CAREER: GPU-Accelerated Framework for Integrated Modeling and Biomechanics Simulations of Cardiac Systems

职业：用于心脏系统集成建模和生物力学模拟的 GPU 加速框架

• 批准号: 1750865
• 负责人: Adarsh Krishnamurthy
• 金额: $ 50万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1750865&HistoricalAwards=false
• 关键词: CAREER; GPU; Accelerated; Framework; Integrated

Cardiovascular diseases, such as heart failure, are one of the leading cause of death in the U.S. and pose a severe burden to the healthcare system. Most current treatments for cardiovascular diseases are based on rough estimates of outcomes from the results of clinical trials, which might not apply to individual patients due to patient-specific variations. Computational models of the cardiovascular system, developed from patient-specific clinical data, can help refine the diagnosis and personalize the treatment, significantly improving patient care and reducing mortality. The current patient-specific methods for cardiovascular diseases have been demonstrated mainly in simple, isolated examples. For widespread adoption of personalized medicine, a flexible and easy-to-use framework for integrating patient data and simulating cardiac biomechanics needs to be developed. This project focuses on creating an integrative framework with simulation, analysis, and visualization tools that will significantly advance the state-of-the-art in personalized medicine, ultimately improving patient care and treatment outcomes. Results from this research will benefit the U.S. healthcare system, society, and economy, while supporting the NSF mission to promote the progress of science and advance the national health. The tools developed as a part of this research involves several disciplines including computer science, bioengineering, and mechanical engineering. The multidisciplinary components of the project is being integrated into a larger educational effort that offers the students a solid foundation in developing computational tools and algorithms, while also broadening the participation of underrepresented groups in research.The primary objective of this research is the advancement of the state-of-the-art in translational medicine with the help of computational modeling and interactive analysis tools to improve the basic understanding of the cardiac muscle and personalize treatment of cardiovascular diseases in patients. The research focuses on creating a novel computational framework to automate biomechanics finite-element simulation and analysis of patient-specific cardiac systems. Further, it aims to advance the knowledge of disease and therapeutic mechanisms by developing advanced multiscale methods to model muscle contraction and growth. Some of the key computational tools and methods proposed as part of this framework include: (1) a geometric mesh generation tool for systematic generation of patient-specific finite element meshes from clinical data; (2) an algorithm for accelerating high-order finite-element simulations using the graphics processing unit (GPU) for fast tuning of model parameters to match the patients' baseline cardiac function; (3) new methods for multiphysics simulations of cardiac systems to model multi-scale muscle mechanics and tissue growth; and (4) new visualization and virtual reality tools to enable animated volume rendering and visual analytics of the results of the cardiac simulations. Successful development of these open-source tools will enable faster adoption of patient-specific computational models by the research community to understand therapeutic mechanisms. This framework can significantly advance the state-of-the-art in personalized medicine, ultimately improving patient care and treatment outcomes. The multidisciplinary components of the project is being integrated into a larger educational effort to offer students a solid foundation in combining biomedical engineering with scientific computing. The education and outreach plans of this research can inform the community about the crucial role of computational models in improving patient-care.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.

