Magnetic resonance imaging (MRI) plays a pivotal role in the evaluation of brain disorders by allowing clinicians to visualize brain alterations in vivo. For instance in focal epilepsies, it allows to detect lesions that cause seizures, which can subsequently be treated surgically in patients who present drug-resistant epilepsy. This ability to unveil lesions is crucial to achieve favorable surgical outcome and may allow limiting or avoiding invasive explorations with intracerebral electrodes. However, standard MRI techniques have a limited spatial resolution, which results in limited sensitivity to detect subtle structural alterations. This is particularly true in the case of the hippocampus, a relatively small cerebral structure frequently involved in adult and adolescent temporal epilepsy, as well as in other brain disorders. Indeed, the hippocampus is composed of a complex set of internal structures whose typical size is below the resolution of conventional MRI. This project aims to develop new techniques to image the hippocampus, by combining cutting edge MRI acquisition techniques, taking advantage of higher signal to noise ratio at a ultra high magnetic field of 7 Tesla, with advanced mathematical modeling techniques. This new approach will be evaluated in patients with temporal lobe epilepsy. It is expected that exploiting to their full extent very high-resolution structural MR images will allow unveiling cerebral lesions currently undetected in conventional radiological evaluation. Furthermore, by providing unprecedented insight into hippocampal structures, this research will help developing new patient classification and new rationale to guide therapeutic choices in temporal lobe epilepsy. The proposed approach is also expected to provide critical information to advance our understanding of other brain disorders, including Alzheimer's disease and depression, which are major public health concerns. Ultimately, this will pave the way to new biomarkers for diagnosis and prognosis, and help developing new treatments.
The overall goal of this project is to develop a coherent mathematical framework for computational anatomy of the internal structures of the hippocampus based on cutting edge MRI acquisition techniques at 7 Tesla. The project introduces a new approach to move computational anatomy beyond morphometry by integrating both volumetric MRI data and shape into a single framework. To achieve this goal, the researchers will first develop MRI acquisition techniques at 7 Tesla to perform high-resolution and multi-contrast imaging, including new technical developments that will facilitate the use of these advanced methods in clinical settings, for adults and teenagers patients. The second part of the project will be devoted to the development of advanced computational techniques to model multi-contrast 7 Tesla MRI. Such techniques will be based on recent mathematical advances allowing to model multi-scale geometric deformations and to combine shape and intensity information in a coherent framework. Finally, the developed approaches will be applied to 7T MRI acquisition of patients with temporal lobe epilepsy. To that purpose, adult (in the US) and teenagers (in France) patients will be studied with 7 Tesla MRI. This should enable to demonstrate the utility of the developed techniques to unveil lesions that are undetectable by conventional means. This should result in important benefits for patients with focal epilepsy. Beyond the present project, the results should have an important impact on the diagnosis and treatment of brain conditions in which the hippocampus plays a key role, including Alzheimer's disease, depression and schizophrenia. A companion project is being funded by the French National Research Agency (ANR).
