[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100641551":3},{"organization":4,"outcomesModule":7,"designInfo":18,"detailedDescription":17,"studyPopulation":21,"armGroups":22,"interventions":28,"overallOfficials":34,"centralContacts":38,"locations":44,"responsibleParty":129,"collaborators":131,"id":134,"slug":135,"hasResults":136,"nctId":137,"briefTitle":138,"officialTitle":139,"acronym":17,"eligibilityCriteria":140,"healthyVolunteers":136,"sex":141,"minAge":142,"maxAge":17,"enrollmentInfo":143,"targetDuration":17,"studyType":146,"phases":17,"briefSummary":147,"conditions":148,"keywords":17,"overallStatus":66,"whyStopped":17,"lastUpdateSubmitDate":153,"lastUpdatePostDateStruct":154,"startDateStruct":157,"completionDateStruct":159,"leadSponsor":161,"locationsCount":162},{"fullName":5,"class":6},"University of North Carolina, Chapel Hill","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":17},[9],{"measure":10,"description":11,"timeFrame":12},"Difference in Mean Absolute Percent Error (MAPE) in fetal weight estimation","Mean of pairwise differences in absolute percent error between the AI diagnostic tool (index test) and specialist biometry (clinical reference standard), compared against actual birthweight (ground truth).","Within 1 week of delivery, 24-42 weeks of gestation",[14],{"measure":15,"description":16,"timeFrame":12},"Proportion of fetal weight estimates within 10% of actual birthweight","Between-method difference in the proportion of estimates within 10% of actual birthweight (ground truth) for the AI diagnostic tool (index test) versus specialist biometry (clinical reference standard).",null,{"allocation":17,"interventionModel":17,"interventionModelDescription":17,"primaryPurpose":17,"observationalModel":19,"timePerspective":20,"maskingInfo":17},"COHORT","PROSPECTIVE","1,000 pregnant individuals",[23],{"label":24,"type":17,"description":25,"interventionNames":26},"Pregnant Women within One Week of Delivery","Participants receive a standardized ultrasound sweep protocol and specialist-performed fetal biometry.",[27],"Diagnostic Test: AI ultrasound diagnostic tool for fetal weight estimation",[29],{"type":30,"name":31,"description":32,"armGroupLabels":33,"otherNames":17},"DIAGNOSTIC_TEST","AI ultrasound diagnostic tool for fetal weight estimation","Participants will undergo study-specific transabdominal ultrasound acquisition using standardized abdominal sweeps of the gravid abdomen, guided by external maternal landmarks and saved as cineloop videos. The cineloop videos will be analyzed by a locked deep-learning AI diagnostic tool to generate an estimated fetal weight. The AI-generated estimate will be compared with specialist-performed fetal biometry and actual birth weight to evaluate diagnostic accuracy. The AI output is for research evaluation only and will not direct clinical management during the study.",[24],[35],{"name":36,"affiliation":5,"role":37},"Jeffrey Stringer, MD","PRINCIPAL_INVESTIGATOR",[39],{"name":40,"role":41,"phone":42,"phoneExt":17,"email":43},"Jeffrey R Stringer, MD","CONTACT","919-962-4717","jeff_stringer@unc.edu",[45,64,83,99,114],{"facility":46,"status":47,"city":48,"state":49,"zip":50,"country":51,"countryCode":52,"cosmosGeoPoint":53,"geoPoint":58,"contacts":59},"Ochsner Health","NOT_YET_RECRUITING","New Orleans","Louisiana","70115","United States","US",{"type":54,"coordinates":55},"Point",[56,57],-90.07507,29.95465,{"lat":57,"lon":56},[60],{"name":61,"role":41,"phone":62,"phoneExt":17,"email":63},"Will Williams, MD","504-842-5574","frank.williams2@ochsner.org",{"facility":65,"status":66,"city":67,"state":68,"zip":69,"country":51,"countryCode":52,"cosmosGeoPoint":70,"geoPoint":74,"contacts":75},"University of North