Prof. Aviv Mezer | Identifying white-matter pathways using quantitative MRI

Diffusion MRI tractography algorithms are essential for reconstructing major long-range white-matter projections in the living human brain. However, there are still considerable challenges in achieving meaningful usage of these algorithms. Particularly, the crossing and mixture of white-matter fibers add ambiguity to the estimation of local fiber orientation from the diffusion MRI signal. Hence, the white-matter reconstructions of different tractography algorithms depend on the underlying assumptions made to overcome this ambiguity. It has been argued that only additional, non-diffusion structural information can solve the current limiting uncertainty. A challenging example is the optic radiation (OR) that connects the thalamus and the primary visual cortex. I will show how OR tractography can be optimized using quantitative MRI information. Based on histology, I propose that myelin-sensitive T1 values along the OR should remain consistently low compared to adjacent white matter. I will show that complementary information from the T1 map allows for increasing the specificity of the reconstructed OR tract by eliminating falsely identified projections. This T1 filtering outperforms other, diffusion-based tractography filters. Next, I will show how this integrative approach can be extended to identify pathways such as the vertical occipital fasciculus (VOF) and the superior longitudinal fasciculus (SLF). Finally, I will discuss a framework for characterizing the conductivity properties of white-matter tracts by combining diffusion MRI with quantitative MRI properties along the reconstructed tracts.

Poster