[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"fetal-anomalies\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:fetal-anomalies":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,45],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":20,"enrollmentInfo":21,"targetDuration":4,"studyType":24,"phases":4,"briefSummary":25,"conditions":26,"keywords":29,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":33,"lastUpdatePostDateStruct":34,"startDateStruct":37,"completionDateStruct":39,"leadSponsor":41,"locationsCount":44},"100567981","airframe-artificial-intelligence-for-recognition-of-fetal-brain-anomalies-at-second-trimester-fetal-brain-scan-100567981",false,"NCT06675266","AIRFRAME: Artificial Intelligence for Recognition of Fetal bRain AnoMaliEs at Second Trimester Fetal Brain Scan","Development of an Artificial Intelligence Algorithm to Recognize Abnormal Findings at Routine Fetal Brain Ultrasound. AIRFRAME (Artificial Intelligence for Recognition of Fetal bRain AnoMaliEs)","AIRFRAME","Inclusion Criteria:\n\n* Women with singleton pregnancies undergoing ultrasound examination between 19+0 - 22+6 weeks of gestation\n\nExclusion Criteria:\n\n* Women who did not have the second trimester screening scan at the settled gestational age.\n* Women in which a good visualization of the transventricular, transthalamic and transcerebellar plane of the fetal head was not technically possible.\n* Women who are not able to give the informed consent.",true,"FEMALE","18 Years","60 Years",{"count":22,"type":23},10000,"ESTIMATED","OBSERVATIONAL","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.",[27,28],"Fetal Anomalies","Brain Malformation",[30,28,31],"Fetal Brain Anomaly","Second trimester ultrasound Scan","RECRUITING","2024-11-04",{"date":35,"type":36},"2024-11-05","ACTUAL",{"date":38,"type":36},"2023-04-30",{"date":40,"type":23},"2026-12-30",{"name":42,"class":43},"Fondazione Policlinico Universitario Agostino Gemelli IRCCS","OTHER",1,{"id":46,"slug":47,"hasResults":11,"nctId":48,"briefTitle":49,"officialTitle":50,"acronym":4,"eligibilityCriteria":51,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":52,"targetDuration":4,"studyType":24,"phases":4,"briefSummary":54,"conditions":55,"keywords":4,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":59,"lastUpdatePostDateStruct":60,"startDateStruct":62,"completionDateStruct":64,"leadSponsor":66,"locationsCount":44},"100266176","biobank-on-prematurity-preeclampsia-and-other-pregnancy-complications-100266176","NCT02744365","Biobank on Prematurity, Preeclampsia and Other Pregnancy Complications","Biobank of Data and of Human Biological Samples on Prematurity, Preeclampsia and Other Pregnancy Complications","Inclusion Criteria:\n\n* (specific to each study)\n\nExclusion Criteria:\n\n* pregnant women \\\u003C18 years old at recruitment\n* negative fetal heart at recruitment\n* women not able to provide an informed consent to the study",{"count":53,"type":23},7845,"The Biobank includes data and biological specimens of women from three original studies: 1) First-trimester Prediction of Preeclampsia (PREDICTION Study, NCT02189148), 2) Pre-Eclampsia And growth Retardation, an evaluative Longitudinal study (PEARL Study, NCT02379832), 3) Effect of Low Dose Aspirin on Birthweight in Twins: The GAP Trial (NCT02280031) and 4)PREDICTION2: Prediction of Preeclampsia and other Pregnancy Complications Following Combined Iterative Screening.",[56,57,58,27],"Preeclampsia","Preterm Birth","Pregnancy Complications","2022-03-14",{"date":61,"type":36},"2022-03-16",{"date":63,"type":36},"2015-04",{"date":65,"type":23},"2028-04",{"name":67,"class":43},"CHU de Quebec-Universite Laval"]