ON THE UNCERTAINTY QUANTIFICATION OF HYPERELASTIC PROPERTIES USING PRECISE AND IMPRECISE PROBABILITIES TOWARD RELIABLE IN SILICO SIMULATION OF THE SECOND-STAGE LABOR

Abstract

Finite element models of the second-stage labor system have been commonly developed for providing objective and quantitative indicators as well as innovative therapeutic solutions for decision supports. However, the reliability of the simulation outcomes remains a challenging issue due to uncertainties in input data and model complexity as well as the lack of validation. The objective of this study was to perform uncertainty quantification (UQ) on the material properties of the pelvis soft tissue with a focus on the uterus tissue during the second labor simulation leading to explore more plausible outcome space for reliable decision support making. The developed modeling and simulation workflow includes an image-based finite element model of the fetal body and pelvis soft tissues (floor, vagina and uterus), an uncertainty modeling procedure using precise and imprecise probabilities and an uncertainty propagation process based on the Monte Carlo method with and without parameter dependency. Obtained results showed that hyperelastic properties of the uterus tissue are very sensitive during the second stage of labor simulation. Moreover, the use of imprecise probability and parameter dependency lead to a more consistent range of values for uterus tissue stress analysis. This study performed, for the first time, an UQ on the hyperelastic properties of the uterus tissue from the in silico simulation of the second-stage labor. This opens new avenues for providing reliable indicators for clinical decision support. As a perspective, the active uterus behavior will be integrated into a more realistic second-stage labor model and simulation. Then, UQ will be conducted for more reliable decision support.