MULTISCALE CARDIAC MODEL OF NANOPARTICLE-DRIVEN ATHEROSCLEROSIS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 与PNNL的合作者：詹姆斯·卡森、凯文·米纳德、安德鲁·库普拉特 共享数据，为建议拨款做出贡献 这项研究旨在产生必要的初步数据和必要的计算技术，以开发将心血管功能与呼吸功能联系起来的小鼠心脏的多尺度计算模型。最终目的是研究动脉粥样硬化、纳米颗粒的存在和继发性呼吸道炎症之间的关系。动脉粥样硬化是一种进行性疾病。然而，越来越多的证据表明，急性暴露于周围颗粒物可能与导致其发病的冠状动脉内皮损伤有关。同时，众所周知，流体切应力和冠状动脉跨壁压的有害变化扰乱了血管内皮细胞的生化，加剧了动脉粥样硬化斑块形成根源的局部炎症。因此，纳米颗粒的局部分散和沉积、心率加快引起的生物力学改变、血液粘度的改变和心律失常的急性发作，以及炎性细胞因子的释放和循环可能协同作用促进动脉粥样硬化斑块的形成。这项研究的长期目标是通过将心血管功能与呼吸功能和生物力学与生物化学联系起来来研究这种协同作用。 在该项目的这一阶段，我们希望获得灌流固定的整个小鼠的高分辨率(50微米)图像，具体目的是仔细描述小鼠心脏的原位几何形状，包括冠状动脉血管和心脏瓣膜。这些数据将被用来开发一个可计算的小鼠心脏网格，作为未来与心脏功能和病理相关的生物物理学计算的基础。我们目前的重点将是完成这项任务的算法开发，并预计将导致一份同行评议的出版物。 作为NIH资助的NHLBI/BRP(1RO1HL073598-01A1)项目“呼吸系统的3D成像和计算建模”的一部分，我们的团队已经成功地从呼吸系统的高分辨率MR图像开发出可计算网格。 此外，作为当前项目的一部分，我们已经成功地开发了从连续的冷冻微体图像重建小鼠心脏几何形状的技术。通过基于约束弹性的方法，将单个截面非线性地配准(翘曲)到连续的截面。由此产生的体积具有细胞分辨率。同时，我们开发了一种尺度不变的网格算法，该算法基于局部特征大小的概念，快速生成高质量的、接近垂直的生物几何铺装。现在可以通过整个心脏网络自动创建三层高质量的四面体。这一点很重要，因为肌纤维角往往由三层组成(心内膜、中壁和心外膜)。我们目前正在编写两份基于这一努力的手稿，以便提交给数字期刊。将该方法应用于小鼠心脏数据的第三份手稿将在今年晚些时候当磁共振数据可用时提交。因此，从技术角度来看，这个项目成功的机会很高。 最后，该项目的合作者是各自领域的专家，具备成功完成该项目的必要背景。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. With collaborators from PNNL: James Carson, Kevin Minard, Andrew Kuprat DATA SHARED to contribute to proposed grant This research is directed at generating the necessary preliminary data and the necessary computational technology to develop a multiscale computational model of the mouse heart that will link cardiovascular function to respiratory function. The ultimate goal is to investigate the relationship among atherosclerosis, the presence of nanoparticles, and the secondary perturbations of respiratory inflammation. Atherosclerosis is a progressive disease. However, there is growing evidence that acute exposure to ambient particulate matter may be involved in lesions of the coronary endothelium that lead to its onset. At the same time, it is well known that deleterious alterations in the fluid shear stress and coronary transmural pressure perturb endothelial biochemistry and exacerbate the local inflammation at the root of atherosclerotic plaque formation. Thus, the local dispersion and sedimentation of nanoparticles, the biomechanical alterations secondary to increased heart rate, altered blood viscosity and acute episodes of cardiac arrhythmia, and the release and circulation of inflammatory cytokines may act synergistically to promote atherosclerotic plaque formation. The long-term goal of this research is to investigate this synergy by linking cardiovascular function with respiratory function and biomechanics with biochemistry. During this phase of the project, we would like to acquire high-resolution (50 micron) images of a perfusion-fixed whole mouse, with the specific aim of carefully characterizing the geometry of the mouse heart in-situ, including coronary vasculature and cardiac valves. The data will used to develop a computable grid of the mouse heart that will serve as a foundation for future biophyics calculations related to cardiac function and pathology. Our current focus will be algorithm development for the completion of this task and is expected to result in a peer-reviewed publication. Our group has successfully developed computable grids from high-resolution MR images of the respiratory system as part of the NIH-funded NHLBI/BRP (1RO1HL073598-01A1 ) project entitled "3D Imaging and Computational Modeling of the Respiratory System". In addition, as part of the current project, we have successfully developed the technology for reconstructing mouse heart geometry from serial cryomicrotome images. Individual sections were nonlinearly registered (warped) to successive sections via a constrained elasticity based approach. The resulting volume has cellular resolution. In tandem, we have developed a scale-invariant gridding algorithm that quickly produces a quality, nearly orthogonal paving of biological geometries based on the concept of local feature size. It is now possible to automatically create three layers of excellent quality tetrahedra through the entire cardiac network. This is important as myofiber angles tend to organize in three layers (endocardium, mid-wall and epicardium). We are currently preparing two manuscripts based on this effort to be submitted to numerical journals. A third manuscript based on the application of the approach to the mouse heart data will be submitted later this year as the MR data becomes available. Thus, from a technological point of view, this project has a high chance of success. Finally, the collaborators on this project are experts in their field and have the necessary background to succesfully complete this project.