Fetal ultrasound randomised trial of AI-assisted workflow for anomaly detection with health economic assessment
| ISRCTN | ISRCTN11223725 |
|---|---|
| DOI | https://doi.org/10.1186/ISRCTN11223725 |
| Integrated Research Application System (IRAS) | 355136 |
| Central Portfolio Management System (CPMS) | 71420 |
| Protocol serial number | R&D 1388 |
| Sponsor | King's College London |
| Funder | National Institute for Health and Care Research |
- Submission date
- 30/07/2025
- Registration date
- 19/02/2026
- Last edited
- 19/02/2026
- Recruitment status
- Recruiting
- Overall study status
- Ongoing
- Condition category
- Pregnancy and Childbirth
Plain English summary of protocol
Background and study aims
This study is exploring whether new computer-based tools can improve pregnancy ultrasound scans. In the UK, pregnant women are usually offered a detailed scan halfway through pregnancy to check how their baby is developing. However, some serious health conditions can be missed. Researchers have developed artificial intelligence (AI) tools that can help spot problems during the scan and support expert review afterwards. The aim is to find out if using both tools together helps detect more problems early and makes clinics run more efficiently.
Who can participate?
Around 9,500 pregnant people will be invited to take part in the study. Participation is entirely voluntary.
What does the study involve?
Participants will be randomly assigned to one of two groups. One group will receive the usual scan, while the other group will have a scan supported by AI and reviewed by an expert. Some participants may also be asked to complete a short survey or take part in an interview to share their views.
What are the possible benefits and risks of participating?
Taking part could help improve how pregnancy scans are done in the future and may lead to earlier detection of health problems in babies. There are no known risks beyond those of a standard scan. Participation will not affect the care participants receive.
Where is the study run from?
King’s College London (UK)
When is the study starting and how long is it expected to run for?
July 2025 to June 2027
Who is funding the study?
National Institute for Health and Care Research (NIHR) (UK)
Who is the main contact?
Professor Reza Razavi, reza.razavi@kcl.ac.uk
Contact information
Public, Scientific, Principal investigator
School of Biomedical Engineering and Imaging Sciences
King’s College London
9th floor, Becket House
Lambeth Palace Road
London
SE1 7EU
United Kingdom
 ORCID ID |
0000-0003-1065-3008 |
|---|---|
| Phone | +44 20 784 89587 |
| reza.razavi@kcl.ac.uk |
Study information
| Primary study design | Interventional |
|---|---|
| Study design | Balanced two-arm explanatory randomized controlled trial with parallel process evaluation |
| Secondary study design | Randomised controlled trial |
| Scientific title | Fetal ultrasound randomised trial of AI-assisted workflow for anomaly detection with health economic assessment |
| Study acronym | FRAIYA |
| Study objectives | Can an AI-enabled workflow for ultrasound screening of prenatal abnormalities, including second review, improve detection rates in a cost-effective way? Primary Outcomes: 1. Scan duration 2. Detection rate of congenital anomalies Secondary Outcomes: 3. Qualitative assessment of user and patient acceptability At the end of the study, we’ll know whether this technology helps detect serious conditions earlier, whether it’s acceptable to patients and staff, and whether it could be affordable for the NHS. We’ll share our findings through public summaries, press releases, and scientific conferences. |
| Ethics approval(s) |
Not yet submitted |
| Health condition(s) or problem(s) studied | Ultrasound screening of prenatal abnormalities |
| Intervention | Pregnant women will be recruited to participate in the trial at the time of their mid-trimester ultrasound anomaly scan. Each participant will be randomised (1 to 1) to have the scan either with AI-assistance (FraiyaScan), or in standard unassisted fashion. Those who have been randomised to AI-assistance will also have an AI-assistance secondary review of the scan (FraiyaDetect). The scan duration and detection rates of congenital anomalies between the two scanning methods will be compared. A parallel process evaluation will employ a convergent parallel design based on survey and interview data from service users (main trial service users) and the healthcare workforce (end user stakeholders). A parallel process evaluation will employ a convergent parallel design based on survey and interview data from service users (main trial service users) and the healthcare workforce (end user stakeholders). Interventional and control arms are both going to last 26 weeks from the initial participation (20 week antenatal scan) to final question about the newborn outcome at 6 weeks of age. Randomisation (1-1) is via a digital application provided by the clinical trials unit (KCL CTU) that runs on the tablet attached to the ultrasound machine. |
| Intervention type | Device |
| Phase | Not Applicable |
| Drug / device / biological / vaccine name(s) | FraiyaScan, FraiyaDetect |
| Primary outcome measure(s) |
1. Scan time in minutes (collected by the computer connected to the ultrasound machine that is recording the examination) |
| Key secondary outcome measure(s) |
There are no secondary outcome measures |
| Completion date | 30/06/2027 |
Eligibility
| Participant type(s) | Patient |
|---|---|
| Age group | Adult |
| Lower age limit | 18 Years |
| Upper age limit | 50 Years |
| Sex | Female |
| Target sample size at registration | 9566 |
| Key inclusion criteria | 1. Pregnant 2. All cases who are due for a routine mid-trimester (18-22 week) antenatal scan |
| Key exclusion criteria | 1. Any identified structural abnormality 2. Any genetic or chromosomal abnormality identified 3. Participant withdrawal 4. Refusal of consent 5. Insufficient English language skills to provide informed consent 6. Multiple pregnancies |
| Date of first enrolment | 01/10/2025 |
| Date of final enrolment | 01/10/2026 |
Locations
Countries of recruitment
- United Kingdom
- England
Study participating centres
London
SE1 7EH
England
London
SE13 6LH
England
Crown Street
Liverpool
L8 7SS
England
Barrack Road
Exeter
EX2 5DW
England
Results and Publications
| Individual participant data (IPD) Intention to share | Yes |
|---|---|
| IPD sharing plan summary | Published as a supplement to the results publication |
| IPD sharing plan | The datasets generated and/or analysed during the study will be published as a supplement to the results publication. |
Study outputs
| Output type | Details | Date created | Date added | Peer reviewed? | Patient-facing? |
|---|---|---|---|---|---|
| Study website | Study website | 11/11/2025 | 11/11/2025 | No | Yes |
Editorial Notes
30/07/2025: Trial's existence confirmed by the National Institute for Health and Care Research (NIHR) (UK).
