Volumetric and morphological analysis of the memory circuit in healthy ageing

海马体位于大脑的内侧颞叶，长期以来与人类的情景记忆有关，长期以来与几种神经精神疾病如阿尔茨海默病和精神分裂症有关。 此外，健康老龄化和海马体体积的整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错综复杂的子区域的组合，具有复杂的三维几何形状和空间关系。 此外，很少有人对包括海马体、内嗅皮层、穹窿和乳头体在内的整个记忆网络进行分析。 此外，虽然许多团体正在使用这些软件包作为一种手段来评估海马子域体积，有很少或没有知识的文献中关于海马子域体积的轨迹或神经解剖学的记忆网络通过健康的老龄化过程。 本研究提案的目标是使用强大的MRI图像采集和分割管道，通过健康老龄化过程绘制男性和女性海马体的体积和形态学轨迹。 我的小组最近发表了一个详细的MRI采集和手动分割协议，允许在3 T MRI扫描仪（大多数研究中心都有）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。 这些采集与详细的分割方案配合使用时，可以对角状氨（CA 1）、CA 2/3、CA 4/齿状回、分子层和下托进行稳健可靠的识别。 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，该提案将我们的手动分割与我的小组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，然后使用正在分析的主题集引导分割过程，以提供最终的一组准确分割水平，甚至在海马子场的水平。 研究设计如下。 我们将招募62名年龄在18岁至80岁之间的受试者。 将采集每名研究参与者的高分辨率T1和T2加权图像体积，并使用我的小组开发的图像分割软件自动分割。 将评估总体海马体积和形状的性别二态性和年龄相关趋势。 将相对于基于表面的总体平均值表示进行形状分析。 局部顶点向内和向外位移将用作感兴趣的度量，用于使用先前描述的分割流水线的扩展来评估形状。 这项工作的结果将是第一次全面分析的记忆网络，通过健康老龄化的过程中，并将提供一个基线的其他研究感兴趣的子领域和认知能力之间的关系。 作为我的研究团队的道德，我们不仅建议开发这些成像协议和自动生成的分割，而且还将我们所有的数据公开（就像我们之前的图谱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）。

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).