Ignite Creation Date:
2025-12-24 @ 11:56 PM
Ignite Modification Date:
2025-12-25 @ 9:52 PM
Study NCT ID:
NCT05903651
Status:
COMPLETED
Last Update Posted:
2024-12-13
First Post:
2023-06-05
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Retinal Deep PhenotypingTM
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 813}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2023-04-03', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-12', 'completionDateStruct': {'date': '2024-03-14', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2024-12-09', 'studyFirstSubmitDate': '2023-06-05', 'studyFirstSubmitQcDate': '2023-06-05', 'lastUpdatePostDateStruct': {'date': '2024-12-13', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-06-15', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-03-14', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'At least one (1) pre-trained DL model from hyperspectral retinal images.', 'timeFrame': '12 months'}, {'measure': 'Report describing the clinical utility of visual inspection of the MHRC retinal images.', 'timeFrame': '12 months'}, {'measure': 'Review of any safety events (AE, SAE, UADEs) that occur throughout the study.', 'timeFrame': '12 months'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Healthy']}, 'descriptionModule': {'briefSummary': 'This study aims to collect a baseline dataset of MHRC retinal scans that will be used for the pre-training of deep learning models from the hyperspectral retinal image phenotypic features that may form the basis for multiple future classification applications. A sub-set of the images will also be analyzed by eye specialists to determine if visual inspection of the images could provide useful information in their practice.\n\nAs an exploratory study, there are no endpoints per se, however the following sub-objective will be evaluated for determining the success of this study:\n\n* Collection and characterization of MHRC retinal images from at least 2000 participants that score at least 80 on the real-time Quality Index (included in the MHRC software).\n* Development of at least one (1) DL model of the retina. Models may be used for the development of novel classifier tests and potential use in a clinical setting.\n* At least 5% of participants shall have an MHRC retinal image reviewed by an eye specialist (Optometrist or Ophthalmologist) to assess the image quality and potential clinical usefulness.', 'detailedDescription': 'This is an exploratory, observational, cross-sectional, multi-site study designed to collect a baseline dataset of MHRC retinal image scans for use in Deep Learning models and to determine the feasibility of visual inspection of the images for use in Optometry and/or Ophthalmology clinical practice. Subjects will be recruited from eye clinics where patients will undergo mydriasis (pupil dilation) as part of their clinical visit. Eligible participants will be provided information about the study and delegated site personnel will assist with the Informed Consent process. If a participant provides their Informed Consent, they will be enrolled in the study and undergo a single retinal imaging session with the Optina MHRC device, on one or both eyes.\n\nThe MHRC retinal images will be transferred to a Picture Archiving and Communication System (PACS) for archiving and later evaluation. Additional information about the Study Participant will be captured in an Electronic Data Capture (EDC) system, including age, date of birth, gender, race/ethnicity, and color of their iris.\n\nImages will be transferred to Optina for further digital analysis, including pre-processing (normalization, registration, and segmentation), feature extraction, and inclusion in Deep Learning models.\n\nA subset (at least 5%) of the MHRC retinal scans will undergo visual inspection by an eye specialist (Ophthalmologist or Optometrist) to determine their quality and utility for inclusion in clinical practice.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Adults ages 18 years and older who have undergone pupil dilation and are not contraindicated for mydriatic imaging with a fundus camera. Ideally, the study population will be reflective of the adult population with the following estimates for demographics.\n\nGender\\* 49% Male 51% Female\n\nAge\\* 45% 18-44 years old 55% 44+ years old\n\nOcular Health ǂ 70% Normal ocular health 30% Eye symptoms\n\n\\* based on 2021 Canada census data ǂ based on CNIB Fast Facts about Vision Loss', 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria:\n\n• Adults 18 years and older who will undergo mydriasis (pupil dilation) as part of their eye clinic visit.\n\nExclusion Criteria:\n\n* Pupil dilation contraindicated (due to a pathology, or presence of 3 quadrants with Van Herick grading of 0 or 1 without iridotomy).\n* Inadequate pupil dilatation (\\< 6mm diameter) preventing uniform illumination of the retina with the MHRC.\n* Refractive error outside the range of -15 D to +15 D.\n* Deficient visual fixation (inability to fixate for at least 2 s)\n* Inability of obtaining at least 3 images of satisfactory quality with the MHRC per the Optina Diagnostics quality index software and /or per the eye specialists' evaluation."}, 'identificationModule': {'nctId': 'NCT05903651', 'briefTitle': 'Retinal Deep PhenotypingTM', 'organization': {'class': 'INDUSTRY', 'fullName': 'Optina Diagnostics Inc.'}, 'officialTitle': 'Retinal Deep PhenotypingTM by a Novel Mydriatic Hyperspectral Retinal Camera (MHRC) and Analysis by Deep Learning', 'orgStudyIdInfo': {'id': '22-002'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Single Group Assignment', 'description': 'The subjects will undergo a single retinal imaging session with the Optina MHRC device, on one or both eyes.'}]}, 'contactsLocationsModule': {'locations': [{'zip': 'H3T 1P1', 'city': 'Montreal', 'state': 'Quebec', 'country': 'Canada', 'facility': "Ecole d'Optometrie, University of Montreal", 'geoPoint': {'lat': 45.50884, 'lon': -73.58781}}, {'zip': 'QC J7H 0E8', 'city': 'Montreal', 'state': 'Quebec', 'country': 'Canada', 'facility': "Clinique d'Opthalmologie desLaurentides, Institue de l'Oeil (IOL)", 'geoPoint': {'lat': 45.50884, 'lon': -73.58781}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Optina Diagnostics Inc.', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}