Foetus-specific neuromusculoskeletal modelling with MRI-driven vaginal delivery kinematics during the second stage of labor

Abstract

Childbirth simulations lack realism due to an oversimplification of the foetal model, particularly as most models do not allow joint motion. Foetus-specific neuromusculoskeletal (NMS) model with a detailed articulated skeleton is still not available in the literature. The present work aims at proposing the first-ever foetus-specific NMS model and then simulating the foetal descent during a vaginal delivery by using in vivo medical resonance imaging (MRI) childbirth data. Moreover, the developed model is provided open source for the community. Our foetus-specific NMS model was developed using the geometries reconstructed from a foetal computed tomography (CT) scan (Female, mass = 2.35 kg, length = 50 cm). The model contains 22 joints (64 degrees of freedom) and 65 muscles with a particular attention to the cervical spine level to enable the simulation of the cardinal movements. Then, the skull-to-cervical-spine (S/CP) and cervical-spine-to-torso (CP/T) deflection angles were extracted from in vivo MRI data for motion simulation. The S/CP and CP/T deflexion angles range from 12 degrees of flexion to 2 degrees of extension and from 7 degrees of flexion to 22 degrees of extension respectively. The developed model opens new avenues in more biofidelic childbirth simulations with a complete foetal NMS model. Obtained outcomes with the in vivo MRI data enabled to perform a first simulation of the foetal descent kinematics using real childbirth data. Future works will focus on developing a novel muscle formulation of the foetus and combining such a NMS model with a deformable model to simulate childbirth and associated complication scenarios.

Keywords:

• Foetus-specific NMS modelling
• in vivo MRI childbirth
• childbirth simulation
• rigid multi-bodies dynamics
• articulated foetal skeleton

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors would like to thank the Hauts-de-France region and the ENGSYS graduate school (Information and Knowledge Society (IKS) program) for funding. The authors also acknowledge the Métropole Européenne de Lille (MEL) and ISITE ULNE (R-TALENT-20-009-DAO) for providing financial support to this project.