Evaluation of voxel-based morphometry for focal lesion detection in individuals

Voxel-based morphometry (VBM) is an automated statistical technique used to detect regional differences in tissue density and tissue amount based on spatially standardized structural magnetic resonance (MR) images. Developed initially to discern differences between groups of subjects, VBM is now being used to characterize structural abnormalities in individual brains. While VBM performance has been qualitatively assessed for this purpose, to date no quantitative validation study has been performed. This study evaluated several commonly used variants of VBM for detecting structural differences at the individual level by assessing their performance in MR images of 10 subjects with stable focal brain lesions. Results were quantitatively compared to expert tracings of the lesions, the current gold standard for lesion detection and delineation. Additionally, analyses using two sets of simulated lesion data were performed to examine the relative impact of the underlying processing steps on VBM results. Performance metrics revealed that (1) for this application, VBM had low sensitivity; (2) detection sensitivity was altered by model parameterization; (3) underperformance was due to the adverse influence of lesions on the preprocessing steps and to insufficient statistical power; and (4) VBM could not satisfactorily delineate the spatial extent of lesions, even in simulations that avoided preprocessing artifacts. In its current form, VBM is not a suitable stand-alone technique for detecting or spatially characterizing focal lesions.