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Developing a Computational Model to Predict Clot Transport

开发预测血块运输的计算模型

基本信息

批准号：
2017805
负责人：
Keefe Manning
金额：
$ 45.99万
依托单位：
Pennsylvania State Univ University Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017805&HistoricalAwards=false
关键词：
Developing Computational Model Predict Clot

项目摘要

The research supported by this award will develop a new tool to better understand potentially dangerous complications that can occur with biomedical implants. Blood-contacting devices such as a heart valves, stents, catheters, and blood pumps are successfully implanted into thousands of patients every year in the United States. While huge strides have been made in improving their safety and effectiveness, the formation of blood clots in these devices remains a leading problem. When a clot forms in a device, it can prevent it from working properly, or break away from the device and result in complications such as stroke. This work will develop a computational tool to simulate how blood flow and biochemistry in these devices interact to result in clotting. This tool will take advantage of state-of-the-art supercomputing resources made available by the National Science Foundation. Thanks to recent efforts to promote the use of such computer simulations in approval of new biomedical devices, there is potential for this work to impact human health. Specifically, the model developed here may be used to offer additional evidence of safety and effectiveness of new devices, reduce development costs, and shorten time to market. This research combines several disciplines, including biochemistry, physics, and high-performance computing, and will help broaden the participation of underrepresented groups.Various blood-contacting cardiovascular devices have been shown to improve outcomes in patients with cardiovascular disease, but thromboembolism remains as a leading risk factor. The nature of these devices makes in-vitro investigation of thromboembolism complicated and costly, leaving gaps in the understanding of the complex interactions between the device and the body. The goal of this research is to develop an in-silico method to model thromboembolism, incorporating biochemical surface interactions between blood and synthetic materials, the kinetics of the coagulation cascade, and the viscoelastic properties of blood clots into a fluid-dynamics solver. Important model processes will be experimentally validated, including concentration curves of pro-coagulant plasma proteins, clot mechanical properties, and fluid-dynamic conditions where embolization occurs. To address the large uncertainties and phenomenology in many of the simulated processes, Monte-Carlo experiments will be used to evaluate the credibility of the models’ predictions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项支持的研究将开发一种新的工具，以更好地了解生物医学植入物可能发生的潜在危险并发症。在美国，每年都有成千上万的患者成功地植入血液接触装置，如心脏瓣膜、支架、导管和血泵。虽然在提高其安全性和有效性方面取得了巨大进步，但这些设备中的血栓形成仍然是一个主要问题。当凝块在装置中形成时，它可以阻止装置正常工作，或从装置脱离并导致并发症，如中风。这项工作将开发一种计算工具来模拟这些设备中的血流和生物化学如何相互作用以导致凝血。该工具将利用美国国家科学基金会提供的最先进的超级计算资源。由于最近努力促进使用这种计算机模拟来批准新的生物医学设备，这项工作有可能影响人类健康。具体而言，本文开发的模型可用于提供新器械安全性和有效性的额外证据，降低开发成本并缩短上市时间。这项研究结合了生物化学、物理学和高性能计算等多个学科，将有助于扩大代表性不足的群体的参与。各种血液接触心血管设备已被证明可以改善心血管疾病患者的预后，但血栓栓塞仍然是主要的风险因素。这些装置的性质使得血栓栓塞的体外研究复杂且昂贵，在装置与身体之间的复杂相互作用的理解方面留下了空白。本研究的目标是开发一种模拟血栓栓塞的计算机模拟方法，将血液和合成材料之间的生物化学表面相互作用，凝血级联的动力学以及血液凝块的粘弹性特性纳入流体动力学求解器。将对重要的模型过程进行实验验证，包括促凝血血浆蛋白的浓度曲线、凝块机械特性和发生栓塞的流体动力学条件。为了解决许多模拟过程中存在的巨大不确定性和现象学问题，将使用蒙特-卡罗实验来评估模型预测的可信度。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。