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Both longitudinal and cross-sectional imaging studies have shown that ventricular volume progressively increases with age and expands even faster in neurodegenerative diseases such as Alzheimer\u2019s disease and related dementias. Strikingly, however, we only have a limited understanding of ventricular shape changes and the corresponding mechanical loads that act on the ventricular wall as we age. Therefore, we propose a framework that uses nonlinear registration to quantify subject-specific brain deformations between two longitudinal scans, maps the resulting warp field onto a ventricular surface template mesh, and quantifies mechanical loading measures including displacement magnitude, curvature change, area stretch, and maximum principal wall strain. From the Alzheimer\u2019s Disease Neuroimaging Initiative, we selected a cohort of 50 cognitively normal subjects aged 70\u201375 years at baseline and with a follow-up scan 4\u20135 years later. In this group, we observed mostly uniform expansion of the lateral ventricles with an average displacement magnitude of 0.88\u00a0\u00b1\u00a00.3\u00a0mm across the whole ventricle. At the same time, there are distinct sections of the ventricular wall that experience high mechanical loads with respect to our mechanomarkers. Specifically, maximum mechanical loading consistently localizes along the ventricular edges and atrium while the ventricle\u2019s main body exhibits minimal loading. Based on the cohort included in this study, we did not observe sex-based differences with respect to any mechanomarker, noticed that on average 29.2\u00a0\u00b1\u00a09.3% of the ventricular wall experience wall area increase, and that on average only 4.4\u00a0\u00b1\u00a02.5% of the ventricular wall experience wall shrinking. Interestingly, regions of elevated mechanical loading showed reliable spatial correspondence with periventricular white matter hyperintensity locations in our subjects for whom FLAIR imaging was available (n\u00a0=\u00a039). Additionally, mechanomarkers showed increased magnitudes with periventricular white matter hyperintensity burden, with curvature change demonstrating the strongest group separation. These findings suggest that ventricular enlargement is associated with localized mechanical stresses that coincide with vulnerable white matter regions. Taken together, we present strong evidence in support of the hypothesis that the mechanical loading associated with age-related ventricular enlargement is intricately linked to periventricular white matter degeneration and corresponding cognitive decline.<\/jats:p>","DOI":"10.1007\/s10237-026-02080-8","type":"journal-article","created":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T07:34:14Z","timestamp":1780472054000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Aging-related lateral ventricular shape changes and corresponding mechanical loading derived from longitudinal image registration"],"prefix":"10.1007","volume":"25","author":[{"given":"Lauren","family":"Cunniff","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johannes","family":"Weickenmeier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"the Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,3]]},"reference":[{"key":"2080_CR56","unstructured":"Andersson JL, Jenkinson M, Smith S, (2010) Non-linear registration, aka spatial normalisation, Technical Report TR07JA2, FMRIB Centre, University of Oxford, FMRIB technical report"},{"key":"2080_CR39","doi-asserted-by":"crossref","unstructured":"Amiri-Hezaveh A, Tan S, Deng Q, Umulis D, Cunniff L, Weickenmeier J, Buganza Tepole A (2025) A physics-informed deep learning deformable medical image registration method based on neural odes, Int J Comput Vision 1\u201326","DOI":"10.1007\/s11263-025-02476-6"},{"key":"2080_CR37","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","volume":"38","author":"J Ashburner","year":"2007","unstructured":"Ashburner J (2007) A fast diffeomorphic image registration algorithm. 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