BACKGROUND AND PURPOSE: Hydrocephalus is a severe pathologic condition in which WM damage is a major factor associated with poor outcomes. The goal of the study was to investigate tract-based WM connectivity and DTI measurements in children with hydrocephalus by using the probabilistic diffusion tractography method. MATERIALS AND METHODS: Twelve children with hydrocephalus and 16 age-matched controls were included in the study. Probabilistic diffusion tractography was conducted to generate tract-based connectivity distribution and DTI measures for the genu of the corpus callosum and the connectivity index. Tract-based summary measurements, including the connectivity index and DTI measures (fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity), were calculated and compared between the 2 study groups. RESULTS: Tract-based summary measurement showed a higher percentage of voxels with lower normalized connectivity index values in the WM tracts in children with hydrocephalus. In the genu of the corpus callosum, the left midsegment of the corticospinal tract, and the right midsegment of the corticospinal tract, the normalized connectivity index value in children with hydrocephalus was found to be significantly lower (P < .05, corrected). The tract-based DTI measures showed that the children with hydrocephalus had significantly higher mean diffusivity, axial diffusivity, and radial diffusivity in the genu of the corpus callosum, left midsegment of the corticospinal tract, and right midsegment of corticospinal tract and lower fractional anisotropy in the genu of the corpus callosum (P < .05, corrected). CONCLUSIONS: The analysis of WM connectivity showed that the probabilistic diffusion tractography method is a sensitive tool to detect the decreased continuity in WM tracts that are under the direct influence of mechanical distortion and increased intracranial pressure in hydrocephalus. This voxel-based connectivity method can provide quantitative information complementary to the standard DTI summary measures.