Recommendations for quantitative cerebral perfusion MRI using multi‐timepoint arterial spin labeling: Acquisition, quantification, and clinical applications

作者：Joseph G. Woods, Eric Achten, Iris Asllani, Divya S. Bolar, Weiying Dai, John A. Detre, Audrey P. Fan, María A. Fernández‐Seara, Xavier Golay, Matthias Günther, Jia Guo, Luis Hernández-García, Mai‐Lan Ho, Meher R. Juttukonda, Hanzhang Lu, Bradley J. MacIntosh, Ananth J. Madhuranthakam, Henk Mutsaerts, Thomas W. Okell, Laura M. Parkes, Nándor Pintér, Joana Pinto, Qin Qin, Marion Smits, Yuriko Suzuki, David L. Thomas, Matthias J.P. van Osch, Danny J.J. Wang, Esther A. H. Warnert, Greg Zaharchuk, Fernando Zelaya, Moss Zhao, Michael A. Chappell, the ISMRM Perfusion Study Group · 发表于：Magnetic Resonance in Medicine · 年份：2024 · DOI：10.1002/mrm.30091 · 被引用次数：65 · 研究领域：Advanced MRI Techniques and Applications、Advanced Neuroimaging Techniques and Applications、MRI in cancer diagnosis

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 ser...