Partial volume correction in arterial spin labeling perfusion MRI: A method to disentangle anatomy from physiology or an analysis step too far?

NeuroImage, vol. 238, pp. 118236

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.

Authors 7

1. Michael A. Chappell corresponding

   University of Nottingham · University of Oxford · Wellcome Centre for Integrative Neuroimaging · Queen's Medical Centre · Nottingham Biomedical Research Centre

   Affiliation as printed

   Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, UK; Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK; Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK. Electronic address: michael.chappell@nottingham.ac.uk

   Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK

   Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK

   Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, UK

   Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, UK

2. Flora A. Kennedy McConnell

   University of Nottingham · Queen's Medical Centre · Nottingham Biomedical Research Centre

   Affiliation as printed

   Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, UK; Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK

   Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, UK

   Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK

   Sir Peter Mansfield Imaging Center, School of Medicine, University of Nottingham, Nottingham, UK

3. Xavier Golay

   UCL Queen Square Institute of Neurology · University College London

   Affiliation as printed

   Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK

4. Matthias Günther

   University of Bremen · Mediri (Germany) · Fraunhofer Institute for Digital Medicine

   Affiliation as printed

   Fraunhofer MEVIS, Bremen, Germany; University Bremen, Bremen, Germany; mediri GmbH, Heidelberg, Germany

   Fraunhofer MEVIS, Bremen, Germany

   University Bremen, Bremen, Germany

   mediri GmbH, Heidelberg, Germany

5. Juan Antonio Hernandez-Tamames

   Erasmus MC

   Affiliation as printed

   Radiology and Nuclear Medicine Department, Erasmus MC, Rotterdam, the Netherlands

6. Matthias J.P. van Osch Aachen C.J. Gorter Center for High Field MRI Radiology Department

   Leiden University Medical Center

   Affiliation as printed

   C.J. Gorter Center for High Field MRI, Radiology Department, Leiden University Medical Center, Leiden, the Netherlands

7. Iris Asllani

   Rochester Institute of Technology · University of Sussex

   Affiliation as printed

   Clinical Imaging Sciences Centre, Department of Neuroscience, University of Sussex, UK; Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, United States

   Clinical Imaging Sciences Centre, Department of Neuroscience, University of Sussex, UK

   Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, United States