Image based modeling of biomechanical factors for risk assessment of developing periventricular white matter hyperintensities

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Image based modeling of biomechanical factors for risk assessment of developing periventricular white matter hyperintensities White matter lesions, visible as white matter hyperintensities (WMH) on T2-weighted MR images, have been shown to have a close association with cognitive impairment and dementia. Commonly found in periventricular brain areas and subcortical white matter, WMH are prevalent in the elderly population (age > 60). They are particularly prevalent in mild cognitive impairment and Alzheimer's disease patients. Multiple pathological changes have been found in WMH, including demyelination and loss of WM fibers. Moreover, WMH has been closely associated with vascular deficits, commonly called “small vessel disease”. Despite the prevalence and potential significance of WMH in cognitive declines, there is little to no in-depth knowledge regarding the underlying causes and biophysical vulnerability of the periventricular brain tissue. Our ultimate goal is to understand the role of various biomechanical factors in formation of WMH in order to predict or intervene in the WMH progression. The objective of this proposal is to determine the effect of biomechanical forces (acting on the lateral ventricular wall due to cardiac pulse) on the adjacent white matter microstructure and formation of periventricular WMH, by using novel MRI methods and image-based computational modeling. In this project, we will develop a computational modeling framework based on 3D brain anatomy obtained with structural MR images, ventricular boundary changes obtained with high-speed MR measurements and mechanical properties of the tissues. The image-based modeling will compute the stress variations in the brain, especially at periventricular white matter. The locations with high stresses will be correlated with the regions of WMHs, microstructural damages and cognitive measures. Understanding the contribution of biomechanical factors to WMH will allow us to improve characterization of WMH, reveal additional contributing factors (e.g., hypertension), and predict cognitive outcomes. In order to determine the role of biomechanical factors in WMH, we propose the following specific aims: Aims proposed:  Specific Aim 1: Develop an MRI-based modeling methodology for computing subject-specific stress distribution in the periventricular brain tissue due to cardiac pressure pulse.  Specific Aim 2: Determine the impact of pulsatile pressure on the formation of periventricular WMH.