US-French Research Proposal: Hippocampal Layers: Advanced Ccomputational Anatomy Using Very High Resolution MRI at 7 Tesla in Humans

磁共振成像(MRI)使临床医生能够在活体内可视化大脑的变化，在评估大脑疾病方面发挥着关键作用。例如，在局灶性癫痫中，它允许检测导致癫痫发作的病变，随后可以对出现抗药性癫痫的患者进行手术治疗。这种揭示病变的能力对于获得良好的手术结果至关重要，并可能允许限制或避免使用脑内电极进行侵入性探查。然而，标准的MRI技术具有有限的空间分辨率，这导致检测细微结构变化的灵敏度有限。在海马体的情况下尤其如此，海马体是一个相对较小的大脑结构，经常涉及成人和青少年的颞叶癫痫，以及其他大脑疾病。事实上，海马体由一组复杂的内部结构组成，其典型大小低于传统核磁共振的分辨率。该项目旨在开发新的海马区成像技术，将尖端的MRI采集技术与先进的数学建模技术相结合，利用7特斯拉超高磁场下的较高信噪比。这一新方法将在颞叶癫痫患者中进行评估。预计充分利用其非常高分辨率的结构磁共振图像将能够揭示目前在常规放射学评估中未发现的脑部病变。此外，通过提供对海马区结构的前所未有的见解，这项研究将有助于开发新的患者分类和新的理论基础，以指导颞叶癫痫的治疗选择。预计拟议的方法还将提供关键信息，以促进我们对其他大脑疾病的了解，包括阿尔茨海默病和抑郁症，这些都是主要的公共卫生问题。最终，这将为诊断和预后的新生物标志物铺平道路，并有助于开发新的治疗方法。该项目的总体目标是基于7特斯拉的尖端MRI采集技术，为海马体内部结构的计算解剖开发一个连贯的数学框架。该项目引入了一种新的方法，通过将体积MRI数据和形状集成到一个框架中，将计算解剖学超越形态测量。为了实现这一目标，研究人员将首先在7特斯拉开发MRI采集技术，以执行高分辨率和多对比度成像，包括新的技术开发，将促进在成人和青少年患者的临床环境中使用这些先进方法。该项目的第二部分将致力于开发先进的计算技术来模拟多对比度7特斯拉磁共振成像。这种技术将以最近的数学进步为基础，允许对多尺度几何变形进行建模，并将形状和强度信息结合在一个连贯的框架中。最后，将所开发的方法应用于颞叶癫痫患者的7T MRI采集。为此，将对成年(美国)和青少年(法国)患者进行7特斯拉核磁共振研究。这应该能够证明所开发的技术的实用性，以揭示用传统方法无法检测到的病变。这应该会给局灶性癫痫患者带来重要的好处。除了目前的项目，这些结果应该会对海马体起关键作用的大脑疾病的诊断和治疗产生重要影响，包括阿尔茨海默病、抑郁症和精神分裂症。法国国家研究机构(ANR)正在资助一个配套项目。

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).