Quality Control of Ultrasound Images During Early Pregnancy Via AI
Deep Learning-based Quality Control of Ultrasound Images During Early Pregnancy
1 other identifier
observational
400
1 country
4
Brief Summary
This research integrates artificial intelligence to enhance early pregnancy ultrasonography quality control, focusing on specific fetal sections. In collaboration with prominent medical institutions, the investigators have amassed extensive fetal ultrasound data. The investigators aim to develop a deep learning model that can accurately identify essential anatomical areas in ultrasound images and evaluate their quality. This tool is expected to significantly decrease misdiagnoses of conditions like Down Syndrome and neural system deformities by ensuring real-time image quality assessment.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Sep 2023
Longer than P75 for all trials
4 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 13, 2023
CompletedFirst Posted
Study publicly available on registry
August 21, 2023
CompletedStudy Start
First participant enrolled
September 1, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
July 30, 2028
ExpectedSeptember 8, 2023
September 1, 2023
4 months
August 13, 2023
September 6, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
PR curve of image quality control module
Using Precision-Recall curve and mean average percision as evaluating indicator of image quality control model.
one month
Secondary Outcomes (1)
The accuracy of intelligent analysis system in image quality control module
one month
Study Arms (4)
Beijing Obstetrics and Gynecology Hospital affiliated to Capital Medical University
Beijing Obstetrics and Gynecology Hospital affiliated to Capital Medical University collects clinical information and ultrasound images of sagittal, NT and choroid plexus views of the fetus which was obtained from early pregnant women who underwent NT sweeps.
Peking University Third Hospital
Peking University Third Hospital collects clinical information and ultrasound images of sagittal, NT and choroid plexus views of the fetus which was obtained from early pregnant women who underwent NT sweeps.
Changsha Hospital for Maternal and Child Health Care
Changsha Hospital for Maternal and Child Health Care collects clinical information and ultrasound images of sagittal, NT and choroid plexus views of the fetus which was obtained from early pregnant women who underwent NT sweeps.
Second Xiangya Hospital of Central South University
Second Xiangya Hospital of Central South University collects clinical information and ultrasound images of sagittal, NT and choroid plexus views of the fetus which was obtained from early pregnant women who underwent NT sweeps.
Interventions
The investigators identify the region of interest in the relevant section to give a conclusion on whether the image is standard or not, guiding clinicians to standardize the operation, and reducing the rate of misdiagnosis and underdiagnosis.
Eligibility Criteria
Women in early pregnancy
You may qualify if:
- Women in early pregnancy who have detailed personal information and ultrasound images.
- The ultrasound images should clearly show the fetus's median sagittal, NT, and choroid plexus views.
You may not qualify if:
- Ultrasound images from women in mid to late pregnancy.
- Ultrasound images that are unclear or blurry, making evaluation difficult.
- Women who did not provide complete personal and medical information during the ultrasound scan.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Chinese Academy of Scienceslead
- Beijing Obstetrics and Gynecology Hospitalcollaborator
- Peking University Third Hospitalcollaborator
- Changsha Hospital for Maternal and Child Health Carecollaborator
- Second Xiangya Hospital of Central South Universitycollaborator
Study Sites (4)
Beijing Obstetrics and Gynecology Hospital affiliated to Capital Medical University
Beijing, China
Peking University Third Hospital
Beijing, China
Changsha Hospital for Maternal and Child Health Care
Changsha, China
Second Xiangya Hospital of Central South University
Changsha, China
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER GOV
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
August 13, 2023
First Posted
August 21, 2023
Study Start
September 1, 2023
Primary Completion
December 31, 2023
Study Completion (Estimated)
July 30, 2028
Last Updated
September 8, 2023
Record last verified: 2023-09
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ANALYTIC CODE
- Time Frame
- Data will become available 6 months after study completion and will remain available for a period of 5 years.
- Access Criteria
- Interested researchers should submit a detailed research proposal and a data usage application for review. All participating units of this study will assess the application to determine eligibility for data access.
Individual participant data (IPD) may be made available to other researchers upon request. Interested researchers should present a reasonable research proposal and a data usage application. All participating units of this study will review and assess the proposal and application to determine whether to share the data.