A Novel Approach Integrating Magnetic Resonance Imaging (MRI) Data and Artificial Intelligence for Predicting the Success Rate of Vaginal Delivery in Pregnant Women

Second Affiliated Hospital of Wenzhou Medical University

Status: Not yet enrolling

Conditions: Vaginal Delivery

Treatments: Device: Mri scan of fetal head and pelvis

Study type: Observational

Funder types: Other

Identifiers

NCT06044129

SAHoWMU-CR2023-07-209

Details and patient eligibility

About

The aim of this study was to use MRI imaging to accurately scan the pregnant woman's pelvis and fetal skull, build a 3D model of them, and combine with artificial intelligence to develop an accurate tool to predict the success rate of vaginal delivery.

Enrollment: 200 estimated patients

Sex: Female

Ages: 18 to 35 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Full-term.
• Single fetus, head first.
• Pregnant women have vaginal couvade wishes.
• Complete clinical data of pregnant women.

Exclusion criteria

• Pregnancy with serious medical and surgical diseases.
• Abnormal fetal position (such as transverse, breech, etc.).
• Twin or multiple pregnancies.
• Vaginal couvade contraindications such as placenta previa.

Trial design

200 participants in 1 patient group

Vaginal trial labor group

Treatment:

Device: Mri scan of fetal head and pelvis