Quality Control of Ultrasound Images During Early Pregnancy Via AI

Deep Learning-based Quality Control of Ultrasound Images During Early Pregnancy

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.

Study Overview

• Status: Recruiting
• Conditions: Early Pregnancy
• Intervention / Treatment: Other: Image quality control

Detailed Description

This research is dedicated to integrating artificial intelligence technology to optimize the quality control process of early pregnancy ultrasonography. The ultrasound images involved primarily focus on the median sagittal section, NT section, and choroid plexus of the fetus during early pregnancy. In this regard, the investigators have collaborated with renowned medical institutions such as Beijing Obstetrics and Gynecology Hospital, Peking University Third Hospital, Changsha Hospital for Maternal and Child Health Care, and Second Xiangya Hospital of Central South University to retrospectively and prospectively collect a vast amount of early pregnancy fetal ultrasound image data. Based on this, the investigators plan to establish a model rooted in deep learning. This model will be capable of precisely identifying key anatomical regions in standard ultrasound scan images. Furthermore, by recognizing these anatomical structures, the model will determine whether the ultrasound image meets the standard scanning quality. This model is anticipated to serve as a powerful auxiliary tool in obstetric ultrasonography, enabling real-time assessment of ultrasound image quality, thereby significantly reducing the rates of missed and misdiagnosed fetal diseases such as Down Syndrome and neural system malformations.

• Study Type: Observational
• Enrollment (Estimated): 400

Contacts and Locations

• Study Contact: Name: Di Dong, Ph.D; Phone Number: +86 13811833760; Email: di.dong@ia.ac.cn
• Study Contact Backup: Name: Yali Zang, ph.D; Email: yali.zang@ia.ac.cn

Study Locations

• China
  • Beijing, China
    • Recruiting
    • Peking University Third Hospital
    • Contact: Di Dong; Email: di.dong@ia.ac.cn
  • Beijing, China
    • Recruiting
    • Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University
    • Contact: Di Dong; Email: di.dong@ia.ac.cn
  • Changsha, China
    • Recruiting
    • Changsha Hospital for Maternal and Child Health Care
    • Contact: Di Dong; Email: di.dong@ia.ac.cn
  • Changsha, China
    • Recruiting
    • Second Xiangya Hospital of Central South University
    • Contact: Di Dong; Email: di.dong@ia.ac.cn

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

Women in early pregnancy

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

• 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.

Study Plan

How is the study designed?

Number of groups / cohorts

4

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
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.	Other: Image quality control; 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.
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.	Other: Image quality control; 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.
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.	Other: Image quality control; 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.
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.	Other: Image quality control; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
The accuracy of intelligent analysis system in image quality control module	The agreement between the prediction outcome of intelligent analysis system and the golden standard	one month

Collaborators and Investigators

• Sponsor: Chinese Academy of Sciences
• Collaborators: Peking University Third Hospital; Second Xiangya Hospital of Central South University; Beijing Obstetrics and Gynecology Hospital; Changsha Hospital for Maternal and Child Health Care

Study record dates

Study Major Dates

• Study Start (Actual): September 1, 2023
• Primary Completion (Estimated): December 31, 2023
• Study Completion (Estimated): July 30, 2028

Study Registration Dates

• First Submitted: August 13, 2023
• First Submitted That Met QC Criteria: August 13, 2023
• First Posted (Actual): August 21, 2023

Study Record Updates

• Last Update Posted (Actual): September 8, 2023
• Last Update Submitted That Met QC Criteria: September 6, 2023
• Last Verified: September 1, 2023

More Information

Terms related to this study

• Keywords: Ultrasound; Early Pregnancy; Quality Control
• Other Study ID Numbers: CASMI005

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: 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.
• IPD Sharing Time Frame: Data will become available 6 months after study completion and will remain available for a period of 5 years.
• IPD Sharing 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.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No