Volumetric and morphological analysis of the memory circuit in healthy ageing

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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).