Abstract
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.
Original language | English |
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Article number | 118236 |
Number of pages | 8 |
Journal | NeuroImage |
Volume | 238 |
Early online date | Jun 2021 |
DOIs | |
Publication status | Published - Sept 2021 |
Bibliographical note
Funding Information:We thank the European Union COST agency (through COST Action BM1103) for sponsorship of the workshops that have stimulated the discussion from which this paper has emerged. MC and FKM have received support from the Engineering and Physical Sciences Research Council UK (EP/P012361/1). FKM is supported by the Beacon of Excellence in Precision Imaging, University of Nottingham. MJPvO is supported by Horizon2020 (project: CDS-QUAMRI, Project number 634541) and the Netherlands organization for Scientific Research Grant (Award Number 016.160.351). XG is supported by the National Institute for Health Research University College London Hospitals Biomedical Research center. The data used in this work for Fig. 2 were obtained from UK Biobank Resource under Application Number 43172. We are grateful to UK Biobank for making the data available, and to all UK Biobank study participants, who generously donated their time to make this resource possible.
Funding Information:
We thank the European Union COST agency (through COST Action BM1103) for sponsorship of the workshops that have stimulated the discussion from which this paper has emerged. MC and FKM have received support from the Engineering and Physical Sciences Research Council UK (EP/P012361/1). FKM is supported by the Beacon of Excellence in Precision Imaging, University of Nottingham. MJPvO is supported by Horizon2020 (project: CDS-QUAMRI, Project number 634541) and the Netherlands organization for Scientific Research Grant (Award Number 016.160.351). XG is supported by the National Institute for Health Research University College London Hospitals Biomedical Research center.
Publisher Copyright:
© 2021