Identification of Gadolinium contrast enhanced regions in MS lesions using brain tissue microstructure information obtained from diffusion and T2 relaxometry MRI

Sudhanya Chatterjee 1 Olivier Commowick 1 Onur Afacan 2 Simon Warfield 2 Christian Barillot 1
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U1228, Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 CRL - Computational Radiology Laboratory [Boston]
Abstract : A multiple sclerosis (MS) lesion at an early stage undergoes active blood brain barrier (BBB) breakdown. Identifying MS lesions in a patient which are undergoing active BBB breakdown is of critical importance for MS burden evaluation and treatment planning. However in non-contrast enhanced structural magnetic resonance imaging (MRI) the regions of the lesion undergoing active BBB breakdown cannot be distinguished from the other parts of the lesion. Hence gadolinium (Gd) contrast enhanced T1-weighted MR images are used for this task. However some side effects of Gd injection into patients have been increasingly reported recently. The BBB breakdown is reflected by the condition of tissue microstructure such as increased inflammation, presence of higher extra-cellular matter and debris. We thus propose a framework to predict enhancing regions in MS lesions using tissue microstructure information derived from T2 relaxometry and diffusion MRI (dMRI) multi-compartment models. We show that combination of the dMRI and T2 relaxometry microstructure information can distinguish the Gd enhancing lesion regions from the other regions in MS lesions.
Keywords : Diffusion MRI Multiple sclerosis Brain Microstructure T2 relaxometry
Type de document :
Communication dans un congrès
21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), Sep 2018, Grenade, Spain. Springer, Lecture Notes in Computer Science, 11072, pp.63-71, Medical Image Computing and Computer Assisted Intervention – MICCAI 2018. 〈10.1007/978-3-030-00931-1_8〉
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https://hal.archives-ouvertes.fr/hal-01830532
Contributeur : Sudhanya Chatterjee <>
Soumis le : jeudi 5 juillet 2018 - 10:31:17
Dernière modification le : jeudi 15 novembre 2018 - 11:59:00

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Sudhanya Chatterjee, Olivier Commowick, Onur Afacan, Simon Warfield, Christian Barillot. Identification of Gadolinium contrast enhanced regions in MS lesions using brain tissue microstructure information obtained from diffusion and T2 relaxometry MRI. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), Sep 2018, Grenade, Spain. Springer, Lecture Notes in Computer Science, 11072, pp.63-71, Medical Image Computing and Computer Assisted Intervention – MICCAI 2018. 〈10.1007/978-3-030-00931-1_8〉. 〈hal-01830532〉

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