DTI based structural damage characterization for Disorders of Consciousness

MRI Diffusion Tensor Imaging (DTI) has been recently proposed as a highly discriminative measurement to detect structural damages in Disorders of Consciousness patients (Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) and Minimally Consciousness State (MCS)). In the DTI analysis, certain tensor features are often used as simplified scalar indices to represent these alterations. Those characteristics are mathematically and statistically more tractable than the full tensors. Nevertheless, most of these quantities are based on a tensor diffusivity estimation, the arithmetic average among the different strengths of the tensor orthogonal directions, which is supported on a symmetric linear relationship among the three directions, an unrealistic assumption for severely damaged brains. In this paper, we propose a new family of scalar quantities based on Generalized Ordered Weighted Aggregations (GOWA) to characterize morphological brain damages. The main idea is to perform a water diffusivity estimation in the damaged tissue by weighting and combining differently each tensor orthogonal strength. Using these new scalar quantities we constructed an affine invariant DTI tensor feature based on regional tissue histograms that outperforms state-of-the-art tensor based scalar representations for discrimination problems.