersion kernel led to more signal included in the arterial blood volume map, which resulted in decreased cerebral blood flow values. The arterial blood volume and cerebral blood flow maps showed overall higher arterial blood volume values and lower cerebral blood flow values for the high temporal resolution dataset compared to the low temporal resolution dataset. Conclusion Inclusion of a gamma dispersion kernel resulted in better fitting of the model to the data. The separation of the macrovascular and tissue component is affected by the inclusion of a gamma dispersion kernel and the temporal resolution of the ASL dataset.Cardiovascular Aspects of Radiolog