COMMITpro: accurate modeling of diffuse axonal fiber degeneration using the Discrete Cosine Transform

Motivation: Current tractography quantification methods, though precise, struggle with accuracy in brains with white-matter damage due to altered microstructural consistency. Goal(s): To overcome the constraint of constancy along streamlines' trajectories, as it could potentially introduce biases in the estimation of quantitative measures. Approach: We extended the Convex Optimization Modeling for Microstructure Informed Tractography (COMMIT) framework to enable the possibility of describing possible signal variations along the tracts due e.g. to Wallerian degeneration, by means of the Discrete Cosine Transform. Results: The proposed method is sensible to variations along the bundles' trajectories, as it can assess signal profiles that follow different degradation patterns. Impact: COMMITpro enables accurate reconstruction of microstructural features in both healthy and damaged brain pathways, offering valuable insights into brain diseases and their progression by identifying various types of fiber pathway damage.