About this trial
Obstetric ultrasound represents the standard of care for the screening of the fetal anomalies. However, its performance is dependent upon several parameters including type of anomaly, gestational age, maternal habitus and skills of the examiner. The use of Artificial Intelligence (AI) in medical diagnostics has been suggested not only to reduce the inter- and intra-operator variability, but also to compress the required time necessary to perform routine tasks, hence optimizing healthcare resources. Fetal brain abnormalities are among the most challenging fetal congenital anomalies in terms of ultrasound diagnosis, prenatal counseling and management. The access to new sources of technology, i.e. AI, has the potential to improve recognition, detection and localization of brain malformations. Therefore, we propose to develop an AI-based software, which would be capable to recognize the brain structures at antenatal ultrasound and discriminate between normal and abnormal fetal brain anatomy through fully automatic data processing.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Women with singleton pregnancies undergoing ultrasound examination between 19+0 - 22+6 weeks of gestation
Disqualifiers
Women who did not have the second trimester screening scan at the settled gestational age.
Women in which a good visualization of the transventricular, transthalamic and transcerebellar plane of the fetal head was not technically possible.
Women who are not able to give the informed consent.
Trial population
All pregnant women undergoing second trimester screening scan in the participating centers who provide informed consent to enrolment
Trial design
Cohort
Other
Treatments tested in this trial
Development of AI algorithm for early detection of fetal brain anomalies in the second trimester screening scan
Diagnostic testDevelopment of AI algorithm for early detection of fetal brain anomalies in the second trimester of pregnancy
Treatment groups
Trial outcomes
Primary outcomes
AI algorithm
Number of cases detected with AI algorithm application
Secondary outcomes
Reproducibility
Number of cases detected with AI algorithm application compared with those detected with standard techniques of prenatal diagnosis
Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Lead sponsor
Ospedale Di Venere - Carbonara di Bari - Bari, Italy
Collaborator
Azienda Ospedaliero-Universitaria di Parma
Collaborator