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- Berron, David, et al.
(author)
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Hippocampal subregional thinning related to tau pathology in early stages of Alzheimer’s disease
- 2022
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In: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 18:S1
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Journal article (peer-reviewed)abstract
- Background: Subregions in the medial temporal lobe (MTL) are affected early by Alzheimer’s disease (AD) pathology and subject to grey matter atrophy. Measuring the earliest AD-related atrophy in the hippocampus is challenging as region-of-interest (ROI) analyses of hippocampal subregional volumes collapse across voxels within anatomical subregions. PET imaging studies, however, report accumulation of tau pathology between anatomical subregions in the earliest disease stages (Berron et al., 2021) fitting reports from the neuropathological literature (Lace et al., 2019; Ravikumar et al., 2021). Thus, sensitive in vivo methods of point-wise structural measures are needed in order to detect the earliest hippocampal thinning in AD along the anterior-posterior as well as the medial-lateral hippocampal axis. Method: Here we analyzed data from 76 amyloid-beta negative (Ab-) cognitively normal (CN), 46 Ab+ CN individuals and 25 Ab+ patients with mild cognitive impairment (MCI) from the BioFINDER-2 study, who underwent 7 Tesla T2-weighted structural magnetic resonance imaging, tau positron emission tomography imaging (using 18F-RO-948) and cognitive assessments. First, we segmented hippocampal subfields and extrahippocampal subregions. Second, we calculated point-wise hippocampal thickness estimates (Diers et al.) of hippocampal subfields subiculum, cornu ammonis (CA)1, CA2 and CA3 on the level of the hippocampal body. Thirdly, we extracted local tau-PET SUVR from Area 35 (A35), entorhinal cortex and amygdala. Finally, we assessed relationships between hippocampal local thickness and tau accumulation as well as cognitive performance. Result: Our analyses revealed earliest hippocampal thinning associated with tau accumulation in an area spanning the boundary of subiculum and CA1 at the level of the anterior hippocampal body. Ab+ MCI patients showed more posterior thinning in comparison to Ab- CU participants. Median thickness in an ROI comprising vertices with A35 tau-related thinning (A35-TauThinning-ROI) was significantly lower in MCI Ab+ and tended to be lower in CU Ab+ compared to CU Ab-. Higher median thickness in the hippocampal A35-TauThinning-ROI, but not whole CA1 nor subiculum thickness, was associated with better 10-Word-Delayed-Recall and higher PACC scores. Conclusion: Our results suggest that tau-related thinning of hippocampal subregions can be observed already in early disease stages. Tau-related point-wise thickness measures were more sensitive compared to volumetric measures of anatomical subregions.
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| 2. |
- Diers, Kersten, et al.
(author)
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An automated, geometry-based method for hippocampal shape and thickness analysis
- 2023
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In: NeuroImage. - 1053-8119. ; 276
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Journal article (peer-reviewed)abstract
- The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and psychiatric diseases. Hippocampal shape changes, however, are complex and cannot be fully characterized by a single summary metric such as hippocampal volume as determined from MR images. In this work, we propose an automated, geometry-based approach for the unfolding, point-wise correspondence, and local analysis of hippocampal shape features such as thickness and curvature. Starting from an automated segmentation of hippocampal subfields, we create a 3D tetrahedral mesh model as well as a 3D intrinsic coordinate system of the hippocampal body. From this coordinate system, we derive local curvature and thickness estimates as well as a 2D sheet for hippocampal unfolding. We evaluate the performance of our algorithm with a series of experiments to quantify neurodegenerative changes in Mild Cognitive Impairment and Alzheimer's disease dementia. We find that hippocampal thickness estimates detect known differences between clinical groups and can determine the location of these effects on the hippocampal sheet. Further, thickness estimates improve classification of clinical groups and cognitively unimpaired controls when added as an additional predictor. Comparable results are obtained with different datasets and segmentation algorithms. Taken together, we replicate canonical findings on hippocampal volume/shape changes in dementia, extend them by gaining insight into their spatial localization on the hippocampal sheet, and provide additional, complementary information beyond traditional measures. We provide a new set of sensitive processing and analysis tools for the analysis of hippocampal geometry that allows comparisons across studies without relying on image registration or requiring manual intervention.
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