Image Guided Constitutive Modeling of the Brain Tissue

图像引导脑组织本构建模

• 批准号: 6805611
• 负责人: OSKAR SKRINJAR
• 金额: $ 7.23万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-30 至 2006-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6805611
• 关键词: bioimaging /biomedical imaging; brain imaging /visualization /scanning; brain morphology; computer assisted diagnosis; diagnosis design /evaluation; image enhancement; image guided surgery /therapy; intracranial pressure; mechanical stress; model design /development; phantom model; physical model; three dimensional imaging /topography; tomography

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.

描述(由申请人提供)： 我们的最终目标是开发一种图像引导的机械计算工具，用于治疗和外科手术，最初的重点是神经外科。该工具将允许预测在任何类型的机械激励下的大脑变形。为了实现这一最终目标，我们的长期目标将是开发体内人脑组织力学行为的可靠本构模型。我们建议通过获取脑室造口后脑组织反应的整体MR或CT图像来定义体内脑组织的机械特性。脑室造口可缓解升高的颅内压(ICP)。使用最先进的3D图像分析，这些图像可以转换为位移场和应变场。利用对脑组织响应的逆分析，可以建立脑组织的本构模型。这种逆分析代表了一个具有挑战性的成像-机械耦合问题，我们将其称为图像引导本构建模(IGCM)。IGCM是一个复杂的迭代过程，采用选定的本构模型来模拟变形的组织行为。拟议的先导性研究的目标是在受控环境中开发和测试图像导引本构建模的概念：在植入“肿瘤”的大脑模型上，尽可能最好地模拟体内大脑的几何形状、力学特性和边界条件。为了实现这一目标，拟议的研究将实现以下一套目标： 目的1：利用硅胶铸造的人脑左半球模型，进行脑室造口和压痕实验，建立肿瘤脑的行为物理模型。 目的2：基于图像的脑模型形变前后CT图像的应变场推导。 目的3：在新的热力学一致性框架-超塑性框架内进行应变场的有限元逆分析和本构模型的推导。 目的4：用从“健康”问题和“肿瘤”中提取的样本的元素测试数据对数值模型进行验证，后者从体模中移除。