Ignite Creation Date:
2025-12-24 @ 7:46 PM
Ignite Modification Date:
2025-12-29 @ 10:18 PM
Study NCT ID:
NCT05538403
Status:
UNKNOWN
Last Update Posted:
2022-09-13
First Post:
2022-09-09
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
AI Performance for the Detection of Bone Fractures in Children
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D050723', 'term': 'Fractures, Bone'}], 'ancestors': [{'id': 'D014947', 'term': 'Wounds and Injuries'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 210}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-05-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-09', 'completionDateStruct': {'date': '2022-12-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2022-09-09', 'studyFirstSubmitDate': '2022-09-09', 'studyFirstSubmitQcDate': '2022-09-09', 'lastUpdatePostDateStruct': {'date': '2022-09-13', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-09-13', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-11-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Percentage of fracture detected by AI on radiographs', 'timeFrame': '1 day', 'description': 'Percentage of fracture detected by AI on radiographs'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Aged', 'Radiography', 'Paediatric imaging', 'Artificial intelligence', 'child abuse'], 'conditions': ['Fracture']}, 'descriptionModule': {'briefSummary': 'The artificial intelligence (AI) software BoneView (GLEAMER Company, Paris, France) has been designed, tested and validated to detect and locate recent or semi-recent fractures on standard radiographs.\n\nThe objective will be to assess the AI performance for the detection of bone fractures in children aged less than 2 years old in suspected child abuse setting.\n\nThese patients benefit from a whole body radiography with a double blind reading by a "generalist" radiologist and a radiologist with expertise in child abuse. This readings will be compared with the AI results.\n\nHypothesis is that AI is effective for child fractures detection and could be of help especially for radiologists who are not experts in child abuse.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD'], 'maximumAge': '2 Years', 'minimumAge': '0 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Children aged less than 2 years old in suspected child abuse setting', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion criteria:\n\n* aged less than 2 years old\n* whole body radiography performed for suspected child abuse setting\n* report available with a double blind reading (generalist radiologist and radiologist with expertise in child abuse)\n\nExclusion criteria:\n\n* Radiograph not interpretable ( poor quality)\n* AI not applicable'}, 'identificationModule': {'nctId': 'NCT05538403', 'briefTitle': 'AI Performance for the Detection of Bone Fractures in Children', 'organization': {'class': 'OTHER', 'fullName': 'University Hospital, Montpellier'}, 'officialTitle': 'Assessment of AI Performance for the Detection of Bone Fractures in Children Aged Less Than 2 Years Old in Suspected Child Abuse Setting.', 'orgStudyIdInfo': {'id': 'RECHMPL22_0224'}}, 'contactsLocationsModule': {'locations': [{'zip': '34295', 'city': 'Montpellier', 'status': 'RECRUITING', 'country': 'France', 'contacts': [{'name': 'Ingrid Millet, PUPH', 'role': 'CONTACT', 'email': 'i-millet@chu-montpellier.fr', 'phone': '0678887174', 'phoneExt': '33'}], 'facility': 'University hospital', 'geoPoint': {'lat': 43.61093, 'lon': 3.87635}}], 'centralContacts': [{'name': 'Ingrid Millet, PUPH', 'role': 'CONTACT', 'email': 'i-millet@chu-montpellier.fr', 'phone': '678887174', 'phoneExt': '33'}], 'overallOfficials': [{'name': 'Ingrid Millet, PUPH', 'role': 'STUDY_DIRECTOR', 'affiliation': 'University Hospital, Montpellier'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED', 'description': 'NC'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University Hospital, Montpellier', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}