A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging

Abstract

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${}^2$/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.

Statement of Significance: Brain aging is accompanied by many structural and functional changes. In nearly all aged brains, white matter lesions appear in periventricular and diffuse subcortical regions which are associated with progressive functional decline. In our work, we present a multiphysics model that not only predicts the onset location of periventricular white matter lesions but also their subsequent growth as a result of age-related cerebral atrophy and ventricular enlargement. Our model provides a mechanics-based rationale for their characteristic spatiotemporal progression patterns and will allow to identify at-risk subjects for early lesion formation.