心力衰竭等心血管疾病是美国的主要原因之一，给医疗保健系统带来了沉重的负担。目前大多数心血管疾病的治疗方法都是基于临床试验结果的粗略估计，由于患者特异性的差异，这可能不适用于个体患者。根据患者特定的临床数据开发的心血管系统计算模型可以帮助完善诊断和个性化治疗，从而显着改善患者护理并降低死亡率。目前治疗心血管疾病的针对患者的方法主要是通过简单、孤立的例子来证明的。为了广泛采用个性化医疗，需要开发一个灵活且易于使用的框架来集成患者数据和模拟心脏生物力学。该项目的重点是创建一个包含模拟、分析和可视化工具的综合框架，该框架将显着推进个性化医疗的最先进水平，最终改善患者护理和治疗结果。这项研究的结果将有利于美国的医疗保健系统、社会和经济，同时支持 NSF 促进科学进步和促进国民健康的使命。作为这项研究的一部分开发的工具涉及多个学科，包括计算机科学、生物工程和机械工程。该项目的多学科组成部分正在被整合到更大的教育工作中，为学生开发计算工具和算法提供坚实的基础，同时也扩大代表性不足的群体对研究的参与。这项研究的主要目标是促进借助计算建模和交互式分析工具，利用最先进的转化医学，提高对心肌的基本了解，并对患者的心血管疾病进行个性化治疗。该研究的重点是创建一种新颖的计算框架，以自动执行患者特定心脏系统的生物力学有限元模拟和分析。此外，它的目标是通过开发先进的多尺度方法来模拟肌肉收缩和生长，以增进对疾病和治疗机制的了解。作为该框架的一部分提出的一些关键计算工具和方法包括：（1）几何网格生成工具，用于根据临床数据系统生成患者特定的有限元网格； (2) 使用图形处理单元 (GPU) 加速高阶有限元模拟的算法，以快速调整模型参数以匹配患者的基线心脏功能； （3）心脏系统多物理场模拟的新方法，以模拟多尺度肌肉力学和组织生长； (4) 新的可视化和虚拟现实工具，可实现心脏模拟结果的动画体积渲染和可视化分析。这些开源工具的成功开发将使研究界更快地采用患者特定的计算模型来了解治疗机制。该框架可以显着推进个性化医疗的最先进水平，最终改善患者护理和治疗结果。该项目的多学科组成部分正在被整合到更大的教育工作中，为学生提供生物医学工程与科学计算相结合的坚实基础。这项研究的教育和推广计划可以让社区了解计算模型在改善患者护理方面的关键作用。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。

项目成果

GPU-Accelerated Post-Processing and Animated Volume Rendering of Isogeometric Analysis Results

GPU 加速的等几何分析结果的后处理和动画体积渲染

• DOI: 10.14733/cadaps.2022.779-796
• 发表时间: 2021-11
• 期刊: Computer-Aided Design and Applications
• 作者: Shah, Harshil;Huang, Xin;Bingol, Onur;Rajanna, Manoj;Krishnamurthy, Adarsh
• 通讯作者: Krishnamurthy, Adarsh

3D reconstruction of plants using probabilistic voxel carving

使用概率体素雕刻对植物进行 3D 重建

• 发表时间: 2023-10
• 期刊: Computers and Electronics in Agriculture
• 影响因子: 8.3
• 作者: Jiale Feng;Mojdeh Saadati;Talukder Jubery;Anushrut Jignasu;Aditya Balu;Yawei Li;Lakshmi Attigala;Patrick S. Schnable;Soumik Sarkar;Baskar Ganapathysubramanian;et al
• 通讯作者: et al

Direct immersogeometric fluid flow and heat transfer analysis of objects represented by point clouds

对点云表示的物体进行直接浸没几何流体流动和传热分析

• DOI: 10.1016/j.cma.2022.115742
• 发表时间: 2022-10-25
• 期刊: Computer Methods in Applied Mechanics and Engineering
• 影响因子: 7.2
• 作者: Aditya Balu;M. Rajanna;Joel Khristy;Fei Xu;A. Krishnamurthy;M. Hsu
• 通讯作者: M. Hsu

Industrial scale Large Eddy Simulations with adaptive octree meshes using immersogeometric analysis

使用浸没几何分析通过自适应八叉树网格进行工业规模大涡模拟

• DOI: 10.1016/j.camwa.2021.05.028
• 发表时间: 2021-09
• 期刊: Computers & Mathematics with Applications
• 影响因子: 2.9
• 作者: Saurabh, Kumar;Gao, Boshun;Fernando, Milinda;Xu, Songzhe;Khanwale, Makrand A.;Khara, Biswajit;Hsu, Ming;Krishnamurthy, Adarsh;Sundar, Hari;Ganapathysubramanian, Baskar
• 通讯作者: Ganapathysubramanian, Baskar

Direct 3D printing of multi-level voxel models

多层次体素模型的直接3D打印

• DOI: 10.1016/j.addma.2021.101929
• 发表时间: 2021-04
• 期刊: Additive Manufacturing
• 影响因子: 11
• 作者: Ghadai, Sambit;Jignasu, Anushrut;Krishnamurthy, Adarsh
• 通讯作者: Krishnamurthy, Adarsh