Improving ultrasound image quality during early pregnancy using AI
Deep Learning-based Quality Control of Ultrasound Images During Early Pregnancy
This study is testing if using artificial intelligence can improve the quality of ultrasound images during early pregnancy to help doctors better identify important fetal features and reduce misdiagnoses.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 400 (estimated) |
| Ages | 20 Years and up |
| Sex | Female |
| Sponsor | Chinese Academy of Sciences Government |
| Locations | 4 sites (Beijing and 3 other locations) |
| Trial ID | NCT06002412 on ClinicalTrials.gov |
What this trial studies
This research integrates artificial intelligence to enhance the quality control of ultrasound images during early pregnancy, focusing on specific fetal anatomical sections. Collaborating with prominent medical institutions, the study collects extensive fetal ultrasound data to develop a deep learning model. This model aims to accurately identify key anatomical areas in ultrasound images and assess their quality in real-time. By ensuring high-quality imaging, the tool is expected to significantly reduce misdiagnoses of conditions such as Down Syndrome and neural system deformities.
Who should consider this trial
Good fit: Ideal candidates for this study are women in early pregnancy who have clear ultrasound images showing specific fetal views.
Not a fit: Patients who are in mid to late pregnancy or have unclear ultrasound images will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to more accurate diagnoses and improved outcomes for pregnancies by reducing the rates of missed fetal abnormalities.
How similar studies have performed: Other studies have shown promise in using AI for image analysis, indicating potential success for this novel approach.
Eligibility criteria
Show full inclusion / exclusion criteria
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.
Where this trial is running
Beijing and 3 other locations
- Beijing Obstetrics and Gynecology Hospital affiliated to Capital Medical University — Beijing, China (Recruiting)
- Peking University Third Hospital — Beijing, China (Recruiting)
- Changsha Hospital for Maternal and Child Health Care — Changsha, China (Recruiting)
- Second Xiangya Hospital of Central South University — Changsha, China (Recruiting)
Study contacts
- Study coordinator: Di Dong, Ph.D
- Email: di.dong@ia.ac.cn
- Phone: +86 13811833760
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.