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This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple-timepoint ASL, body ASL, and clinical ASL recommendations.

This review article provides an overview of the current status of velocity-selective arterial spin labeling (VSASL) perfusion MRI and is part of a wider effort arising from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group. Since publication of the 2015 consensus paper on arterial spin labeling (ASL) for cerebral perfusion imaging, important advancements have been made in the field. The ASL community has, therefore, decided to provide an extended perspective on various aspects of technical development and application. Because VSASL has the potential to become a principal ASL method because of its unique advantages over traditional approaches, an in-depth discussion was warranted. VSASL labels blood based on its velocity and creates a magnetic bolus immediately proximal to the microvasculature within the imaging volume. VSASL is, therefore, insensitive to transit delay effects, in contrast to spatially selective pulsed and (pseudo-) continuous ASL approaches. Recent technical developments have improved the robustness and the labeling efficiency of VSASL, making it a potentially more favorable ASL approach in a wide range of applications where transit delay effects are of concern. In this review article, we (1) describe the concepts and theoretical basis of VSASL; (2) describe different variants of VSASL and their implementation; (3) provide recommended parameters and practices for clinical adoption; (4) describe challenges in developing and implementing VSASL; and (5) describe its current applications. As VSASL continues to undergo rapid development, the focus of this review is to summarize the fundamental concepts of VSASL, describe existing VSASL techniques and applications, and provide recommendations to help the clinical community adopt VSASL.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision‐making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi‐timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post‐labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi‐timepoint data can be acquired in the same scan time as single‐PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single‐PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi‐timepoint ASL and provides robust recommendations for acquiring high‐quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi‐timepoint ASL data. Furthermore, we review the potential clinical applications where multi‐timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article. [ABSTRACT FROM AUTHOR]

This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade-offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo-continuous labeling, background suppression, a segmented three-dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model.

Purpose: In velocity‐selective (VS) arterial spin labeling, strategies using multiple saturation modules or using VS inversion (VSI) pulse can provide improved SNR efficiency compared to the original labeling scheme using one VS saturation (VSS) module. Their performance improvement, however, has not been directly compared. Methods: Different VS labeling schemes were evaluated by Bloch simulation for their SNR efficiency, eddy current sensitivity, and robustness against B1 and B0 variation. These schemes included dual‐module double‐refocused hyperbolic secant and symmetric 8‐segment B1‐insensitive rotation (sBIR8‐) VSS pulses, the original and modified Fourier transform‐based VSI pulses. A subset of the labeling schemes was examined further in phantom and in vivo experiments for their eddy current sensitivity and SNR performance. An additional sBIR8‐VSS with a built‐in inversion (sBIR8‐VSS‐inversion) was evaluated for the effects of partial background suppression to allow a fairer comparison to VSI. Results: According to the simulations, the sBIR8‐VSS was the most robust against field imperfections and had similarly high SNR efficiency (dual‐module, dual‐sBIR8‐VSS) compared with the best VSI pulse (sinc‐modulated, sinc‐VSI). These were confirmed by the phantom and in vivo data. Without additional background suppression, the sinc‐VSI pulses had the highest temporal SNR, closely followed by the sBIR8‐VSS‐inversion pulse, both benefited from partial background suppression effects. Conclusion: Dual‐sBIR8‐VSS and sinc‐VSI measured the highest SNR efficiency among the VS labeling schemes. Dual‐sBIR8‐VSS was the most robust against field imperfections, whereas sinc‐VSI may provide a higher SNR efficiency if its immunity to field imperfections can be improved. [ABSTRACT FROM AUTHOR]

Purpose: Arterial Spin Labeling (ASL) is a quantitative, non‐invasive alternative for perfusion imaging that does not use contrast agents. The magnetic resonance fingerprinting (MRF) framework can be adapted to ASL to estimate multiple physiological parameters simultaneously. In this work, we introduce an optimization scheme to increase the sensitivity of the ASL fingerprint. We also propose a regression based estimation framework for MRF‐ASL. Methods: To improve the sensitivity of MRF‐ASL signals to underlying parameters, we optimized ASL labeling durations using the Cramer‐Rao Lower Bound (CRLB). This paper also proposes a neural network regression based estimation framework trained using noisy synthetic signals generated from our ASL signal model. We tested our methods in silico and in vivo, and compared with multiple post labeling delay (multi‐PLD) ASL and unoptimized MRF‐ASL. We present comparisons of estimated maps for the six parameters of our signal model. Results: The scan design process facilitated precise estimates of multiple hemodynamic parameters and tissue properties from a single scan, in regions of normal gray and white matter, as well as regions with anomalous perfusion activity in the brain. In particular, there was a 86.7% correlation of perfusion estimates with the ground truth in silico, using our proposed techniques. In vivo, there was roughly a 7 fold improvement in the Coefficient of Variation (CoV) for white matter perfusion, and 2 fold improvement in gray matter perfusion CoV in comparison to a reference Multi PLD method. The regression based estimation approach provided perfusion estimates rapidly, with estimation times of around 1s per map. Conclusions: Scan design optimization, coupled with regression‐based estimation is a powerful tool for improving precision in MRF‐ASL [ABSTRACT FROM AUTHOR]

