Streamline-Based Analysis: A novel framework for tractogram-driven streamline-wise statistical analysis

Motivation: Current statistical analysis in diffusion MRI has yet to fully leverage the specificity and wealth of information that the brain axonal pathways, reconstructed as streamlines, can provide. Goal(s): To develop the novel Streamline-Based Analysis (SBA) framework to enable streamline-wise statistical analysis and illustrate its application in detecting sex-related white matter differences. Approach: We define and use the similarity between the streamlines to identify the streamline neighbourhood and enhance sensitivity to optimise the detection of significant differences in streamline values in the statistical test. Results: The presented framework was found to be a sensitive method to detect streamline-based differences. Impact: The introduced SBA method offers an unprecedented streamline-wise specificity and an unexplored perspective for investigating brain differences, where the pathways of the streamlines effectively shape the insights gained from imaging data across different modalities.