White matter 'potholes' in early-onset schizophrenia: a new approach to evaluate white matter microstructure using diffusion tensor imaging.

There is considerable evidence implicating white matter abnormalities in the pathophysiology of schizophrenia. Many of the recent studies examining white matter have utilized diffusion tensor imaging (DTI) using either region of interest (ROI) or voxel-based approaches. Both voxel-based and ROI approaches are based on the assumption that the abnormalities in white matter overlap spatially. However, this is an assumption that has not been tested, and it is possible that aberrations in white matter occur in non-overlapping regions. In order to test for the presence of non-overlapping regions of aberrant white matter, we developed a novel image processing technique that evaluates for white matter 'potholes,' referring to within-subject clusters of white matter voxels that show a significant reduction in fractional anisotropy. We applied this algorithm to a group of children and adolescents with schizophrenia compared to controls and found an increased number of 'potholes' in the patient group. These results suggest that voxel-based and ROI approaches may be missing some white matter differences that do not overlap spatially. This algorithm may be also be well suited to detect white matter abnormalities in disorders such as substance abuse, head trauma, or specific neurological conditions affecting white matter.