A Novel Approach Integrating Magnetic Resonance Imaging (MRI) Data and Artificial Intelligence for Predicting the Success Rate of Vaginal Delivery in Pregnant Women
Not yet recruiting
- Conditions
- Vaginal Delivery
- Interventions
- Device: Mri scan of fetal head and pelvis
- Registration Number
- NCT06044129
- Lead Sponsor
- Second Affiliated Hospital of Wenzhou Medical University
- Brief Summary
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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- Female
- Target Recruitment
- 200
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.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Vaginal trial labor group Mri scan of fetal head and pelvis -
- Primary Outcome Measures
Name Time Method The mode of delivery during delivery Vaginal or cesarean delivery in the end
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
department of obstetrics of Second Affiliated Hospital of Wenzhou Medical University
🇨🇳Wenzhou, Zhejiang, China