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NCT Number: NCT06044129

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

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.

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Key information

Conditions

Age range

18 year–35 year

Sex eligibility

Female

Study type

Observational

Primary location

department of obstetrics of Second Affiliated Hospital of Wenzhou Medical University

Wenzhou, Zhejiang, 325027, China

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Mri scan of fetal head and pelvis

Device

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.

Primary outcomes

  1. The mode of delivery

    Time frame: during delivery

    Vaginal or cesarean delivery in the end

Study contacts

Contact information is provided by the study sponsor or research team.

Ying Hua

CONTACT

[email protected]

+8613676403165 ext. +8613676403165

Sponsors and collaborators

Lead sponsor

Second Affiliated Hospital of Wenzhou Medical University

Other

Registry information

Important dates

Study start
2024
Primary completion
2026
Study completion
2026
First posted
Sep 21, 2023
Registry last updated
Sep 21, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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