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

美法研究提案：海马层：在人体中使用 7 特斯拉的超高分辨率 MRI 进行高级计算解剖学

• 批准号: 1607835
• 负责人: Pierre-Francoi Van de Moortele
• 金额: $ 57.33万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1607835&HistoricalAwards=false
• 关键词: US; French; Research; Proposal; Hippocampal

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).

磁共振成像（MRI）在脑部疾病的评估中发挥着关键作用，它允许临床医生在体内观察大脑的变化。例如，在局灶性癫痫中，它可以检测引起癫痫发作的病变，随后可以对出现耐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，并且可以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。海马体的情况尤其如此，海马体是一种相对较小的大脑结构，经常与成人和青少年颞叶癫痫以及其他脑部疾病有关。事实上，海马体是由一组复杂的内部结构组成的，其典型大小低于传统MRI的分辨率。本项目旨在利用7特斯拉超高磁场下较高的信噪比，结合先进的数学建模技术，结合尖端的MRI采集技术，开发海马成像新技术。这种新方法将在颞叶癫痫患者中进行评估。期望充分利用其高分辨率结构MR图像，可以揭示目前在常规放射评估中未发现的脑病变。此外，通过对海马结构的前所未有的深入了解，这项研究将有助于开发新的患者分类和指导颞叶癫痫治疗选择的新理论基础。拟议的方法也有望提供关键信息，以促进我们对其他脑部疾病的理解，包括阿尔茨海默病和抑郁症，这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学。为了实现这一目标，研究人员将首先开发7特斯拉的MRI采集技术，以执行高分辨率和多对比度成像，包括新技术的发展，将促进这些先进方法在成人和青少年患者的临床环境中的使用。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MRI。这些技术将基于最近的数学进展，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，成人（美国）和青少年（法国）患者将接受7特斯拉核磁共振成像的研究。这应该能够证明已开发的技术在揭示常规手段无法检测到的病变方面的实用性。这将给局灶性癫痫患者带来重要的益处。在目前的项目之外，这些结果应该对海马体起关键作用的脑部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）正在资助一个伙伴项目。