Blinkouskaya Yana, Weickenmeier Johannes
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
Front Mech Eng. 2021 Jul;7. doi: 10.3389/fmech.2021.705653. Epub 2021 Jul 19.
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 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.
健康和病理性脑衰老均以不同程度的认知衰退为特征，这些衰退与被称为脑萎缩的形态学变化密切相关。这些标志性的形态学变化包括皮质变薄、白质和灰质体积减少、脑室扩大以及脑回消失，所有这些都是由无数亚细胞和细胞衰老过程引起的。虽然脑衰老的生物学机制已得到广泛研究，但脑衰老的力学机制仍未得到充分研究。在此，我们提出了一个多物理模型，该模型将组织萎缩与阿尔茨海默病生物标志物的进展联系起来。我们采用将变形梯度乘法分解为收缩部分和弹性部分的方法。我们将萎缩建模为区域特异性各向同性收缩，并区分健康衰老中恒定的、依赖于组织的萎缩率以及阿尔茨海默病中与局部生物标志物浓度成比例的萎缩率。我们的有限元建模方法提供了一个计算框架，用于系统地研究脑萎缩的时空进展及其对脑形态的区域影响。我们通过与揭示持续的年龄相关萎缩模式的横断面医学成像研究进行比较来验证我们的结果。我们的长期目标是开发一种诊断工具，能够区分健康衰老和加速衰老（通常在阿尔茨海默病及相关痴呆症中观察到），以便能进行更早、更有效的干预。
