MULTISCALE CARDIAC MODEL OF NANOPARTICLE-DRIVEN ATHEROSCLEROSIS

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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.