Mechanomarker-informed identification of Alzheimer's disease based on lateral ventricular deformation.
Authors
Affiliations (2)
Affiliations (2)
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA; Department of Engineering Science, University of Oxford, Oxford OX3 7DQ, UK.
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA; Department of Engineering Science, University of Oxford, Oxford OX3 7DQ, UK. Electronic address: [email protected].
Abstract
Structural magnetic resonance imaging reveals lateral ventricular enlargement as a prominent structural change in normal aging, with accelerated expansion in Alzheimer's disease and related dementias. In this study, we characterize ventricular shape changes and corresponding mechanical loading in cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects in their seventies, using longitudinal magnetic resonance images over a two-year interval. Surface-based deformation metrics were computed to capture localized displacement magnitude, curvature changes, surface area stretch, and maximum principal wall strain, both relative to the population average at baseline and relative to each subject's baseline over the two-year follow-up. Longitudinal displacement over two years increased markedly with disease progression, rising 114 ± 15% from CN to AD. Area stretch exhibited a more modest 6 ± 1% increase, while maximum principal wall strain nearly doubled, increasing 110 ± 16% from CN to AD. Curvature change remained minimal when averaged globally, although localized deformations along ventricular edges suggest subtle region-specific alterations. The significant differences between mechanics-related features for individual disease groups highlight the value of deformation-derived mechanomarkers that go beyond the more commonly reported volumetric analyses. As such, our mechanomarkers demonstrated a predictive value for disease classification, especially in the direct comparison of CN and AD. Our results highlight the potential of ventricular mechanomarkers as non-invasive, MRI-derived biomarkers for early detection and monitoring of neurodegenerative progression, providing insight into the mechanical loading resulting from structural brain shape changes.