期刊
FRONTIERS IN MECHANICAL ENGINEERING-SWITZERLAND
卷 7, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fmech.2021.705653
关键词
cerebral atrophy; brain aging; Alzheimer's disease; multiphysics modeling; finite element modeling; brain shape changes
资金
- National Institute on Aging of the National Institutes of Health [R21AG067442]
Both healthy and pathological brain aging are characterized by cognitive decline and morphological changes, with cerebral atrophy playing a key role. While the biology of brain aging has been extensively studied, the mechanics of brain aging is still understudied. The proposed multiphysics model aims to systematically study the progression of cerebral atrophy and differentiate between healthy aging and Alzheimer's disease.
Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer's disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer's disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results via comparison with cross-sectional medical imaging studies that reveal persistent age-related atrophy patterns. Our long-term goal is to develop a diagnostic tool able to differentiate between healthy and accelerated aging, typically observed in Alzheimer's disease and related dementias, in order to allow for earlier and more effective interventions.
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