Automated Segmentation of Levator Ani Muscle from 3D Endovaginal Ultrasound Images.

Levator ani muscle (LAM) avulsion is a common complication of vaginal childbirth and is linked to several pelvic floor disorders. Diagnosing and treating these conditions require imaging of the pelvic floor and examination of the obtained images, which is a time-consuming process subjected to operator variability. In our study, we proposed using deep learning (DL) to automate the segmentation of the LAM from 3D endovaginal ultrasound images (EVUS) to improve diagnostic accuracy and efficiency.

Training community gynecologists to perform intraoperative cystoscopy: a competency-based training experience.

Objective: This study aimed to pilot a cystoscopy training program for community gynecologists that is validated by posttraining examination.

Methods: Twenty-eight gynecologists were trained to perform cystoscopy using a competency-based training approach. Baseline information included years in practice and number of incontinence procedures and/or cystoscopies performed per month.

Age effects on pelvic floor symptoms in a cohort of nulliparous patients.

Objectives: This study aimed to investigate the effects of age on pelvic floor symptoms (PFSs) in nulliparous women.

Methods: Eighty community-dwelling nulliparous women, aged 21 to 70 years, were recruited. Pelvic floor support was assessed with pelvic organ prolapse quantification system.