Image Guided Constitutive Modeling of the Brain Tissue

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DESCRIPTION (provided by applicant): Our ultimate goal is a development of an image guided mechanical computational tool for applications in therapy and surgery with neurosurgery being our initial focus. The tool will allow for prediction of the brain deformation during any kind of mechanical excitation. Towards this ultimate goal, our long-term objective will be a development of reliable constitutive models of the mechanical behavior of the in-vivo human brain tissue. We propose to define the mechanical properties of the brain tissue in-vivo by taking the global MR or CT images of a brain response to ventriculostomy - the relief of the elevated intracranial pressure (ICP). Using state-of-the-art 3D image analysis, these images can be translated into displacement and strain fields. Using inverse analysis of the brain response, the constitutive models of the brain tissue can be developed. This inverse analysis represents a challenging coupled imaging-mechanical problem, which we will term Image Guided Constitutive Modeling (IGCM). The IGCM is a complex iterative process of adapting a chosen constitutive model to mimic the deformed tissue behavior. The goal of the proposed pilot research is to develop and test the concepts of the Image Guided Constitutive Modeling in the controlled environment: on the brain phantoms with implanted "tumors", with the best possible simulation of the in-vivo brain geometry, mechanical properties and boundary conditions. Towards this goal, the following set of aims will be achieved in the proposed research: AIM 1: Physical modeling of the behavior of brain with tumor using phantom of the left hemisphere of human brain cast from silicon gel and subjected to "ventriculostomy" and "indentation" tests. AIM 2: Image based derivation of the strain fields from pre- and post-deformation CT images of the brain phantom. AIM 3: Inverse finite element analysis of the strain fields and derivation of constitutive models within the novel thermodynamically consistent framework - Hyperplasticity. AIM 4: Verification of the numerical models against the data from the element tests on the samples extracted from the "healthy" issue and the "tumor, after the latter is removed from the phantom.