Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

At the typical spatial resolution of MRI in human brain, approximately 60–90% voxels contain multiple fiber populations. Quantifying microstructural properties distinct populations within a voxel is therefore challenging but necessary. While progress has been made for diffusion and T1-relaxation properties, how to resolve intra-voxel T2 heterogeneity remains an open question. Here novel framework, named COMMIT-T2, proposed that uses tractography-based regularization with diffusion-relaxometry data estimate intra-axonal values voxel. Unlike previously-proposed voxel-based estimation methods, which (when applied white matter) implicitly assume just one bundle or same all bundles voxel, COMMIT-T2 can recover specific each unique population passing through In this approach, number recovered not determined by model parameters set priori, rather tractography-reconstructed streamlines Proof-of-concept provided silico vivo, including demonstration tract-specific profiles be even three-way crossing corpus callosum, arcuate fasciculus, corticospinal tract. We demonstrate favourable performance compared voxelwise approaches mapping exploiting diffusion, direction-averaged method AMICO-T2, new extension Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework.