Caçoilo Andreia, Dortdivanlioglu Berkin, Rusinek Henry, Weickenmeier Johannes
Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America.
Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, United States of America.
Brain Multiphys. 2023 Dec;5. doi: 10.1016/j.brain.2023.100072. Epub 2023 May 26.
Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.
脑室周围白质高信号(WMH)是衰老大脑医学影像中的常见表现,与脑小血管疾病、白质炎症及侧脑室壁退变导致的白质损伤相关。尽管已开展大量研究,但脑室周围WMH的病因仍不明确。我们认为,与年龄相关的脑室扩张和脑室壁退变之间存在强烈耦合,这会导致跨脑 - 液屏障的液体交换失调。在此,我们提出了一个多物理场模型,该模型将脑萎缩驱动的脑室壁负荷与脑室周围WMH的形成和进展相耦合。我们使用患者数据创建了八个二维有限元模型,并展示了我们损伤模型的预测能力。我们的模拟结果表明,我们准确捕捉到了脑室周围WMH生长的时空特征。一方面,我们观察到损伤首先出现在前角和后角,然后扩散到更深的白质组织中。另一方面,我们注意到脑室周围WMH首次出现前需要长达12年的时间,并得出我们所有模型中脑室周围WMH损伤的平均年化增长率为15.2±12.7毫米/年。敏感性分析表明,我们的模型参数具有足够的敏感性,能够合理地解释个体在发病时间和损伤生长方面的差异。此外,我们还表明,透明隔(一种分隔左右侧脑室的薄膜)起初会延迟脑室周围WMH的发病,但从长期来看会导致更高的WMH负荷。