Ignite Creation Date:
2025-12-24 @ 3:54 PM
Ignite Modification Date:
2025-12-28 @ 2:50 PM
Study NCT ID:
NCT06268392
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-02-22
First Post:
2024-02-13
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
A Comparative Study of AI Methods for Fetal Diagnostic Accuracy in Ultrasound
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D005317', 'term': 'Fetal Growth Retardation'}, {'id': 'D005320', 'term': 'Fetal Macrosomia'}], 'ancestors': [{'id': 'D005315', 'term': 'Fetal Diseases'}, {'id': 'D011248', 'term': 'Pregnancy Complications'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D009358', 'term': 'Congenital, Hereditary, and Neonatal Diseases and Abnormalities'}, {'id': 'D006130', 'term': 'Growth Disorders'}, {'id': 'D010335', 'term': 'Pathologic Processes'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D016640', 'term': 'Diabetes, Gestational'}, {'id': 'D011254', 'term': 'Pregnancy in Diabetics'}, {'id': 'D048909', 'term': 'Diabetes Complications'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D001724', 'term': 'Birth Weight'}, {'id': 'D001835', 'term': 'Body Weight'}, {'id': 'D012816', 'term': 'Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 150}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2024-02-15', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-02', 'completionDateStruct': {'date': '2024-08-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-02-21', 'studyFirstSubmitDate': '2024-02-13', 'studyFirstSubmitQcDate': '2024-02-13', 'lastUpdatePostDateStruct': {'date': '2024-02-22', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-02-20', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-08-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Fetal weight', 'timeFrame': '10 minutes', 'description': 'Estimation of fetal weight, generated from AI analysis of fetal ultrasound images.'}, {'measure': 'Ultrasound fetal weight estimation', 'timeFrame': '15 minutes', 'description': 'Estimation of fetal weight, calculated from hadlock formula with information from the three standard planes of the head, abdomen and femur.'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Artificial Intelligence', 'Fetal weight estimation', 'Ultrasound'], 'conditions': ['Fetal Growth Retardation', 'Fetal Macrosomia', 'Fetal Growth']}, 'descriptionModule': {'briefSummary': 'This study serves as a supplemental investigation to the randomized controlled SCAN-AID study (NCT0632187). This study will evaluate and compare the fetal growth estimation outcomes of AI-supported groups, expert sonographers, and control groups using a secondary AI predictive model.', 'detailedDescription': 'The goal of this study is to compare the effects of two distinct AI methods on fetal ultrasound diagnostic accuracy. It serves as a supplementary investigation to the SCAN-AID study (NCT NCT06232187). This study aims will compare the diagnostic accuracy of two types of AI methods.\n\nFrom the SCAN-AID study ultrasound novices were randomized into one of three groups with different levels of AI support: control group, AI feedback group 1 where the participants are presented with basic black box AI feedback, and AI feedback group 2 where the participants are presented with a more detailed explainable AI feedback. All the participants are tasked to perform an ultrasound fetal weight estimation (EFW) on pregnant women at gestational age 30-37. The outcomes were than compared to the expert sonographers measurements.\n\nIn this study an operator independent AI method that predicts the fetal weight is used on the SCAN-AID ultrasound examinations. .'}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Medical students are recruited from the Medical universities in Denmark (mainly Copenhagen University) Pregnant women are chosen from the fetal medical departement at Rigshospitalet, Copenhagen.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Pregnant women:\n\nInclusion Criteria:\n\n* Singelton pregnant.\n* Gestational age: 30-38 weeks\n* Maternal age \\< 40 years\n\nExclusion Criteria:\n\n* Oligo hydramnion\n* Severe fetal anomaly e.g. fetal heart anomaly, omphalocele etc.\n* Severe fetal macrosomia or growth restriction.'}, 'identificationModule': {'nctId': 'NCT06268392', 'briefTitle': 'A Comparative Study of AI Methods for Fetal Diagnostic Accuracy in Ultrasound', 'organization': {'class': 'OTHER', 'fullName': 'Copenhagen Academy for Medical Education and Simulation'}, 'officialTitle': 'A Comparative Study of AI Methods for Fetal Diagnostic Accuracy in Ultrasound', 'orgStudyIdInfo': {'id': 'CT-2023-11-20-001'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Expert sonographer', 'description': 'Expert sonographers ultrasound examination.'}, {'label': 'Control Group (CG)', 'description': 'Control group ultrasound examination with no AI support.'}, {'label': 'Feedback group 1 (FG1)', 'description': 'Feedback group 1 ultrasound examination with basic black box AI support.'}, {'label': 'Feedback group 2 (FG2)', 'description': 'Feedback group 2 ultrasound examination with detailed explainable AI support.'}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Mary L Ngo', 'role': 'CONTACT', 'email': 'mary.van.anh.le.ngo@regionh.dk', 'phone': '+4520773779'}, {'name': 'Martin Tolsgaard', 'role': 'CONTACT', 'email': 'martin.groennebaek.tolsgaard@regionh.dk', 'phone': '+4538664631'}], 'overallOfficials': [{'name': 'Martin Tolsgaard', 'role': 'STUDY_DIRECTOR', 'affiliation': 'CAMES rigshopsitalet'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Copenhagen Academy for Medical Education and Simulation', 'class': 'OTHER'}, 'collaborators': [{'name': 'Slagelse Hospital', 'class': 'OTHER'}, {'name': 'Technical University of Denmark', 'class': 'OTHER'}, {'name': 'Rigshospitalet, Denmark', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'PhD student', 'investigatorFullName': 'Mary Le Ngo', 'investigatorAffiliation': 'Copenhagen Academy for Medical Education and Simulation'}}}}