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Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materialsNeurosciencePeer-reviewed journal article

Characterization of mechanical tissue properties in post-mortem human brain using magnetic resonance elastography

Joy MojumderiD, Yuan-Chiao LuiD, Alexa DianoiD, Ahmed AlshareefiD, Matthew McGarryiD, Philip V. BaylyiD, Curtis L. JohnsoniD, John A. ButmaniD, Dzung L. PhamiD

PDFDOIPreprint

Abstract

Traumatic brain injury (TBI) is a serious health condition that can cause neurological dysfunction to varying degrees depending on the nature of the mechanical insult. In biomechanical studies of TBI under high loading conditions, post-mortem human subjects (PMHS) are often used since ethical concerns prohibit such experiments in living human subjects. Because PMHS brains undergo significant changes following death, it is important to understand the relationship between the mechanical properties of PMHS brain tissue and living tissue. In this study, we performed magnetic resonance elastography (MRE) on three PMHS specimens to estimate the material properties of the cadaveric brain, namely the storage modulus and the loss modulus, as well as the resulting shear stiffness and damping ratio. We also performed longitudinal MRE scans on one of the PMHS over the span of two months to investigate the evolution of tissue properties with post-mortem degradation. In comparison to in vivo subjects of age range 70-75 years, a substantially higher stiffness (mean: 5.96kPa) and lower damping ratio (mean: 0.09) were found in PMHS models. This study also revealed an initial increase in shear stiffness up to the seventh day post-mortem, followed by a steady decrease by the fifty-eighth day. However, the damping ratio displayed an opposite trend to that of shear stiffness. These changes were heterogeneous across brain regions. The collected measurements and analysis elucidate the changes in mechanical properties in post-mortem subjects, and can be used to build and validate computational models of TBI.

Citations
3
FWCI
1.73
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top 15%

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