Automated Segmentation of Subregions of the Medial Temporal Lobe in in vivo MRI

描述(申请人提供)：内侧颞叶(MTL)是各种记忆功能的必要组成部分，也是衰老、阿尔茨海默病(AD)、精神分裂症和其他疾病结构变化的部位。构成MTL的不同亚区，包括海马区的不同亚区，与不同的记忆子系统有关，并被证明在正常衰老和AD中受到不同的影响。因此，使用体内神经成像技术可靠而有效地检测这些亚区的能力对于基础神经科学和临床研究都具有巨大的潜在价值。这样的程序将提供对活着的人脑中MTL的功能和结构的关键见解，以及它在正常衰老中是如何受到影响的。这也是寻求敏感的、非侵入性的生物标志物用于AD的早期诊断和治疗评估的重要一步。传统上，典型MRI扫描的有限分辨率一直是MTL成像研究的主要障碍，迫使研究人员将海马体及其周围结构视为一个单一实体。然而，磁共振数据采集技术的实质性发展已经开始产生以前所未有的细节水平显示MTL解剖特征的图像，为对MTL的各个亚区进行精细的功能和形态分析提供了基础。目前在子场水平上对MTL的MRI研究并不广泛。这是因为他们需要深厚的MRI知识、神经解剖学专业知识和仅在选定的几个专业地点提供的人力资源的组合。为了使子场水平的MTL的MRI研究更容易获得，该项目的总体目标是开发和验证一套广泛适用的计算工具集，以从活体MRI图像中自动分割大量MTL亚区。具体地说，鉴于MRI的极端多功能性，以及缺乏用于成像MTL的标准采集协议，我们将构建能够强有力地分析各种图像分辨率和组织对比度的扫描工具。为此，我们的目标是(1)在超高分辨率MRI扫描中使用手动勾画来推导出预测MTL亚区相对位置和形状的计算模型，(2)基于这些模型和MRI成像过程的模型，开发和验证用于超高分辨率MRI扫描中全自动MTL区域分割的贝叶斯框架，以及(3)开发和验证这样一个框架，用于在更广泛使用的系统上获取的较低分辨率图像，通过明确考虑部分体积效应，其中几个结构形成单个体素内的强度。为了向科学界传播开发的技术和地图集，我们计划将它们整合到一个开放源码包中，我们将作为免费冲浪环境的一部分免费提供该包。 与公共卫生相关：通过活体磁共振成像可靠地测量小内侧颞叶(MTL)亚结构的细微退行性变化的能力，将是迈向阿尔茨海默病早期诊断和分期以及监测治疗干预的重要一步。这样的程序还可以提供前所未有的洞察力，了解活着的人脑中伴随着正常衰老的MTL结构的变化，这是一个关键的临床和神经科学目标，因为MTL是已知在人类记忆系统中至关重要的大脑区域。

DESCRIPTION (provided by applicant): The medial temporal lobe (MTL) is a necessary component in a variety of memory functions, as well as the locus of structural change in aging, Alzheimer's disease (AD), schizophrenia, and other conditions. The distinct subregions composing the MTL, including various subfields of the hippocampus, have been implicated in different memory subsystems, and shown to be differentially affected in normal aging and AD. The ability to reliably and efficiently detect these subregions using in vivo neuroimaging would therefore be of great potential value for both basic neuroscience and clinical research. Such a procedure will provide critical insights into the function and structure of the MTL in the living human brain, and how it is affected in normal aging. It is also an important step in the quest for sensitive, non-invasive biomarkers for early diagnosis and treatment evaluation in AD. The limited resolution of typical MRI scans has traditionally been a major hindrance in imaging studies of the MTL, forcing investigators to treat the hippocampus and surrounding structures as a single entity. Substantial developments in MR data acquisition technology, however, have started to yield images that show anatomical features of the MTL at an unprecedented level of detail, providing the basis for fine-scaled functional and morphological analyses of individual subregions of the MTL. MRI studies of the MTL at the subfield level are currently not widely performed. This is because they require a combination of deep MRI know-how, neuroanatomical expertise, and staffing resources available only at a select few specialized sites. In order to make MRI studies of the MTL at the subfield level more widely accessible, the overall goal of this project is to develop and validate a broadly applicable set of computational tools to automatically segment a multitude of MTL subregions from in vivo MRI images. Specifically, given the extreme versatility of MRI and the lack of standard acquisition protocols for imaging the MTL, we will build tools that can robustly analyze scans of various image resolutions and tissue contrasts. Towards this end, we aim to (1) use manual delineations in ultra-high resolution MRI scans to derive computational models that make predictions about the relative position and shape of MTL subregions, (2) based on these models and on a model of the MRI imaging process, develop and validate a Bayesian framework for fully-automated MTL subregion segmentation in ultra-high resolution MRI scans, and (3) develop and validate such a framework for lower resolution images acquired on systems in more widespread use, by explicitly accounting for the partial volume effect where several structures contribute to form the intensity within a single voxel. In order to disseminate the developed techniques and atlases to the scientific community, we plan to integrate them into an open source package that we will make freely available as part of the FreeSurfer environment. PUBLIC HEALTH RELEVANCE: The ability to reliably measure subtle degenerative changes in small medial temporal lobe (MTL) substructures through in vivo MRI would be an important step towards early diagnosis and staging of Alzheimer's disease, and towards monitoring therapeutic interventions. Such a procedure could also provide unprecedented insights into changes in the MTL structure in the living human brain that accompany normal aging, a crucial clinical and neuroscientific objective as the MTL is a brain region known to be critical in the human memory system.