Evaluation of voxel-based group-level analysis of diffusion tensor images using simulated brain lesions

We simulated brain lesions in mean diffusivity (MD) and fractional anisotropy (FA) images of healthy subjects to evaluate the performance of voxel-based analysis (VBA) with SPM2. We increased MD and decreased FA, simulating the most typical abnormalities in brain pathologies, in the superior longitudinal fasciculus (SLF), corticospinal tract (CST), and corpus callosum (CC). Lesion sizes varied from 10 to 400 voxels (10.5 mm3 each) and intensity changes from 10 to 100%. The VBA contained eddy current correction, spatial normalization, smoothing, and statistical analysis.The preprocessing steps changed the intensities of MD and FA lesions from the original values, and many lesions remained undetected. The detection thresholds varied between the three brain areas, and between MD and FA images. Although spatial smoothing often improved the sensitivity, it also markedly enlarged the estimated lesion sizes.Since conventional VBA preprocessing significantly affected the outcome and sensitivity of the method itself, the impact of analysis steps should be verified and considered before interpreting the findings. Our results provide insight into the sizes and intensity changes of lesions that can be detected with VBA applied to diffusion tensor imaging (DTI) data.

► VBA preprocessing steps affect considerably the analysis outcome.
► Lesions below certain thresholds for intensity and extent are not detected.
► Detection thresholds vary between the brain areas, and for MD and FA maps.
► Spatial smoothing has a very strong effect on thresholds and estimated lesion sizes.
► Inter-subject variation in lesion area affects the detection sensitivity as well.