Artifical IntelligenceEcho-IANCT07286591
Study Comparing Two Image Acquisition Modalities for Second-trimester Pregnancy Screening Ultrasound
A study testing Standard Ultrasound and US with AI in people with Artifical Intelligence and Echography Ultrasound, run by Clinique Rive Gauche at 1 site in France.
Trial summary
The second-trimester morphology ultrasound is a key examination in obstetric monitoring that aims to assess fetal growth, identify any structural abnormalities, and inspect anexes such as placenta, umbilical cord, cervix,... Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Artifical Intelligence, Echography Ultrasound
- What is being tested?
- Standard Ultrasound and US with AI
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteFrance
- Study dates
- 15 Dec 2025to 19 May 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Women aged 18 or over,
- With a single, viable pregnancy, definitively dated by first-trimester ultrasound, with no known malformations,
- Scheduled for a routine second-trimester screening ultrasound, i.e., between 20 weeks + 0 days and 24 weeks + 6 days,
- Having given their informed consent,
- Affiliated with the social security system or a beneficiary of such a plan.
Who cannot join
- Multiple pregnancy,
- Known fetal malformation,
- Pathological pregnancy,
- Cognitive impairment, or a disorder causing difficulty understanding instructions or answering questionnaires,
- Patient under legal guardianship,
- Patient not covered by health insurance,
- Protected patient: adult under guardianship, curatorship, or other legal protection, deprived of liberty by judicial or administrative decision
Trial locations and contacts
1 site in 1 country.
About this study
Official title: A Single-center Cross-sectional Study Comparing Two Image Acquisition Modalities for Second-trimester Pregnancy Screening Ultrasound.
The second-trimester morphology ultrasound is a key examination in obstetric monitoring that aims to assess fetal growth, identify any structural abnormalities, and inspect anexes such as placenta, umbilical cord, cervix,...
Several studies suggest that a significant proportion of fetal malformations can be detected during this time frame if a complete morphological analysis is performed. However, the reliability of the screening depends on the quality of the equipment, the operator's level of expertise, and adherence to protocols that define the necessary scans.
Read more
In France, since the first reports of the National Technical Committee on Prenatal Screening Ultrasound (2005), particular attention has been paid to standardizing practices. More recently, the French National Conference on Obstetric and Fetal Ultrasound (CNEOF) published new recommendations (2022, revised in 2023) including the development of reference silhouettes for the second-trimester examination, proposing 26 views (22 required and 4 additional). However, the CNEOF does not formalize quality criteria for evaluating the conformity of these images; this task has been taken over by the French College of Fetal Ultrasound (CFEF), which has established a scoring and validation grid for each fetal slice (see CFEF 2022 document).
In parallel, artificial intelligence (AI) is gradually becoming established as a decision support and automation tool in medical imaging, particularly in ultrasound. Deep learning algorithms are capable of identifying anatomical structures, positioning measurement markers, and selecting the most optimal slice, reducing inter-operator variability and streamlining workflow. In the field of obstetric ultrasound, some companies have launched systems capable of detecting or annotating fetal structures in real time, potentially improving diagnostic reliability and reproducibility. Samsung has developed a system called Live View Assist, available on its latest generation ultrasound scanners, which uses AI to automatically recognize and freeze the required fetal slices in real time.
The tool also offers automated validation: if the detected slice conforms to the expected standards, it is directly checked off on a checklist. This innovation promises time savings, a reduced risk of missing certain complex slices, and improved standardization.
However, there is little data, particularly in France, regarding to the actual performance of this tool in a routine screening context. Before considering the integration of Live View Assist and AI into daily practice, it is therefore essential to evaluate the quality of the images it acquires, the feasibility of a complete examination assisted by AI, as well as the potential impact on examination time and improvement of the workload for sonographers.
The aim of this study is to evaluate whether the quality of the 20 mandatory images automatically validated by Live View Assist is not inferior to that of the 20 mandatory images acquired and validated manually by an ultrasound technician, according to the CFEF quality criteria based on the silhouettes recommended by the CNEOF.
- Conditions
- Artifical Intelligence, Echography Ultrasound
- Being tested
- Standard Ultrasound, US with AI
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Standard UltrasoundProcedure or surgery
Standard US with a sonographer
US with AIProcedure or surgery
US with Live View Assist
| Study group | Role | What they receive |
|---|---|---|
| Standard ultrasound | Active comparator | Manual acquisition: acquisition of the 22 mandatory images and, if possible, the 4 additional images by the sonographer, respecting the standardized procedure derived from the CNEOF recommendations. Receives: Procedure: Standard Ultrasound |
| Artificial intelligence-assisted ultrasound | Experimental | AI-assisted acquisition: using the Live View Assist system to automatically capture the 20 mandatory views in real time, with validation and recording of images as soon as the algorithm detects an image conforming to the reference, and if possible the 2 complementary images. Receives: Procedure: US with AI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Images deemed "acceptable"
Images deemed acceptable (i.e., for each image, all criteria are rated as good or acceptable, with none being insufficient or poor).
