Volumetric and morphological analysis of the memory circuit in healthy ageing

健康衰老过程中记忆回路的体积和形态分析

• 批准号: RGPIN-2014-04034
• 负责人: Chakravarty, Mallar
• 金额: $ 2.26万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=647062
• 关键词: Volumetric; morphological; analysis; memory; circuit

The hippocampus is located in the medial temporal of the brain and has long been associated with episodic memory in humans and has long been associated with several neuropsychiatric disorders such as Alzheimer's disease and schizophrenia. Further, there is a well-known relationship between healthy ageing and the overall decline in volume of the hippocampus. In modern magnetic resonance imaging (MRI) studies, the hippocampus is typically treated as a single homogeneous structure with uniform function. However, the hippocampus is truly the combination of several intricately patterned subfields, with complex three-dimensional geometry and inter-spatial relationships. Further, there are very few analyses of the entire memory network that include the hippocampus, entorhinal cortex, the fornix, and mamillary bodies. Further, although many groups are using these software packages as a means to assess hippocampal subfield volume, there is little to no knowledge in the literature regarding the trajectories of hippocampal subfield volumes or the neuroanatomy of the memory network through the course of healthy ageing. The goal of this research proposal is to map the volumetric and morphometric trajectories of the hippocampus in males and females through the course of healthy ageing using a robust MRI image acquisition and segmentation pipeline.* My group has recently published a detailed MRI acquisition and manual segmentation protocol that allows for T1- and T2-weighted high-resolution scanning (300 micron isotropic voxel dimensions) of the entire brain on a 3T MRI scanner (available to most research centres) that we have paired with a detailed manual segmentation protocol. These acquisitions, when paired with a detailed segmentation protocol, allows for the robust and reliable identification of the cornu ammonus (CA1), CA2/3, CA4/Dentate Gyrus, the molecular layers, and the subiculum. Despite it's robustness, the manual segmentation protocol is time consuming even for the most skilled manual rater. Thus, this proposal will pair our manual segmentations with a sophisticated image processing pipeline, developed in my group, that uses a small number of manually labeled imaged as inputs and then bootstraps the segmentation process using the subject set being analyzed to provide a final set of accurate segmentation level, even at the level of the hippocampal subfields. * The study design will be as follows. We will recruit 62 subjects between the ages of 18 and 80. High-resolution T1- and T2-weighted image volumes will be acquired for each study participant and automatically segmented using the image segmentation software developed in my group. Sexually dimorphic and age related tends in overall hippocampal volume and shape will be assessed. Shape analysis will be carried out relative to a surface-based population mean representation. Local vertex-wise inward and outward displacements will be used as the metric of interest for assessing shape using an extension of the segmentation pipeline previously described. The result of this work will be the first comprehensive analysis of the memory network through the course healthy ageing and will provide a baseline for other studies that are interested in the relationship between the subfields and cognitive abilities. As is the ethic of my research team, we propose not only to develop these imaging protocols and automatically generated segmentations, but to also make all our data publicly available (as we have done with our previous atlas work and algorithmic work; see http://imaging-genetics.camh.ca/Hippocampus and https://github.com/pipitone/MAGeTbrain respectively).

海马体位于大脑内侧颞叶，长期以来一直与人类的情景记忆有关，并与阿尔茨海默病和精神分裂症等几种神经精神疾病有关。此外，在健康衰老和海马体体积总体下降之间存在着众所周知的关系。在现代磁共振成像（MRI）研究中，海马体通常被视为具有统一功能的单一均匀结构。然而，海马体实际上是几个复杂模式子区域的组合，具有复杂的三维几何和空间间关系。此外，对包括海马体、内嗅皮质、穹窿和乳状体在内的整个记忆网络的分析很少。此外，尽管许多研究小组正在使用这些软件包作为评估海马体子区体积的一种手段，但在文献中，关于海马体子区体积的轨迹或记忆网络在健康衰老过程中的神经解剖学知识很少或根本没有。本研究计划的目标是利用强大的MRI图像采集和分割管道，绘制男性和女性在健康衰老过程中海马体的体积和形态轨迹。*我的团队最近发表了一份详细的MRI采集和手动分割协议，该协议允许在3T MRI扫描仪（大多数研究中心都可以使用）上对整个大脑进行T1和t2加权高分辨率扫描（300微米各向同性体素尺寸），我们已经与详细的手动分割协议配对。这些获取，当与详细的分割方案配对时，允许对角状脑（CA1）， CA2/3， CA4/齿状回，分子层和下骨进行稳健和可靠的鉴定。尽管它的鲁棒性，手动分割协议是耗时的，即使是最熟练的手动评分。因此，本建议将我们的手动分割与我的团队开发的复杂图像处理管道配对，该管道使用少量手动标记的图像作为输入，然后使用被分析的主题集引导分割过程，以提供最终的精确分割水平集，甚至在海马体子场的水平上。*研究设计如下：我们将招募62名年龄在18岁到80岁之间的受试者。将为每个研究参与者获取高分辨率T1和t2加权图像体积，并使用我小组开发的图像分割软件自动分割。评估海马总体体积和形状的性别二型性和年龄相关趋势。形状分析将相对于基于表面的人口平均表示进行。局部顶点向内和向外的位移将被用作使用前面描述的分割管道的扩展来评估形状的度量。这项工作的结果将是通过健康老龄化课程对记忆网络的第一次全面分析，并将为其他对子领域与认知能力之间关系感兴趣的研究提供基线。作为我的研究团队的道德规范，我们不仅建议开发这些成像协议和自动生成的分割，而且还建议将我们所有的数据公开可用（就像我们之前的地图集工作和算法工作一样；分别参见http://imaging-genetics.camh.ca/Hippocampus和https://github.com/pipitone/MAGeTbrain）。