Ignite Creation Date:
2025-12-24 @ 10:52 PM
Ignite Modification Date:
2025-12-25 @ 8:21 PM
Study NCT ID:
NCT07108569
Status:
COMPLETED
Last Update Posted:
2025-08-07
First Post:
2024-08-08
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Ability of Physicians to Distinguish Real From Artificial Colon Polyp Images
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003111', 'term': 'Colonic Polyps'}], 'ancestors': [{'id': 'D007417', 'term': 'Intestinal Polyps'}, {'id': 'D011127', 'term': 'Polyps'}, {'id': 'D020763', 'term': 'Pathological Conditions, Anatomical'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE', 'maskingDescription': 'Participant does not know if pesented image is real or artificial'}, 'primaryPurpose': 'BASIC_SCIENCE', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 53}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2024-11-06', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-08', 'completionDateStruct': {'date': '2025-02-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-08-06', 'studyFirstSubmitDate': '2024-08-08', 'studyFirstSubmitQcDate': '2025-08-06', 'lastUpdatePostDateStruct': {'date': '2025-08-07', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-08-07', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-02-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Ability to detect artificial images as artificial', 'timeFrame': '6 months', 'description': 'The ability to recognise artificial images as being artificial, using an online questionnaire - binary question'}], 'secondaryOutcomes': [{'measure': 'Ability to detect real images as real', 'timeFrame': '6 months', 'description': 'The ability to recognise real images as being real using an online questionnaire - binary question'}, {'measure': 'Accuracy to correctly classify images', 'timeFrame': '6 months', 'description': 'Accuracy to correctly classify images using an online questionnaire'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Colonoscopy'], 'conditions': ['Colon Polyp', 'Colonic Adenoma']}, 'descriptionModule': {'briefSummary': 'Training in endoscopy is essential for the early detection of precursors of colorectal cancer. Up to now, this training has been carried out with image collections of findings and in practice when working on patients.\n\nThe investigators want to use artificial intelligence (AI) to better train doctors to recognise these precursors. By using generative AI, the investigators were able to create realistic images that comply with data protection regulations and whose content can be predefined. Parts of the image can also be regenerated so that it is possible to create different precancerous stages in the same place in the image.\n\nIn this study the investigators want to identify the ability of physicians to distinguish artificial from real polyp images.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Physicians with or without experience in colonoscopy'}, 'identificationModule': {'nctId': 'NCT07108569', 'acronym': 'LUTETIA1', 'briefTitle': 'Ability of Physicians to Distinguish Real From Artificial Colon Polyp Images', 'organization': {'class': 'OTHER', 'fullName': 'Wuerzburg University Hospital'}, 'officialTitle': 'Ability of Physicians to Distinguish Real From Artificial Colon Polyp Images', 'orgStudyIdInfo': {'id': '2022120701'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Image assessment', 'description': 'Physicians judge whether the random image presented to them is real or artificial', 'interventionNames': ['Other: Lutetia']}], 'interventions': [{'name': 'Lutetia', 'type': 'OTHER', 'description': 'Lutetia is an AI-based training plattform', 'armGroupLabels': ['Image assessment']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Würzburg', 'country': 'Germany', 'facility': 'University hospital Würzburg b', 'geoPoint': {'lat': 49.79391, 'lon': 9.95121}}], 'overallOfficials': [{'name': 'Alexander Hann, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Wuerzburg University Hospital'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Wuerzburg University Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}