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Abstract #3487

Hydraulic Conductivity Estimation using Magnetic Resonance Elastography

Adam J. Pattison1, Phillip R. Perrinez1, Matthew D. J. McGarry1, John B. Weaver1,2, Keith D. Paulsen1,3

1Thayer School of Engineering, Dartmouth College, Hanover, NH, United States; 2Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States; 3Norris Cotton Cancer Center, Lebanon, NH, United States

While linear elastic and viscoelastic material models are the norm for magnetic resonance elastography (MRE), poroelasticity may better estimate properties of biphasic material like brain tissue. Further, this algorithm allows for estimation of hydrodynamic material parameters such as pore pressure, porosity, and hydraulic conductivity. Defined as the rate at which fluid penetrates through pores, hydraulic conductivity may provide new clinical information like differentiation between normal and tumorous tissues and detection of increased intracranial pressure. In a recently developed poroelastic algorithm, this parameter can be estimated with high accuracy and resolution in simulated phantoms and may become an important biomarker in disease processes.