Ignite Creation Date:
2025-12-25 @ 4:51 AM
Ignite Modification Date:
2025-12-26 @ 3:52 AM
Study NCT ID:
NCT07246018
Status:
COMPLETED
Last Update Posted:
2025-11-24
First Post:
2025-11-14
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Accuracy and Reliability of Artificial Intelligence Cephalometric Analysis Software Compared to Manual Tracing
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2022-11-20', 'size': 640571, 'label': 'Study Protocol, Statistical Analysis Plan, and Informed Consent Form', 'hasIcf': True, 'hasSap': True, 'filename': 'Prot_SAP_ICF_000.pdf', 'typeAbbrev': 'Prot_SAP_ICF', 'uploadDate': '2025-11-17T22:25', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 40}, 'targetDuration': '6 Months', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2023-01-02', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-01', 'completionDateStruct': {'date': '2023-06-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-11-17', 'studyFirstSubmitDate': '2025-11-14', 'studyFirstSubmitQcDate': '2025-11-17', 'lastUpdatePostDateStruct': {'date': '2025-11-24', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-11-24', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2023-06-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Intraclass Correlation Coefficient (ICC) for repeated manual measurements', 'timeFrame': 'Baseline (T₀) and 4 weeks later (T₁)', 'description': 'ICC calculated for all 15 cephalometric measurements (8 angular and 7 linear) performed manually at two time points to assess intra-examiner reliability'}, {'measure': 'Intraclass Correlation Coefficient (ICC) for repeated AI measurements', 'timeFrame': 'Baseline (T₀) and 4 weeks later (T₁)', 'description': 'ICC calculated for all 15 cephalometric measurements performed by WeDoCeph software at two time points to assess consistency'}, {'measure': 'Mean differences between manual and AI-based measurements at T₀', 'timeFrame': 'Baseline (T₀)', 'description': 'Paired T-Test comparison of all 15 measurements between manual tracing and AI analysis at initial time point'}, {'measure': 'Mean differences between manual and AI-based measurements at T₁', 'timeFrame': '4 weeks', 'description': 'Paired T-Test comparison of all 15 measurements between manual tracing and AI analysis at 4-week time point'}], 'secondaryOutcomes': [{'measure': 'Angular Measurements', 'timeFrame': 'Baseline (T₀) and 4 weeks (T₁)', 'description': 'Comparison of angular cephalometric measurements between methods'}, {'measure': 'Linear Measurements', 'timeFrame': 'Baseline (T₀) and 4 weeks (T₁)', 'description': 'Comparison of linear cephalometric measurements between methods'}, {'measure': 'Inter-examiner Reliability', 'timeFrame': 'During calibration phase', 'description': '10% of radiographs were analyzed by three examiners to ensure inter-examiner agreement'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Cephalometry', 'Orthodontic', 'Cephalometric Analysis']}, 'referencesModule': {'references': [{'pmid': '31059836', 'type': 'RESULT', 'citation': 'Alqahtani H. Evaluation of an online website-based platform for cephalometric analysis. J Stomatol Oral Maxillofac Surg. 2020 Feb;121(1):53-57. doi: 10.1016/j.jormas.2019.04.017. Epub 2019 May 3.'}, {'pmid': '38999299', 'type': 'RESULT', 'citation': 'Kazimierczak W, Gawin G, Janiszewska-Olszowska J, Dyszkiewicz-Konwinska M, Nowicki P, Kazimierczak N, Serafin Z, Orhan K. Comparison of Three Commercially Available, AI-Driven Cephalometric Analysis Tools in Orthodontics. J Clin Med. 2024 Jun 26;13(13):3733. doi: 10.3390/jcm13133733.'}, {'pmid': '33028287', 'type': 'RESULT', 'citation': 'Lee JH, Yu HJ, Kim MJ, Kim JW, Choi J. Automated cephalometric landmark detection with confidence regions using Bayesian convolutional neural networks. BMC Oral Health. 2020 Oct 7;20(1):270. doi: 10.1186/s12903-020-01256-7.'}]}, 'descriptionModule': {'briefSummary': 'This study compares the accuracy and reliability of artificial intelligence (AI) software for analyzing dental X-rays to the traditional manual tracing method used by dentists.\n\nLateral cephalometric radiographs are special X-rays of the head used in orthodontics (teeth straightening) to measure jawbone positions, tooth angles, and facial proportions. Traditionally, orthodontists manually trace these X-rays using pencil and paper to identify key landmarks and make measurements. This manual method is time-consuming and can vary between different practitioners or even when the same practitioner measures twice.\n\nAI-based software can automatically identify these landmarks and perform measurements instantly. This study examined 40 dental X-rays to determine if the AI software (WeDoCeph) is as accurate and more reliable than manual tracing.\n\nEach X-ray was measured twice - once manually by a trained examiner and once by AI software - at two different times (4 weeks apart). The researchers compared 15 different measurements, including 8 angles and 7 distances, to assess accuracy and reliability.', 'detailedDescription': 'Lateral cephalometric analysis is essential for orthodontic diagnosis and treatment planning. The traditional manual tracing method involves identifying anatomical landmarks on radiographs using pencil, ruler, and protractor, which is subjective, time-consuming, and prone to intra- and inter-observer variability.\n\nThis diagnostic accuracy study evaluated the WeDoCeph AI-based cephalometric analysis software against conventional manual tracing. The study used a comparative repeated-measures design where each radiograph was analysed by both methods at two time points (T₀ and T₁, separated by 4 weeks) to assess both accuracy and reliability.\n\nSample size calculation was based on 95% power and a 0.05 significance level, resulting in 40 lateral cephalometric radiographs. All measurements included angular parameters (SNA, SNB, ANB, FMPA, MMPA, UIA, LIA, IIA) and linear parameters (A-N perpendicular, POG-N perpendicular, ANS-Me, SN, UFH, MxPI, MnPI).