AI-based imaging and measurement of jaw cysts
Official title: Artificial Intelligence-Based Assessment of Endosseous Lesions: A Prospective Clinical Study
Run by University of Bari Aldo Moro · NCT07505485 · Data updated 2026-11-12
This project tests whether an AI tool can automatically measure and map jaw cysts from 3D dental scans to help adults who may need surgery for maxillary or mandibular cysts.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years to 80 Years |
| Sex | All |
| Enrollment | 10 (estimated) |
| Sponsor | University of Bari Aldo Moro Academic / other |
| Locations | 2 sites (Bari and 1 other locations) |
| Status | Recruiting |
| Started | April 1, 2026 |
| Main results expected | May 1, 2026 |
| Study ends | May 1, 2026 |
| Registry record updated | April 15, 2026 |
| Trial ID | NCT07505485 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults over 18 in good general health with diagnosed maxillary or mandibular cysts and no general contraindication to surgery are the intended participants.
✕Probably not a fit
Patients with acute infections, pregnant people, heavy smokers (>15 cigarettes/day), or those medically unfit for surgery are unlikely to benefit or be eligible.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Adults with maxillary or mandibular cysts will undergo cone-beam CT (CBCT) imaging and have both conventional 2D/linear measurements and an AI-based segmentation applied to their scans. The AI tool will delineate lesion boundaries and compute volumetric measurements (mm³) for comparison with standard assessments. The study will compare measurement reproducibility, anatomical involvement predictions, and any changes to surgical planning that result from AI-generated data. Outcomes include differences in measured lesion size, potential reductions in diagnostic variability, and implications for standardized follow-up.
Why it matters
Potential benefit: If successful, the AI could provide objective lesion volumes and maps that improve surgical planning and follow-up while reducing diagnostic variability.
How similar studies have gone: Similar AI segmentation tools have shown promising accuracy in other medical imaging tasks and emerging dental CBCT research, but their direct clinical impact on surgical outcomes remains incompletely established.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Good health according to the System of the American Society of Anesthesiology * Aged older than 18 years * No general medical contraindication for surgery Exclusion Criteria: * Smoking more than 15 cigarettes a day * Pregnancy * Acute infections
Where it's running
-
University of Bari Aldo Moro
Bari, Italy Recruiting -
Dr. Giuseppe D'Albis
Bari, Italy Recruiting
Study contacts
- Principal investigator: Giuseppe D'Albis, Dr — University of Bari Aldo Moro
- Study coordinator: Giuseppe D'Albis, Dr.
- Email: giuseppe.dalbis@uniba.it
- Phone: +393495103642
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.