Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis

Author:

Clark Kelly A.12ORCID,O'Donnell Carly M.12,Elliott Mark A.3,Tauhid Shahamat4,Dewey Blake E.5,Chu Renxin4,Khalil Samar4,Nair Govind6,Sati Pascal7,DuVal Anna5,Pellegrini Nicole5,Bar‐Or Amit89,Markowitz Clyde89,Schindler Matthew K.89ORCID,Zurawski Jonathan4,Calabresi Peter A.5ORCID,Reich Daniel S.10,Bakshi Rohit4ORCID,Shinohara Russell T.128ORCID,

Affiliation:

1. Penn Statistics in Imaging and Visualization Endeavor University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA

2. Department of Biostatistics, Epidemiology, and Informatics University of Pennsylvania Perelman School of Medicine Philadelphia Pennsylvania USA

3. Department of Radiology University of Pennsylvania Philadelphia Pennsylvania USA

4. Department of Neurology, Brigham and Women's Hospital Harvard Medical School Boston Massachusetts USA

5. Department of Neurology Johns Hopkins University School of Medicine Baltimore Maryland USA

6. Quantitative MRI Core Facility, National Institute of Neurological Disorders and Stroke National Institutes of Health Bethesda Maryland USA

7. Neuroimaging Program, Department of Neurology Cedars‐Sinai Medical Center Los Angeles California USA

8. Center for Neuroinflammation and Neurotherapeutics, Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA

9. Department of Neurology, Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA

10. Translational Neuroradiology Section National Institute of Neurological Disorders and Stroke National Institutes of Health Bethesda Maryland USA

Abstract

AbstractBackground and PurposeMulticenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image‐based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at four sites.MethodsImages were acquired on Siemens or Philips scanners at 3 Tesla. Automated white matter lesion detection and whole‐brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 magnetization‐prepared rapid acquisition gradient echo and T2 fluid‐attenuated inversion recovery lesions. Random‐effect and permutation‐based nonparametric modeling was performed to assess differences in estimated volumes within and across sites.ResultsRandom‐effect modeling demonstrated model assumption violations for most comparisons of interest. Nonparametric modeling indicated that site explained >50% of the variation for most estimated volumes. This expanded to >75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter‐ and intrasite differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact.ConclusionDifferences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating intersite differences show promise in reducing biases in multicenter studies of MS.

Funder

National Multiple Sclerosis Society

National Institute of Neurological Disorders and Stroke

National Institute of Mental Health

Publisher

Wiley

Subject

Neurology (clinical),Radiology, Nuclear Medicine and imaging

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