Amygdalar atrophy in symptomatic Alzheimer's disease based on diffeomorphometry: the BIOCARD cohort

Abstract

This paper examines the diffeomorphometry of MRI derived structural markers for the amygdala, in subjects with symptomatic Alzheimer’s disease (AD). Using linear mixed-effects models we show differences between those with symptomatic AD and controls. Based on template centered population analysis, the distribution of statistically significant change is seen in both the volume and shape of the amygdala in subjects with symptomatic AD compared to controls. We find that high-dimensional vertex based markers are statistically more significantly discriminating (p<.00001) than lower-dimensional markers and volumes, consistent with comparable findings in presymptomatic Alzheimer’s disease. Using a high-field 7T atlas, significant atrophy was found to be centered in the basomedial and basolateral subregions, with no evidence of centromedial involvement.

Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer's disease

“…According to our vertex-based shape analysis, we observed significant, regionally specific, surface area atrophies on both the bilateral hippocampi and the bilateral amygdalas, which is also consistent with the shape findings obtained from our previous studies [20,23] as well as other studies [15–19,21,26], although shape analyses of the amygdala are less common than those of the hippocampus.…”

“…5 and 6), the localized surface area atrophy in the right amygdala is more wide spread than that in the left amygdala, with the main subregions affected being the basolateral and basomedial components. A thorough survey of the AD literature would suggest that there have been very few published amygdalar subfield morphometric analyses, with [69] being the sole example outside of previous studies by the current authors' research groups [20,23,24]. A direct comparison with the findings reported in [69] is challenging given that the subdivision criteria of the amygdalas were rather different.…”

“…This shape analysis pipeline lies in the framework of large deformation diffeomorphic metric mapping (LDDMM) [34], the key idea of which is to quantify local morphometric properties using a diffeomorphism that connects two coordinate systems of interest and is itself obtained as the endpoint of a geodesic. This pipeline has been successfully applied to various aspects of AD-related investigation, including the detection and quantification of subcortical surface area atrophies in MCI and AD [20] as well as preclinical AD [23,35], the quantification of rates of change in the localized surface areas of the hippocampus, the amygdala, and the ventricle in MCI and AD [24], the analysis of MTL shape neurodegeneration networks in preclinical AD [36], the interactive effects of the apolipoprotein E genotype and age upon hippocampal and amygdalar shapes in MCI and AD [37], and the estimation of the onset time for MTL morphometric abnormalities induced by AD [38]. In keeping with our previous studies, we will introduce high-field (7 Tesla) subregional divisions of the hippocampus (four subregions: CA1, CA2, CA3 combined with dentate gyrus, and subiculum) and the amygdala (four subregions: basolateral, basomedial, centromedial, and lateral nucleus) for a more detailed evaluation of the regionally specific shape abnormalities in AD.…”

Reproducibility of Deep Gray Matter Atrophy Rate Measurement in a Large Multicenter Dataset

“…Atrophy has been found to be associated with impaired neurologic and neurocognitive performance. [7][8][9][10] More recently, research revealed that deep GM atrophy specifically plays an important role in the characterization, course, and progression of AD [11][12][13][14][15][16][17] and in other diseases like MS [18][19][20] and Parkinson disease. [21][22][23] Measurements of deep GM atrophy could therefore be of importance in the evaluation of neuroprotective treatment (eg, in investigating drug efficacy).…”

Development of multimodal neuroimaging markers for neurological disorders – Part 1

“…By using the fMRI method, this study focused on amygdale segmentation and proposed its accu-rate functional disconnection pattern in the AD patients. Recent researches on AD have shown that altered structure and function of amygdale, which provided a promising indicator of AD [17]. However, previous studies often considered the amygdale as a single structure [18], and little is known about the functional connectivity changes of amygdale subregions in AD subjects.…”