Study of AI-Based 3D Imaging to Analyze Jawbone Lesions for Better Diagnosis and Surgery Planning

What this Trial Is About

This clinical trial evaluates the use of Artificial Intelligence AI to analyze endosseous lesions in patients with maxillary or mandibular cysts. Traditional interpretation of cone beam computed tomography CBCT scans relies on qualitative and experience-dependent methods, which may underestimate lesion complexity. The study aims to compare AI-based segmentation and volumetric analysis with conventional CBCT interpretation to assess potential improvements in lesion evaluation and clinical outcomes. Participants will be randomly assigned to either receive conventional CBCT evaluation or AI-assisted evaluation of their scans. The AI tool performs automated segmentation of the lesion, 3D reconstruction, and volumetric calculation to provide objective and reproducible measurements. This approach seeks to enhance surgical planning, predict anatomical involvement, reduce diagnostic errors, and standardize follow-up assessments. During the study, researchers will measure the time required for CBCT interpretation and monitor intraoperative and postoperative complications. Participants will undergo evaluations on day 1, including scan analysis and clinical assessments. The study involves adults aged 18 to 80 years in good health, with no contraindications for surgery, and will continue until May 2026.

Artificial Intelligence-Based Assessment of Endosseous Lesions