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

描述（由申请人提供）：内侧颞叶（MTL）是多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的结构变化位点。组成MTL的不同亚区，包括海马体的不同亚区，涉及不同的记忆子系统，并显示在正常衰老和AD中受到不同的影响。因此，使用体内神经成像可靠有效地检测这些亚区域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。这一过程将为人类大脑中MTL的功能和结构以及它在正常衰老中如何受到影响提供关键的见解。这也是为阿尔茨海默病的早期诊断和治疗评估寻找敏感、非侵入性生物标志物的重要一步。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和周围结构视为一个单一的实体。然而，磁共振数据采集技术的实质性发展已经开始产生图像，以前所未有的细节水平显示MTL的解剖特征，为MTL单个亚区域的精细功能和形态学分析提供基础。在子场水平上对MTL的MRI研究目前尚未广泛进行。这是因为他们需要结合深度核磁共振技术、神经解剖学专业知识，以及只有在少数专业地点才能获得的人员资源。为了使MTL在子场水平的MRI研究更广泛地获得，本项目的总体目标是开发和验证一套广泛适用的计算工具，以从活体MRI图像中自动分割大量MTL子区域。具体来说，考虑到MRI的极端多功能性和MTL成像缺乏标准采集协议，我们将构建能够健壮地分析各种图像分辨率和组织对比度扫描的工具。为此，我们的目标是：(1)在超高分辨率MRI扫描中使用手动描绘来推导计算模型，预测MTL子区域的相对位置和形状；(2)基于这些模型和MRI成像过程模型，开发并验证用于超高分辨率MRI扫描中全自动MTL子区域分割的贝叶斯框架。(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得的低分辨率图像，通过明确地考虑部分体积效应，其中几个结构有助于形成单个体素内的强度。为了向科学界传播已开发的技术和地图集，我们计划将它们集成到一个开源包中，并将其作为FreeSurfer环境的一部分免费提供。

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.