Abstract #5234

Unified multi-modal characterization of microstructural parameters of brain tissue using diffusion MRI and multi-echo T2 data

Erick Jorge Canales-Rodríguez^1,2,3, Marco Pizzolato², Yasser Alemán-Gómez^4,5,6, Nicolas Kunz⁷, Caroline Pot^8,9, Jean-Philippe Thiran^1,2, and Alessandro Daducci^2,10

¹Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland, ²Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ³FIDMAG Germanes Hospitaláries, Barcelona, Spain, ⁴Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, ⁵Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, ⁶Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Lausanne, Switzerland, ⁷Centre d'Imagerie BioMédicale (CIBM)-AIT, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁸Department of Pathology and Immunology, Geneva University Hospital and University of Geneva, Geneva, Switzerland, ⁹Laboratories of Neuroimmunology, Division of Neurology and Neuroscience Research Center, Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland, ¹⁰Computer Science Department, University of Verona, Verona, Italy

In this study we propose a theoretical model to estimate different microstructure indices from diffusion MRI and multi-echo T2 (MET2) data. The proposed estimation framework takes into account the common and complementary information provided by both modalities. While the MET2 data allow us to model the myelin compartment, the diffusion data enable us to better characterize the intra-axonal and extra-axonal compartments. Results from numerical experiments support the hypothesis that the new unified estimation is more accurate than the alternative approach based on the individual sequential fitting of both image modalities. The performance was stable for noise levels commonly found in clinical protocols.

This abstract and the presentation materials are available to members only; a login is required.

Join Here