We present new quantitative diffusion-tensor imaging (DTI) tractography-based metrics for assessing cerebral white matter integrity. These metrics extend prior work in this area. Tractography models of cerebral white matter were produced from each subject's DTI data. The models are a set of curves (e.g., "streamtubes") derived from DTI data that represent the underlying topography of the cerebral white matter. Nine metrics were calculated in whole brain tractography models and in three "tracts-of-interest" (TOI): transcallosal fibers, and the left and right cingulum bundles. The metrics included the number of streamtubes and several metrics based on the summed length of streamtubes in including some that were weighted by scalar anisotropy metrics and normalized for estimated intracranial volume. We then tested whether patients with subcortical ischemic vascular disease (i.e., vascular cognitive impairment or VCI) vs. healthy controls (HC) differed on the metrics. The metrics were significantly lower in the VCI group in whole brain and in transcallosal TOI but not in the left or right cingulum bundles. The metrics correlated significantly with cognitive functions known to be impacted by white matter abnormalities (e.g., processing speed) but not with those more impacted by cortical disease (e.g., naming). These new metrics help bridge the gap between DTI tractography and scalar analytical methods and provide a potential means for examining group differences in white matter integrity in specific tracts-of-interest.

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