Artificial Intelligence-Based Assessment of Endosseous Lesions
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI assisted Evaluation.
- Who it may be relevant to
- Registry conditions: Maxillary Cyst, Mandibular Cyst. Basic parameters: 18 years — 80 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Italy
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Artificial Intelligence-Based Assessment of Endosseous Lesions: A Prospective Clinical Study
Overview
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 test AI assisted Evaluation
CBCT scans were processed using AI-based software capable of: * Automated segmentation of the lesion * 3D reconstruction * Volumetric calculation
Primary outcome measures
- Time required for CBCT interpretation (minutes) [Time frame: Day 1]
Secondary outcome measures (1)
- Intraoperative and Postoperative Complications [Time frame: Day 1]
Eligibility 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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Diagnostic
Study locations
Italy · 2 centers
- University of Bari Aldo Moro — Bari
- Dr. Giuseppe D'Albis — Bari
Identifiers
NCT: NCT07505485 · AIpreoperative