Mathematical modeling and sensitivity analysis of arterial anastomosis in the arm

Abstract

Mathematical modeling is a powerful tool for predicting and investigating cardiovascular (CV) diseases. It has been shown that the lumped-parameter model can draw on an analogy between electrical circuits and fluid flow to provide a simple but effective method for modeling the human cardiovascular system.In order to build a patient-specific CV model, it is not practically feasible to estimate numerous model parameters (electrical and structural) from patient-specific data (measurements). However, estimation may be possible if optimal measurement locations are identified for important model parameters with complementary optimal time regions. Thus, sensitivity analysis can be used to identify important parameters as well as the optimal measurement locations and optimal time regions in the pressure and flow waves.In this study, we applied parametric local sensitivity analysis to a linear elastic lumped-parameter model of the arm arteries (with and without anastomosis) to identify important electrical and structural parameters. The ultimate goal of this study is to provide guidance for experimentalists about what to measure (pressure and flow) and where (network locations) in order to estimate the key CV model parameters, which are the first steps required to build a patient-specific CV model.