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AIRFRAME: Artificial Intelligence for Recognition of Fetal bRain AnoMaliEs at Second Trime

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 su

Condition(s)Fetal Anomalies, Brain Malformation
StatusRecruiting
Study typeObservational
SummaryObstetric 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.
Who can participateInclusion Criteria: * Women with singleton pregnancies undergoing ultrasound examination between 19+0 - 22+6 weeks of gestation Exclusion Criteria: * 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.
Ages18 Years to 60 Years
SexFemale
Accepts healthy volunteersYes
Lead sponsorFondazione Policlinico Universitario Agostino Gemelli IRCCS
LocationsRome, Italy
Start date2023-04-30
NCT IDNCT06675266
Official listinghttps://clinicaltrials.gov/study/NCT06675266

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