Ms. Peyton L. Delgorio Profile

Peyton L. Delgorio

at Univ of Delaware

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Proceedings Article | 4 April 2022 Presentation + Paper

Relationship between cerebral vasculature and brain stiffness measured using MR elastography

Ahmed Alshareef, Curtis Johnson, Aaron Carass, Andrew Knutsen, Peyton Delgorio, Grace McIlvain, Alexa Diano, K. T. Ramesh, Phillip Bayly, Dzung Pham, Jerry Prince

Proceedings Volume 12036, 120360O (2022) https://doi.org/10.1117/12.2612987

KEYWORDS: Brain, Magnetic resonance elastography, Image segmentation, Image processing, Traumatic brain injury, Neuroimaging, Mechanics, Magnetic resonance imaging

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Modeling brain tissue mechanics is important for understanding the pathogenesis of traumatic brain injury, with models often including brain tissue geometry and microstructural features like white matter fiber orientation. Recently, the cerebral vasculature has been included in models, however the effect of cerebral vessels on the mechanical response of the brain is unclear. A dataset of 23 subjects that includes structural MRI, angiography, and mechanical neuroimaging using magnetic resonance elastography (MRE) was collected to determine if there is a dependence of vasculature on in vivo brain mechanical properties. A pipeline was implemented using existing methods for processing anatomical, angiography, and MRE images; all images were co-registered for each subject and transformed to a common space. The regional mean stiffness and damping ratio of the brain, by anatomical segmentation, showed no dependence on vessel density but showed heterogeneity across the brain. A sub-regional analysis after stratifying by MRE stiffness showed a strong positive correlation in the cortical gray matter (R²=0.69) and a strong negative correlation in the deep gray matter (R²=0.76). Other regions showed similar trends with R² values below 0.54. The opposite trends could be a result of regional microstructure difference, or a dependence on vessel type and size. A similar analysis using the brain damping ratio showed no dependence of vasculature on brain viscous properties. Quantifying the dependence of brain mechanical properties on vasculature will aid in understanding the biomechanics of the brain and inform their use in computational models of brain injury.

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