CAREER: Multiscale Modeling of Thrombus Formation and its Response to External Loads

该教师早期职业发展（CAREER）奖将资助旨在提高我们在建模和预测患者血管中血栓（或凝块）形成和破裂方面的知识的研究。血栓虽然有助于止血，但也会阻碍血管中的血液流动，导致高血压、心脏病和中风等心血管疾病。事实上，心血管疾病是全世界死亡的主要原因。因此，了解血块形成及其在活血液环境中的反应对于预测和治疗血块生长至关重要。然而，预测凝块的生长和破裂具有挑战性，因为血流会影响凝块的形成和成分，而这反过来又决定了凝块的强度及其对流动的响应。另一方面，凝块的生长和成分也会改变流量。该奖项将支持致力于开发多尺度建模工具的研究，这些工具使用强大的计算机和人工智能来更好地预测凝块生长及其对脉动流、血细胞碰撞和血管扩张的反应。将使用 3D 打印硅基血管网络复制品进行实验验证。 此外，该项目将通过开发课程、采用交互式笔记本等创新教学工具来培训下一代工程师和科学家，重点关注代表性不足的少数群体，以整合研究和教育，包括计算思维、高性能计算和机器学习。外展活动包括参加STEM节日和组织工程夏令营，以激励K12学生进入STEM领域。 该职业项目的总体目标是开发一个多尺度模型来预测不同流动条件下的凝块生长和反应。具体来说，它将： 1) 识别和研究关键无量纲参数对血凝块生长和结构的影响，考虑流量、红细胞 (RBC)、血小板和其他生物聚合物，如纤维蛋白和血管性血友病因子； 2) 表征凝块响应，包括由于脉动流和给定成分的血管壁变形导致的变形和破裂； 3) 使用物理信息神经网络（或 PINN）增强一维模型预测大规模血管网络中的凝块生长、破裂并量化其不确定性。 该项目是了解血栓力学并为手术和治疗的临床决策提供支持的关键一步。该项目将使首席研究员能够推进计算科学和工程的知识基础，并在生物力学和力学生物学领域建立长期职业生涯。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Faculty Early Career Development (CAREER) award will fund research that intends to advance our knowledge in modeling and predicting thrombus (or clot) formation and rupture in patient’s blood vessels. Clots, while aiding in stopping bleeding, can also obstruct blood flow in vessels, leading to cardiovascular diseases like hypertension, heart attack, and stroke. In fact, cardiovascular disease is the leading cause of death worldwide. Thus, understanding clot formation and its response in the live blood environment is crucial for predicting and treating clot growth. However, predicting clot growth and rupture is challenging, as blood flow impacts the formation and composition of a clot, which in-return determines the strength of the clot and its response to flow. On the other hand, the growth and composition of the clot changes the flow as well. This award will support research striving to develop multiscale modeling tools that use powerful computers and artificial intelligence to better predict clot growth and its response to pulsatile flows, collision from blood cells, and vessel dilation. Experimental validations will be performed using 3D printed silicon based vascular network replica. In addition, the project will integrate research and education by developing curriculum, employing innovative teaching tools like interactive notebooks to train the next generation or engineers and scientists, with a focus on underrepresented minorities, in computational thinking, high-performance computing, and machine learning. Outreach activities involve participation in STEM festivals and organizing engineering summer camps to inspire K12 students to enter the STEM field. The overall objective of this CAREER project is to develop a multiscale model to predict clot growth and response, under different flow conditions. Specifically, it will: 1) identify and investigate the impact of key dimensionless parameters on clot growth and structure considering flow, red blood cells (RBCs), platelets, and other biopolymers such as fibrin and von Willebrand factor; 2) characterize clot response including deformation and rupture due to pulsatile flow and vessel wall deformation with given composition; and 3) predict clot growth, rupture, and quantify its uncertainties in large scale vascular network using physics informed neural network (or PINN) augmented one-dimensional models. This project is a critical step toward understanding clot mechanics and providing support for clinical decision-making for surgery and treatment. This project will allow the Principal Investigator to advance the knowledge base in computational science and engineering and establish a long-term career in Biomechanics and Mechanobiology.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.