Carolina","RECRUITING","Chapel Hill","North Carolina","27516",{"type":54,"coordinates":71},[72,73],-79.05584,35.9132,{"lat":73,"lon":72},[76,80],{"name":77,"role":41,"phone":78,"phoneExt":17,"email":79},"Katelyn J Rittenhouse, MD","919-966-5281","katelyn_rittenhouse@med.unc.edu",{"name":81,"role":41,"phone":78,"phoneExt":17,"email":82},"Jeffrey S.A. Stringer, MD","jeffrey_stringer@med.unc.edu",{"facility":84,"status":47,"city":85,"state":86,"zip":17,"country":87,"countryCode":88,"cosmosGeoPoint":89,"geoPoint":93,"contacts":94},"University of Saskatchewan","Saskatoon","Saskatchewan","Canada","CA",{"type":54,"coordinates":90},[91,92],-106.66892,52.13238,{"lat":92,"lon":91},[95],{"name":96,"role":41,"phone":97,"phoneExt":17,"email":98},"Scott Adams, MD, PhD","(306) 655-2402","scott.adams@usask.ca",{"facility":100,"status":47,"city":101,"state":17,"zip":17,"country":102,"countryCode":103,"cosmosGeoPoint":104,"geoPoint":108,"contacts":109},"University of Rwanda","Kigali","Rwanda","RW",{"type":54,"coordinates":105},[106,107],30.05885,-1.94995,{"lat":107,"lon":106},[110],{"name":111,"role":41,"phone":112,"phoneExt":17,"email":113},"Stephen Rulisa, MD, PhD","+250788571436","s.rulisa@gmail.com",{"facility":115,"status":47,"city":116,"state":17,"zip":17,"country":117,"countryCode":118,"cosmosGeoPoint":119,"geoPoint":123,"contacts":124},"University Teaching Hospital","Lusaka","Zambia","ZM",{"type":54,"coordinates":120},[121,122],28.28713,-15.40669,{"lat":122,"lon":121},[125],{"name":126,"role":41,"phone":127,"phoneExt":17,"email":128},"Margaret Kasaro, MBChB, MMed, MSc","+260963223210","margaret.kasaro@unclusaka.org",{"type":130,"investigatorFullName":17,"investigatorTitle":17,"investigatorAffiliation":17,"oldNameTitle":17,"oldOrganization":17},"SPONSOR",[132],{"name":133,"class":6},"Bill and Melinda Gates Foundation","100641551","prospective-evaluation-of-an-ai-diagnostic-ultrasound-tool-for-fetal-weight-estimation-100641551",false,"NCT07661433","Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation","Z 32503 - Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation","Inclusion Criteria:\n\n* 18 years of age or older\n* Viable intrauterine pregnancy\n* Delivery expected within one week of study procedures between 24 0\u002F7 and 42 6\u002F7 weeks, including participants with a scheduled induction or cesarean delivery on a known date, or those admitted in spontaneous labor\n* Ability and willingness to provide written informed consent\n* Willingness to comply with all study procedures\n\nExclusion Criteria:\n\n* Maternal body mass index ≥ 40 kg\u002Fm\\^2\n* Multiple gestation (i.e., twins or higher order)\n* Known major fetal malformation or anomaly\n* Any maternal condition (medical, psychological, or social) that, in the opinion of the study team, may interfere with study participation or data integrity.","FEMALE","18 Years",{"count":144,"type":145},1000,"ESTIMATED","OBSERVATIONAL","Purpose: The primary objective of this study is to assess the diagnostic accuracy of an AI-enabled ultrasound tool for estimating fetal weight Participants: 1,000 pregnant individuals Procedures (methods): This prospective diagnostic accuracy study will enroll 1,000 pregnant individuals within one week of anticipated delivery. At a single visit, each participant will undergo two ultrasound assessments: (1) standardized sweeps for AI analysis (performed by both specialist and nonspecialist users), (2) specialist-performed fetal biometry.",[149,150,151,152],"Fetal Weight","Pregnancy","Machine Learning","Pregnancy - Prenatal Testing","2026-07-06",{"date":155,"type":156},"2026-07-08","ACTUAL",{"date":158,"type":156},"2026-06-29",{"date":160,"type":145},"2026-12",{"name":5,"class":6},5]