Novel subject-specific method of visualising group differences from multiple DTI metrics without averaging

Averaging is commonly used for data reduction/aggregation to summarise such high-dimensional data, resulting in information loss. However, individual variability makes group-wise comparisons difficult without data reduction/aggregation. To address these issues, we developed a novel technique that integrates diffusion tensor (DTI) metrics along the whole volumes of the fibre bundle using a mesh-fitting technique. Using the right Corticospinal Tract (rCST) as an example, we demonstrate the utility of the method in detecting differences in DTI metrics of contact-sports and non-contact-sports athletes.