Does AI-based cephalometric tracing match digital manual tracing for orthodontic measurements?
Official title: Cephalometric Tracing: A Comparison Between Digital Analysis and Artificial Intelligence
Run by University of Pavia · NCT07664488 · Data updated 2026-11-12
This study tests whether AI-powered cephalometric analysis can produce measurements similar to traditional digital tracing in 100 patient radiographs.
Quick facts
| Study type | Observational |
|---|---|
| Sex | All |
| Enrollment | 100 (estimated) |
| Sponsor | University of Pavia Academic / other |
| Locations | 1 site (Pavia, Italy) |
| Status | Recruiting |
| Started | June 1, 2026 |
| Main results expected | September 30, 2026 |
| Study ends | September 30, 2026 |
| Registry record updated | June 24, 2026 |
| Trial ID | NCT07664488 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Patients with available high-quality digital lateral cephalometric radiographs taken for orthodontic diagnostic purposes, with no craniofacial anomalies and no prior orthodontic or orthognathic treatment.
✕Probably not a fit
Patients whose radiographs are of insufficient quality, show artifacts, or have conditions preventing reliable landmark identification may not benefit from AI-based methods.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study compares AI-based cephalometric analysis with manual digital tracing to determine accuracy and reproducibility. It analyzes 100 standardized lateral cephalometric radiographs using manual landmarking in Delta-Dent and three automated AI systems (WebCeph, QuantX, Smartee) without landmark adjustments. Ten cephalometric parameters across sagittal, vertical, dental, and soft tissue relationships will be evaluated for agreement with manual tracing, using intra-rater reliability and statistical analyses to assess clinical relevance. The reference method is manual tracing performed by a single experienced orthodontist. Data will be retrospective, drawn from records at the University of Pavia, with appropriate consent.
Why it matters
Potential benefit: If successful, AI-based tracing could speed up analysis and provide reliable adjuncts to support orthodontic diagnosis and treatment planning.
How similar studies have gone: Prior work suggests AI can approach manual tracing accuracy in cephalometrics, but results vary by system and parameter; this study adds direct comparison across three AI tools.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Availability of digital lateral cephalometric radiographs of adequate diagnostic quality * Radiographs acquired with patients in centric occlusion and proper head positioning using a cephalostat * Patients of any age and sex * Absence of congenital or acquired craniofacial anomalies * No previous orthodontic treatment * No previous orthognathic surgical treatment * Absence of agenesis of incisors or first molars * Absence of supernumerary teeth overlapping the region of interest Exclusion Criteria: * Radiographs presenting artifacts or inadequate visualization of anatomical structures * History of significant craniofacial trauma * Radiographs acquired without a cephalostat * Presence of severe skeletal asymmetries * Incomplete clinical or radiographic records * Radiographs unsuitable for manual or AI-based cephalometric landmark identification
Where it's running
-
Unit of Orthodontics and Pediatric Dentistry - Section of Dentistry - Department of Clinical, Surgical, Diagnostic and Pediatrics - University of Pavia, Pavia, Lombardy 27100
Pavia, Italy, Italy Recruiting
Study contacts
- Study coordinator: Andrea Scribante, DDS, PhD
- Email: andrea.scribante@unipv.it
- Phone: +39 0382516223
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.