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Artificial Intelligence-Based Assessment of Endosseous Lesions

Artificial Intelligence-Based Assessment of Endosseous Lesions: A Prospective Clinical Study

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07505485
Acronym
AIpreop
Enrollment
10
Registered
2026-04-01
Start date
2026-04-01
Completion date
2026-05-01
Last updated
2026-04-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Mandibular Cyst, Maxillary Cyst

Brief summary

Despite these advances, CBCT interpretation remains largely qualitative and dependent on the clinician's experience. Conventional evaluation is based on two-dimensional slices and linear measurements, which may underestimate lesion complexity and spatial distribution. Recent developments in Artificial Intelligence in Medicine have introduced automated image segmentation tools capable of identifying lesion boundaries and calculating volumetric data. These technologies allow a transition from subjective assessment to objective, reproducible quantification. The potential clinical advantages include: * Objective measurement of lesion size (volume in mm³) * Improved surgical planning * Enhanced prediction of anatomical involvement * Reduction of diagnostic errors * Standardization of follow-up and outcome assessment Therefore, the aim of the present study was to evaluate the clinical impact of AI-based segmentation and volumetric analysis of endosseous lesions compared to conventional CBCT interpretation.

Interventions

DIAGNOSTIC_TESTAI assisted Evaluation

CBCT scans were processed using AI-based software capable of: * Automated segmentation of the lesion * 3D reconstruction * Volumetric calculation

Sponsors

University of Bari Aldo Moro
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
Yes

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

Design outcomes

Primary

MeasureTime frameDescription
Time required for CBCT interpretation (minutes)Day 1assessment of the time required for CBCT interpretation by the surgeon. A digital stopwatch was used to record the operative time required for each procedural step, with measurements expressed in seconds, in order to obtain an objective and standardized assessment of execution time.

Secondary

MeasureTime frameDescription
Intraoperative and Postoperative ComplicationsDay 1* Unexpected endodontic treatment of adjacent teeth * Intraoperative nerve exposure * Paresthesia * Excessive bone removal * Incomplete lesion removal * Postoperative infection * Delayed healing * Sinus involvement * Root damage to adjacent teeth

Countries

Italy

Contacts

CONTACTGiuseppe D'Albis, Dr.
giuseppe.dalbis@uniba.it+393495103642
CONTACTSaverio Capodiferro, Prof.
saverio.capodiferro@uniba.it
PRINCIPAL_INVESTIGATORGiuseppe D'Albis, Dr

University of Bari Aldo Moro

STUDY_DIRECTORSaverio Capodiferro, Prof

University of Bari Aldo Moro

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Apr 16, 2026