Ignite Creation Date:
2025-12-24 @ 2:39 PM
Ignite Modification Date:
2025-12-26 @ 1:33 PM
Study NCT ID:
NCT07197359
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2025-10-02
First Post:
2025-09-21
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Looksmaxxing AI for Chin Deviation Detection
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 90}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2025-09-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2025-10-15', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-29', 'studyFirstSubmitDate': '2025-09-21', 'studyFirstSubmitQcDate': '2025-09-21', 'lastUpdatePostDateStruct': {'date': '2025-10-02', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-09-29', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2025-09-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Accuracy of Looksmaxxing AI in Detecting Chin Deviation', 'timeFrame': 'At study completion (October 2025)', 'description': 'The proportion of correct classifications (presence or absence of chin deviation) made by the Looksmaxxing AI application compared to the clinical gold standard, expressed as a percentage.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['chin asymmetry', 'photographic analysis', 'artificial intelligence'], 'conditions': ['Mandibular Asymmetry']}, 'referencesModule': {'seeAlsoLinks': [{'url': 'https://bmcoralhealth.biomedcentral.com/articles/10.1186/s12903-022-02466-x', 'label': 'This article reports the use of deep learning for automatic classification of orthodontic photographs, providing methodological background relevant to AI-based facial asymmetry detection.'}]}, 'descriptionModule': {'briefSummary': 'This study aims to evaluate whether an artificial intelligence application called Looksmaxxing AI will be able to correctly identify chin deviation (chin asymmetry) from standard frontal facial photographs. A total of 540 photographs will be included in the study. The eye areas will be covered to protect identity. Each photo will be analyzed by the AI, and its answers will be compared with clinical reality. The accuracy of two versions of the software (Looksmaxxing 4o and 5) will be assessed. The results may help show whether simple photo-based analysis can support early detection of chin asymmetry, especially in areas with limited access to orthodontic examination.', 'detailedDescription': 'This observational study will investigate the accuracy of the Looksmaxxing AI application in detecting chin deviation based on standardized frontal facial photographs. A total of 540 images will be included. To protect identity, the eye areas of all participants will be covered. The AI will be asked to determine whether chin deviation is present relative to the midline of the face (excluding the nose).\n\nThe study population will consist of two equally sized groups:\n\n270 individuals with clinically observed chin deviation (laterognathia)\n\n270 individuals with clinically normal chin position\n\nThe responses provided by Looksmaxxing AI will be compared with the clinical reality and recorded for accuracy. Both versions of the software, Looksmaxxing 4o and Looksmaxxing 5, will be analyzed to evaluate their level of consistency with clinical findings. Results will be reported as accuracy percentages. In addition, prediction accuracy will be compared between individuals with and without chin deviation, and the statistical significance of the difference will be tested using the Chi-square method.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT'], 'maximumAge': '40 Years', 'minimumAge': '10 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Standardized frontal facial photographs of 90 individuals (540 images in total) will be analyzed. The study population consists of two equal groups: 270 photographs from individuals with clinically observed chin deviation (laterognathia) and 270 photographs from individuals with clinically normal chin position.', 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Absence of any craniofacial anomaly\n\nNo major wound or scar in the facial or neck region\n\nNo history of previous orthodontic treatment\n\nFor male participants: absence of a long beard that could affect the appearance of the chin\n\nAvailability of standardized frontal facial photographs taken in natural head position\n\nExclusion Criteria:\n\n* Photographs in which the patient's face appears slightly angled or turned sideways\n\nBlurred or low-quality photographs with reduced clarity"}, 'identificationModule': {'nctId': 'NCT07197359', 'briefTitle': 'Looksmaxxing AI for Chin Deviation Detection', 'organization': {'class': 'OTHER', 'fullName': 'Konya Necmettin Erbakan Üniversitesi'}, 'officialTitle': 'Detecting Asymmetry With Artificial Intelligence: Consistency Evaluation of the Looksmaxxing Application in Photo-Based Facial Analysis', 'orgStudyIdInfo': {'id': '2025/635'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'With Chin Deviation', 'description': 'Participants clinically diagnosed with chin deviation (laterognathia) based on frontal facial examination.', 'interventionNames': ['Other: Looksmaxxing AI Facial Analysis']}, {'label': 'Without Chin Deviation', 'description': 'Participants with clinically normal chin position confirmed by frontal facial examination.', 'interventionNames': ['Other: Looksmaxxing AI Facial Analysis']}], 'interventions': [{'name': 'Looksmaxxing AI Facial Analysis', 'type': 'OTHER', 'description': "Participants' standardized frontal facial photographs will be analyzed using the Looksmaxxing AI application (versions 4o and 5) to determine the presence or absence of chin deviation relative to the facial midline.", 'armGroupLabels': ['With Chin Deviation', 'Without Chin Deviation']}]}, 'contactsLocationsModule': {'locations': [{'zip': '42090', 'city': 'Konya', 'state': 'Konya', 'country': 'Turkey (Türkiye)', 'facility': 'Necmettin Erbakan University', 'geoPoint': {'lat': 37.87135, 'lon': 32.48464}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Individual participant data (facial photographs) will not be shared due to privacy concerns and the risk of re-identification. Only aggregated and anonymized results will be published.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Konya Necmettin Erbakan Üniversitesi', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Research assistant', 'investigatorFullName': 'Seda Sağoğlu', 'investigatorAffiliation': 'Konya Necmettin Erbakan Üniversitesi'}}}}