An observational study in Cephalometric Analysis, Cephalometry and Artificial Intelligence (AI), sponsored by University of Pavia. Recruiting at 1 site in Italy. Per ClinicalTrials.gov, last updated 2026-06-24.
Sponsored by University of Pavia · Observational
This study aims to evaluate the accuracy and reliability of artificial intelligence (AI)-based cephalometric analysis compared with digital manual tracing. A total of 100 standardized lateral cephalometric radiographs will be analyzed using Delta-Dent software with manual landmark identification and three fully automated AI-based systems (WebCeph, QuantX, and Smartee). Sagittal, vertical, dental, and soft tissue cephalometric parameters will be compared among the different methods. Statistical analysis will assess inter-method agreement and the clinical relevance of any observed discrepancies. The study seeks to determine whether AI-based systems provide measurements comparable to conventional digital tracing and whether they can be considered reliable adjunctive tools in orthodontic diagnosis and treatment planning.
This prospective observational study aims to evaluate the accuracy, reproducibility, and clinical reliability of artificial intelligence (AI)-based cephalometric analysis systems compared with digital manual tracing. Patients whose lateral cephalometric radiographs were previously acquired for orthodontic diagnostic purposes at the Unit of Orthodontics and Paediatric Dentistry, University of Pavia, will be retrospectively selected according to predefined inclusion and exclusion criteria. Written informed consent for the use of clinical records for research purposes will be obtained from all participants or their legal guardians. A total of 100 standardized digital lateral cephalometric radiographs will be included in the study. Each radiograph will be analysed using Delta-Dent software with manual landmark identification and three fully automated AI-based software systems: WebCeph™, QuantX, and Smartee. Cephalometric analyses will be performed without manual adjustment of landmarks in the AI-based systems. Ten cephalometric parameters representative of sagittal, vertical, dental, and soft tissue relationships will be evaluated, including SNA, SNB, ANB, SN-GoGn, L1-GoGn, U1-ANSPNS, nasolabial angle, facial angle, Wits appraisal, and N-Me. Manual digital tracing performed by a single experienced orthodontist will be considered the reference method. Intra-rater reliability will be assessed using intraclass correlation coefficient (ICC). Statistical analysis will be conducted using R software (version 3.1.3; R Foundation for Statistical Computing, Wien, Austria). Descriptive statistics will be calculated for all variables. Normality of data distribution will be assessed using the Kolmogorov-Smirnov test. Comparisons among the different methods will be performed using the Friedman test followed by Dunn's post hoc test. Statistical significance will be predetermined at p \< 0.05.
University of Pavia is the lead sponsor of 144 studies on the registry; 39 are open to participants now.
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The study population consists of patients of any age and sex who underwent digital lateral cephalometric radiography as part of routine orthodontic diagnostic records at the Unit of Orthodontics and Paediatric Dentistry, University of Pavia. Radiographs meeting the predefined inclusion and exclusion criteria will be retrospectively selected for analysis.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
This study includes a single observational arm, since all lateral cephalometric radiographs included in the study will undergo the same analysis procedures. Each radiograph will be evaluated using one digital manual tracing method (Delta-Dent) and three fully automated artificial intelligence-based cephalometric analysis systems (WebCeph™, QuantX, and Smartee). No patient allocation, randomization, or therapeutic intervention will be performed.
Diagnostic Test: Cephalometric Analysis
All included lateral cephalometric radiographs will undergo cephalometric analysis using both digital manual tracing and artificial intelligence-based automated systems. Manual digital tracing will be performed with Delta-Dent software by a single experienced orthodontist through manual identification of cephalometric landmarks. The same radiographs will subsequently be analysed using three fully automated AI-based software programs (WebCeph™, QuantX, and Smartee) without manual correction of landmark positioning. No therapeutic intervention or modification of patient treatment will be performed, as this is an observational comparative study based exclusively on retrospective analysis of radiographic records.
Agreement between AI-based cephalometric analysis and digital manual tracing
Agreement between cephalometric measurements obtained with AI-based software systems and digital manual tracing will be assessed using the intraclass correlation coefficient (ICC) and differences in angular and linear cephalometric measurements.
Time frame: Baseline
SNA
Time frame: Baseline
SNB
Time frame: Baseline
ANB
Time frame: Baseline
SN-GoGn
Time frame: Baseline
L1-GoGn
Time frame: Baseline
U1-ANSPNS
Time frame: Baseline
Nasolabial angle
Time frame: Baseline
Facial angle
Time frame: Baseline
Wits appraisal
Time frame: Baseline
N-Me
Time frame: Baseline
Plan to share: No — Data will be available upon motivated request to the corresponding authors.
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