Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 40}, 'targetDuration': '3 Months', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2023-10-08', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-09', 'completionDateStruct': {'date': '2024-03-08', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-09-07', 'studyFirstSubmitDate': '2023-09-07', 'studyFirstSubmitQcDate': '2023-09-07', 'lastUpdatePostDateStruct': {'date': '2023-09-14', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-09-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-03-08', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Application of Artificial Intelligence Deep Learning Technology in Magnetic Resonance Lumbar Imaging', 'timeFrame': '2025.3-2025.6', 'description': 'manuscript'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Deep Learning,Lumbar Magnetic Resonance Imaging']}, 'descriptionModule': {'briefSummary': 'To study the comparative analysis of artificial intelligence deep learning technology in the image quality of under-artificial intelligence (AI) reconstruction images and the original acquisition images of magnetic resonance lumbar spine'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients of both sexes, aged ≥18 years, with no history of lumbar surgery, underwent lumbar magnetic resonance imaging examination.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Patients of both sexes, aged ≥18 years, with no history of lumbar surgery, underwent lumbar magnetic resonance imaging examination.\n\nExclusion Criteria:\n\n* With metal implants in the body, claustrophobic, unable to lie flat for 15 minutes, with a history of lumbar surgery.'}, 'identificationModule': {'nctId': 'NCT06037057', 'briefTitle': 'Application of Artificial Intelligence Deep Learning Technology in Magnetic Resonance Lumbar Imaging', 'organization': {'class': 'OTHER', 'fullName': 'RenJi Hospital'}, 'officialTitle': 'Application of Artificial Intelligence Deep Learning Technology in Magnetic Resonance Lumbar Imaging', 'orgStudyIdInfo': {'id': 'LY2023-121-B'}}, 'armsInterventionsModule': {'interventions': [{'name': 'no intervention name', 'type': 'OTHER', 'description': 'no intervention description'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'RenJi Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}