To evaluate the primary objective, the statistical unit will be the image. All 20 mandatory images for each patient will be analyzed
Measured: through study completion, an average of 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Dec 2025
- Study start15 Dec 2025
- Primary completion19 May 2026
- Study completion19 May 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artifical IntelligenceStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Lead sponsor
- Clinique Rive Gauche
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07286591
- Sponsor's protocol ID
- Echo-IA
- Other IDs
- 2025-A01468-41, 2025-CRG-01
- Acronym
- Echo-IA
- Status last verified
- Mar 2026
- First submitted
- 27 Nov 2025
- Last updated
- 23 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 23 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Single-center Cross-sectional Study Comparing Two Image Acquisition Modalities for Second-trimester Pregnancy Screening Ultrasound.
- ClinicalTrials.gov ID
- NCT07286591
- Acronym / sponsor ID
- Echo-IA / Echo-IA
- Conditions
- Artifical Intelligence, Echography Ultrasound
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- Clinique Rive GaucheUniversity, hospital or other
- Study start
- 15 Dec 2025 (actual)
- Primary completion
- 19 May 2026 (actual)
- Study completion
- 19 May 2026 (actual)
- First posted
- 16 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The second-trimester morphology ultrasound is a key examination in obstetric monitoring that aims to assess fetal growth, identify any structural abnormalities, and inspect anexes such as placenta, umbilical cord, cervix,...
Several studies suggest that a significant proportion of fetal malformations can be detected during this time frame if a complete morphological analysis is performed. However, the reliability of the screening depends on the quality of the equipment, the operator's level of expertise, and adherence to protocols that define the necessary scans.
In France, since the first reports of the National Technical Committee on Prenatal Screening Ultrasound (2005), particular attention has been paid to standardizing practices. More recently, the French National Conference on Obstetric and Fetal Ultrasound (CNEOF) published new recommendations (2022, revised in 2023) including the development of reference silhouettes for the second-trimester examination, proposing 26 views (22 required and 4 additional). However, the CNEOF does not formalize quality criteria for evaluating the conformity of these images; this task has been taken over by the French College of Fetal Ultrasound (CFEF), which has established a scoring and validation grid for each fetal slice (see CFEF 2022 document).
In parallel, artificial intelligence (AI) is gradually becoming established as a decision support and automation tool in medical imaging, particularly in ultrasound. Deep learning algorithms are capable of identifying anatomical structures, positioning measurement markers, and selecting the most optimal slice, reducing inter-operator variability and streamlining workflow. In the field of obstetric ultrasound, some companies have launched systems capable of detecting or annotating fetal structures in real time, potentially improving diagnostic reliability and reproducibility. Samsung has developed a system called Live View Assist, available on its latest generation ultrasound scanners, which uses AI to automatically recognize and freeze the required fetal slices in real time.
The tool also offers automated validation: if the detected slice conforms to the expected standards, it is directly checked off on a checklist. This innovation promises time savings, a reduced risk of missing certain complex slices, and improved standardization.
However, there is little data, particularly in France, regarding to the actual performance of this tool in a routine screening context. Before considering the integration of Live View Assist and AI into daily practice, it is therefore essential to evaluate the quality of the images it acquires, the feasibility of a complete examination assisted by AI, as well as the potential impact on examination time and improvement of the workload for sonographers.
The aim of this study is to evaluate whether the quality of the 20 mandatory images automatically validated by Live View Assist is not inferior to that of the 20 mandatory images acquired and validated manually by an ultrasound technician, according to the CFEF quality criteria based on the silhouettes recommended by the CNEOF.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Standard ultrasound | Active comparator | Procedure: Standard UltrasoundManual acquisition: acquisition of the 22 mandatory images and, if possible, the 4 additional images by the sonographer, respecting the standardized procedure derived from the CNEOF recommendations. |
| Artificial intelligence-assisted ultrasound | Experimental | Procedure: US with AIAI-assisted acquisition: using the Live View Assist system to automatically capture the 20 mandatory views in real time, with validation and recording of images as soon as the algorithm detects an image conforming to the reference, and if possible the 2 complementary images. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Women aged 18 or over,
- With a single, viable pregnancy, definitively dated by first-trimester ultrasound, with no known malformations,
- Scheduled for a routine second-trimester screening ultrasound, i.e., between 20 weeks + 0 days and 24 weeks + 6 days,
- Having given their informed consent,
- Affiliated with the social security system or a beneficiary of such a plan.
Key exclusion criteria (7 listed)
- Multiple pregnancy,
- Known fetal malformation,
- Pathological pregnancy,
- Cognitive impairment, or a disorder causing difficulty understanding instructions or answering questionnaires,
- Patient under legal guardianship,
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Standard UltrasoundStandard US with a sonographer | Procedure or surgery | Standard ultrasound |
| US with AIUS with Live View Assist | Procedure or surgery | Artificial intelligence-assisted ultrasound |
Primary outcome
Images deemed "acceptable"
Time frame: through study completion, an average of 6 months
Images deemed acceptable (i.e., for each image, all criteria are rated as good or acceptable, with none being insufficient or poor). To evaluate the primary objective, the statistical unit will be the image. All 20 mandatory images for each patient will be analyzed
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Jul 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Standard Ultrasound and US with AI in people with Artifical Intelligence and Echography Ultrasound, run by Clinique Rive Gauche at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Images deemed "acceptable" (time frame: through study completion, an average of 6 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Jul 2026.