Purpose: This paper discusses several challenges faced by super‐selective pseudo‐continuous arterial spin labeling, which is used to quantify territorial perfusion in the cerebral circulation. The effects of off‐resonance, pulsatility, vessel movement, and label rotation scheme are investigated, and methods to maximize labeling efficiency and overall image quality are evaluated. A strategy to calculate the territorial perfusion fractions of individual vessels is proposed. Methods: The effects of off‐resonance, label rotation scheme, and vessel movement on labeling efficiency were simulated. Two off‐resonance compensation strategies (multiphase prescan, field map), cardiac triggering, and vessel movement were studied in vivo in a group of 10 subjects. Subsequently, a territorial perfusion fraction map was acquired in 2 subjects based on the mean vessel labeling efficiency. Results: Multiphase calibration provided the highest labeling efficiency (P =.002) followed by the field map compensation (P =.037) compared with the uncompensated acquisition. Cardiac triggering resulted in a qualitative improvement of the image and an increase in signal contrast between the perfusion territory and the surrounding tissue (P =.010) but failed to show a significant change in temporal and spatial SNR. The constant clockwise label rotation scheme yielded the highest labeling efficiency. Significant vessel movement (>2 mm according to simulations) was observed in 50% of subjects. The measured territorial perfusion fractions showed good agreement with anatomical data. Conclusion: Optimized labeling efficiency resulted in increased image quality and accuracy of territorial perfusion fraction maps. Labeling efficiency depends critically on off‐resonance calibration, cardiac triggering, optimal label rotation scheme, and vessel location tracking. [ABSTRACT FROM AUTHOR]

Purpose: This work aims to investigate the utility of velocity selective inversion pulses for perfusion weighted functional MRI. Methods: Tracer kinetic properties of velocity selective inversion (VSI) pulses as an input function for an arterial spin labeling (ASL) experiment were characterized in a group of healthy participants. Numerical simulations were conducted to search for a robust set of timing parameters for FMRI time series acquisition with maximal signal to noise ratio efficiency. The performance of three VSI pulse sequences with different timing parameters was compared with a pseudocontinuous ASL sequence in a simple FMRI experiment conducted on healthy participants. Results: The fit to the tracer kinetic model yielded arterial CBV of 1.24% ± 0.52% and 0.45 ± 0.11% and perfusion rates of 60.8 ± 32.3 and 34.4 ± 5.4 mL/min/100 g for gray and white matter, respectively. Bolus arrival times were estimated as 75.7 ± 21 ms and 349 ± 78 ms for gray and white matter, respectively. The FMRI experiments showed that VSI pulses yield comparable sensitivity to PCASL with similar timing parameters (TR = 4 s). However, VSI pulses could be used at a faster acquisition speed (TR = 3 s) and were more sensitive to neuronal activity than PCASL pulses, as evidenced by the 31% higher Z scores obtained on average in the active regions. Conclusion: VSI pulses can be very beneficial for perfusion weighted functional MRI because of their tracer kinetic characteristics, which allow a faster acquisition rate while maintaining an efficient labeling input function. [ABSTRACT FROM AUTHOR]

In the above referenced article, we would like to correct the error of the misplaced SI SB B sb term and update the Equation (1) as well as the first sentence of Section 9.5 as below: 9.5 Quantification of VSASL The blood flow (BF, in mL/100 g/min) can be quantified based on the kinetic model as: 1 HT ht Erratum to: Velocity-selective arterial spin labeling perfusion MRI: A review of the state of the art and recommendations for clinical implementation (Magn Reson Med. [Extracted from the article]

Purpose To demonstrate that MR sequences can detect individual histotripsy bubble clouds formed inside intact tissues. Methods A line-scan and an EPI sequence were sensitized to histotripsy by inserting a bipolar gradient whose lobes bracketed the lifespan of a histotripsy bubble cloud. Using a 7 Tesla, small-bore scanner, these sequences monitored histotripsy clouds formed in an agar phantom and in vitro porcine liver and brain. The bipolar gradients were adjusted to apply phase with k-space frequencies of 10, 300 or 400 cm−1. Acoustic pressure amplitude was also varied. Cavitation was simultaneously monitored using a passive cavitation detection system. Results Each image captured local signal loss specific to an individual bubble cloud. In the agar phantom, this signal loss appeared only when the transducer output exceeded the cavitation threshold pressure. In tissues, bubble clouds were immediately detected when the gradients created phase with k-space frequencies of 300 and 400 cm−1. When the gradients created phase with a k-space frequency of 10 cm−1, individual bubble clouds were not detectable until many acoustic pulses had been applied to the tissue. Conclusion Cavitation-sensitive MR-sequences can detect single histotripsy bubble clouds formed in biologic tissue. Detection is influenced by the sensitizing gradients and treatment history. Magn Reson Med 76:1486-1493, 2016. © 2015 International Society for Magnetic Resonance in Medicine [ABSTRACT FROM AUTHOR]