Preterm BirthNCT07598097
The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice
An observational study of Preterm Birth and Artificial Intelligence (AI) in Diagnosis, run by Copenhagen University Hospital, Rigshospitalet at 1 site in Denmark.
Trial summary
This study prospectively evaluates whether the performance of an already-developed artificial intelligence (AI) model for predicting spontaneous preterm birth changes when cervical ultrasound images are obtained using different ultrasound image settings. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Preterm Birth, Artificial Intelligence (AI) in Diagnosis
- What is being tested?
- Cervical ultrasound image acquisition
- How many people
- 2,000 participants
- Where
- 1 siteDenmark
- Study dates
- 11 Mar 2026to Feb 2027
- Phase
- Observational
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
- Adult, Older adult
Study population: Pregnant women attending routine second-trimester scan at Rigshospitalet from March to September, 2026.
Who may be able to join
- Pregnant women aged ≥18 years
- Attending routine second-trimester scan (and scheduled transvaginal cervical assessment per local protocol/workflow)
Who cannot join
- Absence of transvaginal cervical assessment at the second-trimester scan
- Missing follow-up data on pregnancy outcome (gestational age at delivery)
- Inadequate image quality or missing required cervical ultrasound image
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Denmark1 site, 1 recruiting
- Recruiting
Rigshospitalet, Copenhagen Univeristy Hospital
Copenhagen, 2100
Emilie Pi F Sejer, MD, 0045 28890690, emilie.pi.fogtmann.sejer.01@regionh.dk
About this study
Official title: The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice: A Prospective Observational Study
This study prospectively evaluates whether the performance of an already-developed artificial intelligence (AI) model for predicting spontaneous preterm birth changes when cervical ultrasound images are obtained using different ultrasound image settings.
The primary research question is whether the AI model performs differently across images acquired with different imaging settings.
- Being tested
- Cervical ultrasound image acquisition
- Keywords
- Preterm birth, Premature birth, Artificial intelligence, Deep learning, Image acquisition, Diagnostic accuracy, Cervical ultrasound, Prospective validation
- Medical subject headings
- Premature Birth
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Cervical ultrasound image acquisitionOther
Acquisition of cervical ultrasound images with variation in image acquisition parameters.
| Study group | Role | What they receive |
|---|---|---|
| Pregnant women attending routine second-trimester scan | Pregnant women aged ≥18 years attending routine second-trimester scan (and scheduled transvaginal cervical assessment per local protocol/workflow). Receives: Other: Cervical ultrasound image acquisition |
What is being measured
The primary outcome is the main question the study is designed to answer.
Spontaneous preterm birth <37+0 weeks
Birth <37+0 weeks after spontaneous onset of labor (with or without preterm prelabor rupture of membranes [PPROM]), regardless of mode of delivery, and excluding medically indicated (iatrogenic) preterm births without spontaneous onset.
Measured: At delivery.
Secondary outcomes (1)
Spontaneous preterm birth <34+0 and <32+0 weeks
Measured: At delivery.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 May 2026
- Study start11 Mar 2026
- Primary completionJan 2027 (estimated)
- Study completionFeb 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Preterm BirthStudies of the same condition, open and under way.
- More trials run by Copenhagen University Hospital, RigshospitaletThe sponsor's other registered studies.
- 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
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 2,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Copenhagen University Hospital, Rigshospitalet
- Sponsor type
- University, hospital or other
- Collaborators
- Department of Computer Science, University of Copenhagen, Denmark, Technical University of Denmark, Sundhedsdonationer
- Responsible party
- Principal investigator, Emilie Pi Fogtmann Sejer, Copenhagen University Hospital, Rigshospitalet
- Investigators
- Martin G Tolsgaard, MD, PhD, DMSc, Study chair, Department of Obstetrics and Gynecology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07598097
- Sponsor's protocol ID
- P-2026-21388
- Status last verified
- May 2026
- First submitted
- 12 May 2026
- Last updated
- 20 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided