Multi-Compartment Model of Brain Tissues from T2 Relaxometry MRI Using Gamma Distribution

Sudhanya Chatterjee (1) , Olivier Commowick (1) , Onur Afacan (2) , Simon K Warfield (2) , Christian Barillot (1)

1 VisAGeS - Vision, Action et Gestion d'informations en Santé
2 CRL - Computational Radiology Laboratory [Boston]

The brain microstructure, especially myelinated axons and free fluids, may provide useful insight into brain neurodegen-erative diseases such as multiple sclerosis (MS). These may be distinguished based on their transverse relaxation times which can be measured using T 2 relaxometry MRI. However, due to physical limitations on achievable resolution, each voxel contains a combination of these tissues, rendering the estimation complex. We present a novel multi-compartment T 2 (MCT2) estimation based on variable projection, applicable to any MCT2 microstructure model. We derive this estimation for a three-gamma distribution model. We validate our framework on synthetic data and illustrate its potential on healthy volunteer and MS patient data.

Mots clés: brain; microstructure; T 2 relaxometry

Domaines: Imagerie médicale

Sudhanya Chatterjee, Olivier Commowick, Onur Afacan, Simon K Warfield, Christian Barillot. Multi-Compartment Model of Brain Tissues from T2 Relaxometry MRI Using Gamma Distribution. ISBI 2018 - IEEE International Symposium on Biomedical Imaging, Apr 2018, Washington DC, United States. pp.141-144, ⟨10.1109/ISBI.2018.8363541⟩. ⟨hal-01744852⟩