A sensitivity analysis of q-space indices with respect to changes in axonal diameter, dispersion and tissue composition

• Published in: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) pp. 1241 - 1244
• Main Authors: Fick, R. H. J., Pizzolato, M., Wassermann, D., Zucchelli, M., Menegaz, G., Deriche, R.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.04.2016
• Subjects: Axonal Diameter; Axonal Dispersion; Brain; Diffusion; Diffusion MRI; Diffusion tensor imaging; Dispersion; Indexes; Integrated circuits; MAP-MRI; Markers; Microstructure; NODDI; Pathology; q-space Indices; Scalars; Sensitivity; Sensitivity analysis; Simulation; Tensile stress
• DOI: 10.1109/ISBI.2016.7493491

In Diffusion MRI, q-space indices are scalar quantities that describe properties of the ensemble average propagator (EAP). Their values are often linked to the axonal diameter - assuming that the diffusion signal originates from inside an ensemble of parallel cylinders. However, histological studies show that these assumptions are incorrect, and axonal tissue is often dispersed with various tissue compositions. Direct interpretation of these q-space indices in terms of tissue change is therefore impossible, and we must treat them as scalars that only give non-specific contrast - just as DTI indices. In this work, we analyze the sensitivity of q-space indices to tissue structure changes by simulating axonal tissue with changing axonal diameter, dispersion and tissue compositions. Using human connectome project data, we then predict which indices are most sensitive to tissue changes in the brain. We show that, in both multi-shell and single-shell (DTI) data, q-space indices have higher sensitivity to tissue changes than DTI indices in large parts of the brain. Based on these results, it may be interesting to revisit older DTI studies using q-space indices as markers for pathology.