Ignite Creation Date:
2025-12-25 @ 2:37 AM
Ignite Modification Date:
2025-12-31 @ 10:33 AM
Study NCT ID:
NCT06879834
Status:
RECRUITING
Last Update Posted:
2025-03-17
First Post:
2025-03-11
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Assessing of Artificial Intelligence-based Software Platform for Diabetic Retinopathy Screening
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003930', 'term': 'Diabetic Retinopathy'}], 'ancestors': [{'id': 'D012164', 'term': 'Retinal Diseases'}, {'id': 'D005128', 'term': 'Eye Diseases'}, {'id': 'D003925', 'term': 'Diabetic Angiopathies'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D048909', 'term': 'Diabetes Complications'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 200}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2024-11-02', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-03', 'completionDateStruct': {'date': '2025-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-03-11', 'studyFirstSubmitDate': '2025-03-11', 'studyFirstSubmitQcDate': '2025-03-11', 'lastUpdatePostDateStruct': {'date': '2025-03-17', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-03-17', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-08', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The accuracy', 'timeFrame': 'Baseline', 'description': 'The accuracy of detecting of DR'}], 'secondaryOutcomes': [{'measure': 'The percent of invalid images', 'timeFrame': 'Baseline', 'description': 'The percent of invalid images for analysing by neural network'}, {'measure': 'The percent of false positive detection of DR', 'timeFrame': 'Baseline', 'description': 'The percent of false positive detection of DR in individuals without DR'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Diabetic Retinopathy', 'Fundus photo', 'nonmydriatic camera', 'Artificail Intelligence', 'CheckEye', 'Fundus image', 'fundus photography'], 'conditions': ['Diabetic Retinopathy']}, 'referencesModule': {'seeAlsoLinks': [{'url': 'https://ua.ozhurnal.com/index.php/files/article/view/101', 'label': 'Detecting diabetic retinopathy using an artificial intelligence-based software platform: a pilot study'}]}, 'descriptionModule': {'briefSummary': 'To examine the potential for the detection of diabetic retinopathy (DR) using the artificial intelligence (AI)-based software platform Retina-AI.', 'detailedDescription': 'Operator took fundus images with a non-mydriatic fundus camera as per the Retina-AI CheckEye imaging protocol (an optic disc centered image and a fovea centered image for each eye).Thereafter, operator uploaded fundus images in the AI system for processing by the neural network.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': '200 participants were planed to include in study, 100 of them had diabetes mellitus and 100 participants were as a control group have risk factors for diabetes mellitus.\n\nAll participants were selected for the study based on the following inclusion and exclusion criteria', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Documented diagnosis of diabetes mellitus by definition.\n2. Understanding of the Study and willingness and ability to sign informed consent\n3. Patient age 18 or above\n4. Diagnostic for diabetes: 4a) Type 1 diabetes of a lest 5 years of evolution; or 4b) Type 2 diabetes\n\nExclusion Criteria:\n\n-1. Patients under 18 years of age; 2. Failure to give informed consent; 3. Presence of retinal diseases - acquired disease: age-related macular degeneration (AMD), occlusion of retinal vessels (ORV), etc.; birth defects: coloboma of choroid or optic nerve disc, etc.; hereditary diseases: retinitis pigmentosa, angioid streaks of the retina, etc.\n\n4\\. A patient who has already undergone treatment (surgery, laser, etc.) for any disease of the retina: age-related macular degeneration (AMD), retinal vascular occlusion (ARV), etc. These patients should be excluded or allocated to a separate group.'}, 'identificationModule': {'nctId': 'NCT06879834', 'acronym': 'ARTDR', 'briefTitle': 'Assessing of Artificial Intelligence-based Software Platform for Diabetic Retinopathy Screening', 'organization': {'class': 'OTHER', 'fullName': 'The Filatov Institute of Eye Diseases and Tissue Therapy'}, 'officialTitle': 'Assessing of Artificial Intelligence-based Software Platform for Diabetic Retinopathy Screening', 'orgStudyIdInfo': {'id': '02.10.2024'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'main group', 'description': 'have diabetes mellitus', 'interventionNames': ['Device: taking fundus photos using non-mydriatic fundus camera']}, {'label': 'control group', 'description': 'have risk factors for developing diabetes mellitus', 'interventionNames': ['Device: taking fundus photos using non-mydriatic fundus camera']}], 'interventions': [{'name': 'taking fundus photos using non-mydriatic fundus camera', 'type': 'DEVICE', 'description': 'using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.', 'armGroupLabels': ['control group', 'main group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '65061', 'city': 'Odesa', 'status': 'RECRUITING', 'country': 'Ukraine', 'facility': 'The Filatov Institute of Eye Diseases and Tissue Therapy', 'geoPoint': {'lat': 46.48572, 'lon': 30.74383}}], 'centralContacts': [{'name': 'Andrii MD Korol, PhD', 'role': 'CONTACT', 'email': 'andrii.r.korol@gmail.com', 'phone': '380936327266'}, {'name': 'Olha MD Pohosian', 'role': 'CONTACT', 'email': 'olha.a.pohosian@gmail.com', 'phone': '380932084927'}], 'overallOfficials': [{'name': 'Andrii MD Korol, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'The Filatov Institute of Eye Diseases and Tissue Therapy'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'The Filatov Institute of Eye Diseases and Tissue Therapy', 'class': 'OTHER'}, 'collaborators': [{'name': 'CheckEye LLC', 'class': 'INDUSTRY'}, {'name': 'Oftacentro SA', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'MD, PhD, DMedSc,Prof', 'investigatorFullName': 'Andrii Korol, MD, PhD', 'investigatorAffiliation': 'The Filatov Institute of Eye Diseases and Tissue Therapy'}}}}