\n\nPaired T-Test will be employed as the statistical analysis method for comparisons and Intraclass Correlation Coefficient (ICC) for reliability assessment. The study aimed to determine whether AI-based cephalometric analysis provides sufficient accuracy and superior reliability for clinical application in orthodontic practice.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The study population consisted of radiographs from orthodontic patients at various stages of treatment, including both pretreatment (initial diagnostic) and post-treatment radiographs. All radiographs were high-quality digital or digitized lateral cephalograms suitable for landmark identification and measurement. Patients with surgical rigid fixations, orthodontic appliances visible on radiographs, or dental prostheses were excluded to ensure clear visualization of anatomical landmarks. Additionally, radiographs of very poor quality or from patients with diagnosed syndromes or craniofacial deformities were excluded to maintain consistency in anatomical structure assessment.\n\nThe unit of analysis is the cephalometric radiograph rather than individual patients, as each radiograph represents a single diagnostic assessment.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Pretreatment/post-treatment lateral cephalometric radiographs\n* High-quality cephalograms with visible anatomical landmarks\n\nExclusion Criteria:\n\n* Patients with surgical rigid fixations, orthodontic appliances and dental prostheses visible on radiographs\n* Very poor quality/diagnostically unacceptable radiographs\n* Patients with syndromes or with craniofacial deformities'}, 'identificationModule': {'nctId': 'NCT07246018', 'briefTitle': 'Accuracy and Reliability of Artificial Intelligence Cephalometric Analysis Software Compared to Manual Tracing', 'organization': {'class': 'OTHER', 'fullName': 'International Islamic University Malaysia'}, 'officialTitle': 'The Accuracy and Reliability of Orthodontic Cephalometry Analysis Using Web-Based Artificial Intelligence Program', 'orgStudyIdInfo': {'id': 'IREC 2023-045'}, 'secondaryIdInfos': [{'id': 'CHAIN 22-001-0001', 'type': 'OTHER_GRANT', 'domain': 'IIUM Kulliyyah of Dentistry Postgraduate CHAIN Grant'}]}, 'armsInterventionsModule': {'armGroups': [{'label': 'Orthodontic Patients with Lateral Cephalometric Radiographs', 'description': 'Lateral cephalometric radiographs from 40 orthodontic patients collected between January 2023 and June 2023 from the Orthodontic Specialist Clinic. Each radiograph was analyzed using both manual tracing and AI-based software (WeDoCeph) at two time points (initial and 4 weeks later)', 'interventionNames': ['Diagnostic Test: Manual Cephalometric Tracing', 'Diagnostic Test: AI-Based Cephalometric Analysis (WeDoCeph Software)']}], 'interventions': [{'name': 'Manual Cephalometric Tracing', 'type': 'DIAGNOSTIC_TEST', 'description': 'Conventional manual cephalometric analysis performed by trained examiner using traditional tracing technique. Lateral cephalometric radiographs are hand-traced in a darkened room using a view box for transillumination. A 25cm x 18cm radiographic film is used as the base, with a 21cm x 16cm matte acetate tracing paper taped over it. Hard and soft tissue cephalometric landmarks are manually identified and traced using a 0.3mm 2HB pencil. Angular measurements are obtained using a protractor, and linear measurements using a ruler. All 15 cephalometric measurements (8 angular: SNA, SNB, ANB, FMPA, MMPA, UIA, LIA, IIA; and 7 linear: A-N perpendicular, POG-N perpendicular, ANS-Me, SN, UFH, MxPI, MnPI) are calculated manually. Each radiograph is traced and analyzed twice at 4-week intervals by the same examiner to assess intra-examiner reliability.', 'armGroupLabels': ['Orthodontic Patients with Lateral Cephalometric Radiographs']}, {'name': 'AI-Based Cephalometric Analysis (WeDoCeph Software)', 'type': 'DIAGNOSTIC_TEST', 'description': 'Automated cephalometric analysis using WeDoCeph artificial intelligence-based software. Digital lateral cephalometric radiographs are imported as high-quality JPEG images into the software platform. The AI system automatically identifies and traces cephalometric landmarks using deep learning algorithms, then instantly generates all measurements based on the predefined parameters. The same 15 cephalometric measurements obtained in manual tracing (8 angular: SNA, SNB, ANB, FMPA, MMPA, UIA, LIA, IIA; and 7 linear: A-N perpendicular, POG-N perpendicular, ANS-Me, SN, UFH, MxPI, MnPI) are automatically calculated by the software. Each radiograph is analyzed twice at 4-week intervals using the previously uploaded digital images to assess reproducibility and consistency of the AI system. No manual landmark identification or measurement calculation is required.', 'armGroupLabels': ['Orthodontic Patients with Lateral Cephalometric Radiographs']}]}, 'contactsLocationsModule': {'locations': [{'zip': '25200', 'city': 'Kuantan', 'state': 'Pahang', 'country': 'Malaysia', 'facility': 'Orthodontic Specialist Clinic, Kulliyyah of Dentistry', 'geoPoint': {'lat': 3.8077, 'lon': 103.326}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Individual participant data will not be made publicly available to protect patient privacy and confidentiality. The study involves radiographic images and associated measurements from orthodontic patients. Even with de-identification, radiographic images may be potentially identifiable. Data sharing was not included in the original ethics approval and informed consent process. Aggregate summary data and statistical results are available in the published manuscript.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'International Islamic University Malaysia', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Assistant Professor Dr.', 'investigatorFullName': 'Siti Hajjar Nasir', 'investigatorAffiliation': 'International Islamic University Malaysia'}}}}