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A systematic study of the sensitivity of partial volume correction methods for the quantification of perfusion from pseudo-continuous arterial spin labeling MRI

Zhao, Moss Y.; Mezue, Melvin; Segerdahl, Andrew R.; Okell, Thomas W.; Tracey, Irene; Xiao, Yingyi; Chappell, Michael A.

A systematic study of the sensitivity of partial volume correction methods for the quantification of perfusion from pseudo-continuous arterial spin labeling MRI Thumbnail


Authors

Moss Y. Zhao

Melvin Mezue

Andrew R. Segerdahl

Thomas W. Okell

Irene Tracey

Yingyi Xiao



Abstract

Arterial spin labeling (ASL) MRI is a non-invasive technique for the quantification of cerebral perfusion, and pseudo-continuous arterial spin labeling (PCASL) has been recommended as the standard implementation by a recent consensus of the community. Due to the low spatial resolution of ASL images, perfusion quantification is biased by partial volume effects. Consequently, several partial volume correction (PVEc) methods have been developed to reduce the bias in gray matter (GM) perfusion quantification. The efficacy of these methods relies on both the quality of the ASL data and the accuracy of partial volume estimates. Here we systematically investigate the sensitivity of different PVEc methods to variability in both the ASL data and partial volume estimates using simulated PCASL data and in vivo PCASL data from a reproducibility study. We examined the PVEc methods in two ways: the ability to preserve spatial details and the accuracy of GM perfusion estimation. Judging by the root-mean-square error (RMSE) between simulated and estimated GM CBF, the spatially regularized method was superior in preserving spatial details compared to the linear regression method (RMSE of 1.2 vs 5.1 in simulation of GM CBF with short scale spatial variations). The linear regression method was generally less sensitive than the spatially regularized method to noise in data and errors in the partial volume estimates (RMSE 6.3 vs 23.4 for SNR = 5 simulated data), but this could be attributed to the greater smoothing introduced by the method. Analysis of a healthy cohort dataset indicates that PVEc, using either method, improves the repeatability of perfusion quantification (within-subject coefficient of variation reduced by 5% after PVEc).

Citation

Zhao, M. Y., Mezue, M., Segerdahl, A. R., Okell, T. W., Tracey, I., Xiao, Y., & Chappell, M. A. (2017). A systematic study of the sensitivity of partial volume correction methods for the quantification of perfusion from pseudo-continuous arterial spin labeling MRI. NeuroImage, 162, 384-397. https://doi.org/10.1016/j.neuroimage.2017.08.072

Journal Article Type Article
Acceptance Date Aug 24, 2017
Online Publication Date Sep 5, 2017
Publication Date Nov 15, 2017
Deposit Date Sep 8, 2020
Publicly Available Date Mar 10, 2021
Journal NeuroImage
Print ISSN 1053-8119
Electronic ISSN 1095-9572
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 162
Pages 384-397
DOI https://doi.org/10.1016/j.neuroimage.2017.08.072
Public URL https://nottingham-repository.worktribe.com/output/4889357
Publisher URL https://www.sciencedirect.com/science/article/abs/pii/S1053811917307103?via%3Dihub

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