brain NAVigation Lab


Brain microstructure

The diffusion Magnetic Resonance Imaging (dMRI) is sensitive to random movements of nuclear spins carried by particles such as water molecules. The diffusion process in the brain tissue is hindered by its complex architecture due to the broad variety of cellular structures. Microstructure properties can be inferred by fitting the dMRI signal using mathematical models involving different set of parameters. In-vivo microstructure imaging as enabled by the dMRI is a considerable, indispensable, and exciting challenge for shedding light on the biological structures and processes underneath the health and disease brain.


Boscolo Galazzo I., Brusini L., Akinci M., Cruciani F., Pitteri M., Ziccardi S., Bajrami A., Castellaro M., Salih A., Pizzini F. B., Jovicich J., Calabrese M. and Menegaz G.
“Unraveling the MRI-Based Microstructural Signatures Behind Primary Progressive and Relapsing–Remitting Multiple Sclerosis Phenotypes.”
Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine

Brusini L., Menegaz G. and Nilsson M.
“Monte Carlo Simulations of Water Exchange Through Myelin Wraps: Implications for Diffusion MRI.”
IEEE Transactions on Medical Imaging (Volume: 38, Issue: 6, June 2019)

Boscolo Galazzo I., Brusini L., Obertino S., Zucchelli M., Granziera C. and Menegaz G.
“On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke.”
Front. Neurosci., 21 February 2018, Sec. Brain Imaging Methods

Zucchelli M., Brusini L., Andrés Méndez C. and Menegaz G.
“Multi-Tensor MAPMRI: How to Estimate Microstructural Information from Crossing Fibers.”
In: Fuster, A., Ghosh, A., Kaden, E., Rathi, Y., Reisert, M. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham, 2016.

Zucchelli M., Brusini L., Andrés Méndez C., Daducci A., Granziera C. and Menegaz G.
“What lies beneath? Diffusion EAP-based study of brain tissue microstructure.”
Medical Image Analysis; 32:145-56, 2016