An Outflow Boundary Condition Model for Noninvasive Prediction of Fractional Flow Reserve in Diseased Coronary Arteries

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American Society of Mechanical Engineers (ASME)

Abstract

This paper reports on a new boundary condition formulation to model the total coronary myocardial flow and resistance characteristics of the myocardial vascular bed for any specific patient when considered for noninvasive diagnosis of ischemia. The developed boundary condition model gives an implicit representation of the downstream truncated coronary bed. Further, it is based on incorporating patient-specific physiological parameters that can be noninvasively extracted to account for blood flow demand to the myocardium at rest and hyperemic conditions. The model is coupled to a steady three-dimensional (3D) collocated pressure-based finite volume flow solver and used to characterize the functional significance of a patient diseased coronary artery segment without the need for predicting the hemodynamics of the entire arterial system. Predictions generated with this boundary condition provide a deep understanding of the inherent challenges behind noninvasive image-based diagnostic techniques when applied to human diseased coronary arteries. The overall numerical method and formulated boundary condition model are validated via two computational-based procedures and benchmarked with available measured data. The newly developed boundary condition is used via a designed computational methodology to (a) confirm the need for incorporating patient-specific physiological parameters when modeling the downstream coronary resistance, (b) explain the discrepancies presented in the literature between measured and computed fractional flow reserve (FFRCT), and (c) discuss the current limitations and future challenges in shifting to noninvasive assessment of ischemia.

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Coronary artery disease, Fractional flow reserve, myocardial, Humans, Models, cardiovascular, Blood vessels, Boundary conditions, Forecasting, Heart, Hemodynamics, Noninvasive medical procedures, Numerical methods, Physiology, Computational methodology, Coronary artery segments, Fractional flow reserves, Implicit representation, Non-invasive assessments, Outflow boundary conditions, Physiological parameters, Resistance characteristics, Allometry, Animal experiment, Animal model, Article, Benchmarking, Canine model, Cardiac muscle, Coronary artery, Coronary vascular resistance, Diagnostic procedure, Fractional flow reserve, Heart muscle blood flow, Human, Hyperemia, Mathematical analysis, Mathematical model, Non invasive procedure, Nonhuman, Physical model, Prediction, Validation process, Biological model, Pathophysiology, Physiological models

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