A holistic view of the effects of episiotomy on pelvic floor

Patient-specific surrogate model to predict pelvic floor dynamics during vaginal delivery

Childbirth is a challenging event that can lead to long-term consequences such as prolapse or incontinence. While computational models are widely used to mimic vaginal delivery, their integration into clinical practice is hindered by time constraints. The primary goal of this study is to introduce an artificial intelligence pipeline that leverages patient-specific surrogate modeling to predict pelvic floor injuries during vaginal delivery. A finite element-based machine learning approach was implemented to generate a dataset with information from finite element simulations. Thousands of childbirth simulations were conducted, varying the dimensions of the pelvic floor muscles and the mechanical properties used for their characterization. Additionally, a mesh morphing algorithm was developed to obtain patient-specific models. Machine learning models, specifically tree-based algorithms such as Random Forest (RF) and Extreme Gradient Boosting, as well as Artificial Neural Networks, were trained to predict the nodal coordinates of nodes within the pelvic floor, aiming to predict the muscle stretch during a critical interval. The results indicate that the RF model performs best, with a mean absolute error (MAE) of 0.086 mm and a mean absolute percentage error of 0.38%. Overall, more than 80% of the nodes have an error smaller than 0.1 mm. The MAE for the calculated stretch is equal to 0.0011. The implemented pipeline allows loading the trained model and making predictions in less than 11 s. This work demonstrates the feasibility of implementing a machine learning framework in clinical practice to predict potential maternal injuries and assist in medical-decision making.

The Most Common Functional Disorders and Factors Affecting Female Pelvic Floor

The pelvic floor (PF) is made of muscles, ligaments, and fascia, which ensure organ statics, maintain muscle tone, and are involved in contractions. This review describes the myofascial relationships of PF with other parts of the body that determine the proper functions of PF, and also provides insight into PF disorders and the factors contributing to them. PF plays an important role in continence, pelvic support, micturition, defecation, sexual function, childbirth, and locomotion, as well as in stabilizing body posture and breathing, and cooperates with the diaphragm and postural muscles. In addition, PF associates with distant parts of the body, such as the feet and neck, through myofascial connections. Due to tissue continuity, functional disorders of muscles, ligaments, and fascia, even in the areas that are distant from PF, will lead to PF disorders, including urinary incontinence, fecal incontinence, prolapse, sexual dysfunction, and pain. Dysfunctions of PF will also affect the rest of the body.