Abstract
VBM is increasingly used in the study of neurodegeneration, and recently there has been interest in its potential as a biomarker. However, although it is largely "automated," VBM is rarely implemented consistently across studies, and changing user-specified options can alter the results in a way similar to the very biologic differences under investigation. This work uses data from patients with HD to demonstrate the effects of several user-specified VBM parameters and analyses: type and level of statistical correction, modulation, smoothing kernel size, adjustment for brain size, subgroup analysis, and software version. The results demonstrate that changing these options can alter results in a way similar to the biologic differences under investigation. If VBM is to be useful clinically or considered for use as a biomarker, there is a need for greater recognition of these issues and more uniformity in its application for the method to be both reproducible and valid.
Highlights
ObjectivesThis article aims to illustrate the above problem by using data from patients with HD, a neurodegenerative disease which has been investigated using VBM
AND PURPOSE: VBM is increasingly used in the study of neurodegeneration, and recently there has been interest in its potential as a biomarker
The results demonstrate that changing these options can alter results in a way similar to the biologic differences under investigation
Summary
This article aims to illustrate the above problem by using data from patients with HD, a neurodegenerative disease which has been investigated using VBM. The aims of the work were the following: 1) to illustrate that all users need to be aware of these caveats when interpreting results and 2) to show that a more uniform approach to VBM is vital if it is to be considered a robust and valid clinical tool and eventually meet criteria for a biomarker
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