Mathematical modeling and computer simulation of aortic dissection

主动脉夹层的数学建模和计算机模拟

• 批准号: 9031871
• 负责人: Boyce Eugene Griffith
• 金额: $ 44.63万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-26 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9031871
• 关键词: Accounting; Acute; Address; Affect; Anatomy; Animal Model; Aorta; Aortic Diseases; Arteriographies; Automobile Driving; Blood; Blood Circulation; Blood Pressure; Blood Vessels; Blood flow; Caliber; Chronic; Clinical; Clinical Management; Computer Simulation; Data; Development; Disease; Dissection; Distal; Eating; Elasticity; Ensure; Genetic; Geometry; Goals; Health; Human; Image; Implant; Intervention; Lesion; Liquid substance; Magnetic Resonance; Magnetic Resonance Imaging; Mechanics; Medical; Methodology; Methods; Modeling; Operative Surgical Procedures; Outcome; Pathology; Patient risk; Patients; Pattern; Physicians; Physiological; Plant Roots; Play; Property; Residual state; Risk; Risk Assessment; Role; Rupture; Shapes; Specimen; Stents; Stress; Structure; Surgical Flaps; Surgical Management; Syndrome; Testing; Thoracic aorta; Time; Tissue Sample; Tissues; Tube; Work; X-Ray Computed Tomography; ascending aorta; base; clinical decision-making; dacron; experience; hemodynamics; high risk; implantation; improved; in vivo; innovation; mathematical model; mortality; non-compliance; physical model; predictive modeling; repaired; research study; response; shear stress; simulation; treatment planning; treatment strategy; valve replacement

DESCRIPTION (provided by applicant): Management of aortic diseases has progressed dramatically since the first successful, reproducible surgical intervention in 1956; however, although our understanding of the genetic and cellular bases of such diseases has steadily grown, treatment planning still generally relies on simple risk-assessment models and clinical experience. Some pathological conditions have been mimicked with animal models, but results from such studies may not be readily extrapolated to patients. Other pathologies lack any accepted or reproducible animal model. An example is aortic dissection, in which an intimal tear in the aortic wall propagates into the media to form a false lumen within the vessel wall. Surgical treatment for aortic dissection consists of either replacement of a portion of the aorta, or endovascular stent implantation to cover the affected segment. Both approaches carry significant risks, and determining the optimal choice and timing of an intervention is challenging. Because there are no accepted animal models of aortic dissection, experimental studies must use physical or computational models. Existing computational models of aortic dissection use conventional computational fluid dynamics (CFD) approaches, in which the vessel wall and flap are treated as rigid structures. Although CFD models are able to predict wall shear stress distributions, they are unable to account for the interactions between the blood and vascular tissues, or for the effects of such interactions on the dynamics of the dissected aorta. This project will develop fluid-structure interaction (FSI) models of aortic dissection that overcome th limitations of CFD models. These predictive models will be used to perform patient-specific simulations that ultimately will aid in clinical decision making, e.g., selecting optimal medical therapies or surgical interventions. This project will develop two types of FSI models of aortic dissection. The first type of model will use an idealized description of the geometry of the vessel and lesion. Such models are ideally suited for addressing questions that take the form of parameter studies. These models will be used to study systematically how geometry and driving conditions affect the dynamics of both developing dissections and fully developed lesions. The second type of model will account for the effects of patient-specific anatomy by using geometries derived from computed tomography (CT) and/or magnetic resonance (MR) imaging studies. To characterize the elastic response of human aortic tissue, tissue samples will be collected from both normal and diseased human aortas, and tensile tests will be performed to characterize the mechanical properties of these specimens. The data from these tests will be used to develop corresponding healthy and disease-specific constitutive models. The characterization of the elasticity of both the healthy and diseased human aorta has the potential to impact work on a broad range of aortic diseases. Finally, these models will be used to study the medical and surgical management of patients who require or who have undergone only partial surgical repair of the dissection, as is now commonly done in cases in which the dissection involves the proximal ascending aorta (Type A dissections).

描述（由申请人提供）：自 1956 年首次成功、可重复的外科手术以来，主动脉疾病的治疗取得了巨大进展；然而，尽管我们对此类疾病的遗传和细胞基础的了解不断增长，但治疗计划仍然普遍依赖于简单的风险评估模型和临床经验。一些病理状况已经用动物模型进行了模拟，但此类研究的结果可能无法轻易外推到患者身上。其他病理学缺乏任何公认的或可重复的动物模型。一个例子是主动脉夹层，其中主动脉壁的内膜撕裂传播到中膜中，在血管壁内形成假腔。外科 主动脉夹层的治疗包括更换部分主动脉，或植入血管内支架以覆盖受影响的部分。这两种方法都存在重大风险，确定干预的最佳选择和时机具有挑战性。由于没有公认的主动脉夹层动物模型，实验研究必须使用物理或计算模型。现有的主动脉夹层计算模型使用传统的计算流体动力学（CFD）方法，其中血管壁和瓣被视为刚性结构。尽管 CFD 模型能够预测壁剪切应力分布，但它们无法解释血液和血管组织之间的相互作用，或这种相互作用对解剖主动脉动力学的影响。该项目将开发主动脉夹层的流固耦合 (FSI) 模型，克服 CFD 模型的局限性。这些预测模型将用于执行针对患者的模拟，最终将有助于临床决策，例如选择最佳的药物治疗或手术干预。 该项目将开发两种类型的主动脉夹层 FSI 模型。第一种模型将使用船舶几何形状的理想化描述 和病变。此类模型非常适合解决参数研究形式的问题。这些模型将用于系统地研究几何形状和驾驶条件如何影响发育中的夹层和完全发育的病变的动力学。第二种类型的模型将通过使用计算机断层扫描 (CT) 和/或磁共振 (MR) 成像研究得出的几何形状来解释患者特定解剖结构的影响。为了表征人类主动脉组织的弹性响应，将从正常和患病的人类主动脉收集组织样本，并进行拉伸测试来表征这些样本的机械特性。这些测试的数据将用于开发相应的健康和疾病特异性本构模型。健康和患病人类主动脉的弹性特征有可能影响广泛的主动脉疾病的研究。最后，这些模型将用于研究需要或仅接受部分夹层手术修复的患者的医疗和手术治疗，就像现在在夹层涉及近端升主动脉（A 型夹层）的情况下通常所做的那样。