A Combined Experimental-Computational Method to Evaluate Abdominal Aortic Aneurysm Wall Stress

评估腹主动脉瘤壁应力的实验-计算相结合的方法

• 批准号: 1031366
• 负责人: Robert Peattie
• 金额: $ 60.65万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1031366&HistoricalAwards=false
• 关键词: Combined; Experimental; Computational; Method; Evaluate

PROJECT ABSTRACTIntellectual Merit:Abdominal aortic aneurysms (AAAs) represent permanent, localized swellings of the aorta that occur where the diseased vessel is weakened. AAA rupture accounts for 14,000 deaths in the US annually. A growing body of literature has developed in recent years concerned with methods for quantitatively evaluating the distribution and magnitude of stress in patient-specific models of the aneurysm wall, since mechanical stress is thought to be the cause of rupture. However, the role of blood flow in creating wall stress has not been addressed to date. Accordingly, the research objective of this award is to develop a combined experimental-computational physiologic wall stress analysis (PWSA) procedure that evaluates wall stress distributions and maxima in models accurately replicating the shape, non-uniform thickness and mechanical properties of individual patient AAAs. To accomplish this aim, AAA wall tissue samples will be collected from patients undergoing surgical repair. The mechanical properties of those samples will be measured, and an elastic material replicating the diseased wall stiffness will be used to fabricate a model replicating the shape of the patient lesion. Wall pressure in this model will be measured under flow conditions emulating the patient aorta. The measured wall pressure data will then be used as loading in a corresponding computational evaluation of stress levels within the wall.Broader Impact:Establishment of a protocol for accurate assessment of AAA wall stress using patient-specific information has the potential to significantly impact clinical AAA management. The proposed studies will provide the first quantitative measurements of pressure distributions using aneurysm phantoms with both realistic geometries and patient-derived mechanical properties, as well as the first quantitative evaluation of wall stress based entirely on patient properties. Furthermore, the project will permit us to continue to engage undergraduate as well as graduate students in our ongoing research efforts, expanding the research training, educational experience and opportunities available to the students involved. Moreover, we will take full advantage of infrastructure in place at Tufts University for recruiting and retaining women and underrepresented minorities in research. These include undergraduate outreach programs in Computer Science, Biomedical Engineering and robotics. In addition, the Tufts University School of Medicine has conducted a highly successful NIH-funded minority outreach program for over ten years, permitting underrepresented undergraduates to spend summers at Tufts involved in biomedical science research. Research-driven training activities generated through this project will engage students in cross-disciplinary computational thinking, thus providing critical training for future scientists and engineers.

项目摘要：腹主动脉瘤(AAA)是指发生在病变血管减弱的部位的永久性的、局限性的主动脉肿胀。在美国，AAA破裂每年造成1.4万人死亡。近年来，由于机械应力被认为是破裂的原因，越来越多的文献涉及定量评估特定患者模型中动脉瘤壁应力分布和大小的方法。然而，到目前为止，血流在产生壁应力中的作用还没有得到解决。因此，该奖项的研究目标是开发一种实验-计算相结合的生理壁应力分析(PWSA)程序，在准确复制单个患者AAA的形状、不均匀厚度和机械特性的模型中评估壁应力分布和最大值。为了实现这一目标，将从接受手术修复的患者身上收集AAA壁组织样本。这些样本的机械性能将被测量，一种复制病壁僵硬的弹性材料将被用来制造复制患者病变形状的模型。该模型中的壁压将在模拟患者主动脉的流动条件下进行测量。然后，测量的壁压数据将被用作相应的壁内应力水平的计算评估的载荷。广泛的影响：建立使用患者特定信息准确评估AAA壁应力的方案有可能显著影响临床AAA管理。拟议的研究将首次使用具有真实几何形状和患者派生的机械特性的动脉瘤模型对压力分布进行定量测量，以及首次完全基于患者的特性对壁应力进行定量评估。此外，该项目将允许我们继续让本科生和研究生参与我们正在进行的研究工作，扩大参与的学生可以获得的研究培训、教育经验和机会。此外，我们将充分利用塔夫茨大学现有的基础设施，招聘和留住女性和研究中代表性不足的少数族裔。这些项目包括计算机科学、生物医学工程和机器人学方面的本科生拓展项目。此外，塔夫茨大学医学院实施了一项由美国国立卫生研究院资助的少数民族外展计划，十多年来非常成功，允许未被充分代表的本科生在塔夫茨大学从事生物医学科学研究的暑假。通过该项目产生的以研究为导向的培训活动将使学生参与跨学科的计算思维，从而为未来的科学家和工程师提供关键培训。