A Statistical Shape Model of Individual Fiber Tracts Extracted from Diffusion Tensor MRI

Diffusion Tensor MRI has become the preferred imaging modality to explore white matter structure and brain connectivity in vivo. Conventional region of interest analysis and voxel-based comparison does not make use of the geometric properties of fiber tracts. This paper explores shape modelling of major fiber bundles. We describe tracts, represented as clustered sets of curves of similar shape, by a shape prototype swept along a space trajectory. This approach can naturally describe white matter structures observed either as bundles dispersing towards the cortex or tracts defined as dense patterns of parallel fibers. Sets of streamline curves obtained from tractography are clustered, parametrized and aligned with a similarity transform. An average curve and eigenmodes of shape variation describe a compact statistical shape model. Reconstruction by sweeping the template along the trajectory results in a simplified model of a tract. Feasibility is demonstrated by modelling callosal and cortico-spinal fasciculi of two different subjects.