CDI: Type II / Collaborative Research: A New Approach to the Modeling of Clot Formation and Lysis in Arteries
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abstract
Acute cardiac syndrome (ACS) due to arterial thrombosis is a leading cause of death in the US. There is a clear need to develop methods for quantitative risk assessment and analysis of ACS. However, due to inadequate, imperfect and uncertain knowledge regarding the various parameters that control arterial thrombosis, such methods do not exist. Given current incomplete knowledge, the proposed approach seeks to develop efficient simulation techniques to gain insight into thrombogenesis and to make probabilistic predictions of outcomes such as the probability of clot formation over specific time intervals. Coupling continuum mechanics to ideas from estimation theory and statistical signal processing the PIs will develop models whose parameters are random variables that allows for the incorporation of variability of parameters in the modeling stage itself. By ensuring that the continuum models have the structure of Hidden Markov Models (HMMs) it is possible to use the powerful tools of estimation theory to find probability distributions for the hidden variables from experimental measurements. In order to simulate the biochemistry of clotting and its complex interaction with blood flow and artery deformation, and to carry out risk analysis, the PIs will use parallelizable computational algorithms for the simulations. The PIs plan to replace the usual discrete approximation of the traditional balance laws of mechanics with highly parallelizable stochastic or ?probability flow? based simulation techniques. Disorders of coagulation and bleeding are of substantial clinical importance. Such conditions including ACS, myocardial infarction, pulmonary embolus, deep vein thrombosis and hemorrhagic disorders, amongst others are major contributors to mortality in the western world. The proposed research will provide an understanding of the processes of coagulation and bleeding and has the potential to have a tremendous impact on a variety of blood disorders. The proposed work is transformative in that it will meld together ideas from various scientific communities from biomedicine and biomechanics, mathematics, statistics and probability theory, estimation theory and signal processing, and has the potential to have significant impact on numerous scientific communities. As the researchers have a substantial track record in educational innovations the proposed research will also have salutary effect on educational aspects.
