Parameter Estimation in a Rule-Based Fiber Orientation Model from End Systolic Strains Using the Reduced Order Unscented Kalman Filter

Fiber orientation is a major factor in the determination of end-systolic strains within models of cardiac mechanics. Unfortunately, direct patient-specific acquisition of fiber orientation is not readily available nowadays in the clinic. As an alternative, we propose to use the Reduced Order Unscented Kalman Filter to estimate rule-based fiber orientation parameters from end-systolic wall strains that can be obtained using more traditional imaging methodologies. We address the estimation of fiber orientation in the physiological left ventricle, where end-systolic strains were generated in-silico using a 12-parameter rule-based fiber model. The estimation process focused on the determination of the three most influential parameters of an imperfect 5-parameter rule-based fiber model. Our results show that these three fiber parameters can be estimated within an average deviation of 6^∘ from a combination of three end-systolic strains even when the initial guess for each estimated parameter was set 10^∘ away from the ground truth value.