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

N/ANot Yet RecruitingNCT06044129

Second Affiliated Hospital of Wenzhou Medical University200 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

200

Conditions

Vaginal Delivery

Interventions

Mri scan of fetal head and pelvisDEVICE

The pelvic parameters and fetal head parameters of pregnant women were measured by MRI, including pelvic entrance plane, middle pelvic plane, pelvic outlet plane, pubic arch Angle, double parietal diameter, occipitofrontal diameter, and suboccipital fontanel diameter.

Eligibility

Sex: FEMALEMin age: 18 YearsMax age: 35 YearsHealthy volunteers:

Medical Language ↔ Plain English

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.

Locations (1)

department of obstetrics of Second Affiliated Hospital of Wenzhou Medical University

Wenzhou, Zhejiang, China

Outcomes

Primary Outcomes

The mode of delivery

Vaginal or cesarean delivery in the end

Time frame: during delivery

Central Contacts

Ying Hua

CONTACT

+8613676403165 wzfeyhy1015@126.com

Data from ClinicalTrials.gov

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