Ignite Creation Date:
2025-12-24 @ 9:42 PM
Ignite Modification Date:
2025-12-29 @ 11:51 AM
Study NCT ID:
NCT06273332
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-02-22
First Post:
2024-02-05
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Assessment of the Artifical Intelligence Assisted Registration Versus Conventional Point Based Registration on Cone Beam-computed Tomography (CBCT) With Heavy Metal Artifacts
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NON_RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'OTHER', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 16}}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2023-12-20', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-02', 'completionDateStruct': {'date': '2024-02-25', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-02-14', 'studyFirstSubmitDate': '2024-02-05', 'studyFirstSubmitQcDate': '2024-02-14', 'lastUpdatePostDateStruct': {'date': '2024-02-22', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-02-22', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-01-20', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Registration accuracy', 'timeFrame': 'immediately after the procedure', 'description': 'Distance between registered 3d model and CBCT in millimeters'}], 'secondaryOutcomes': [{'measure': 'Duration for registration', 'timeFrame': 'During the procedure', 'description': 'time taken for registration procedure'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Point-based registration', 'AI registration', 'Accuracy', 'Digital implant planning'], 'conditions': ['Registration Accuracy']}, 'descriptionModule': {'briefSummary': 'Our study investigates the accuracy and duration needed for 3D model registration using artifical intelligence (AI) assistance compared to conventional point-based registration. Manual segmentation of all cone beam computed tomography (CBCT) scans will be performed before the registration procedure.', 'detailedDescription': 'CBCT images and intraoral scans will be screened following specific eligibility criteria. 16 CBCT images and intraoral scans that will meet the inclusion criteria will undergo manual segmentation via 3D medical image processing software. Afterward, point-based registration and AI-assisted registration will be performed by a single operator using specialized implant planning software. Then, the registration accuracy will be examined by measuring the distances between the three-dimensional models of CBCT data and intraoral scans. Also, the duration required for registration will be calibrated and recorded by a stopwatch.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'minimumAge': '15 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\nCBCT scans for either the maxilla or mandible or both and intraoral scans or manual impressions with metal restorations.\n\nExclusion Criteria:\n\nScans without metal restorations.'}, 'identificationModule': {'nctId': 'NCT06273332', 'briefTitle': 'Assessment of the Artifical Intelligence Assisted Registration Versus Conventional Point Based Registration on Cone Beam-computed Tomography (CBCT) With Heavy Metal Artifacts', 'organization': {'class': 'OTHER', 'fullName': 'Ain Shams University'}, 'officialTitle': 'Assessment of the AI-assisted Registration Versus Conventional Point-based Registration on CBCTs With Heavy Metal Artifacts', 'orgStudyIdInfo': {'id': 'AI surgery protocol'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'AI-assisted registration', 'description': '3D model registration will be carried out using artificial intelligence', 'interventionNames': ['Other: AI-assisted registration']}, {'type': 'ACTIVE_COMPARATOR', 'label': 'Point-based registration', 'description': '3D model registration will be carried out using point-based approach', 'interventionNames': ['Other: Point-based registration']}], 'interventions': [{'name': 'AI-assisted registration', 'type': 'OTHER', 'description': 'We will use artificial intelligence to register 3d model on intra-oral scan', 'armGroupLabels': ['AI-assisted registration']}, {'name': 'Point-based registration', 'type': 'OTHER', 'description': 'We will use five references points or more to perform model registration', 'armGroupLabels': ['Point-based registration']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Cairo', 'country': 'Egypt', 'facility': 'Private maxillofacial digital lab', 'geoPoint': {'lat': 30.06263, 'lon': 31.24967}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'no data will be shared'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Ain Shams University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'principal investigator', 'investigatorFullName': 'Nehal Ibrahim Ahmed Shobair', 'investigatorAffiliation': 'Ain Shams University'}}}}