Pilot Study: Algorithm-Based Assessment of Maxillary Sinus Volume in Zygomatic and Pterygoid Implant Planning

TL;DR

A new algorithm helps assess maxillary sinus volume changes in dental implant planning, improving surgical precision and safety.

Contribution

A novel computational algorithm for automated maxillary sinus volume assessment in implant surgery planning is introduced.

Findings

The algorithm showed consistent reductions in sinus volume post-surgery, validated by experts.

Relative sinus volume changes ranged from 1.1% to 24.5% across patients.

The method is feasible for non-invasive surgical planning and monitoring anatomical changes.

Abstract

Background/Objetives: Zygomatic implants are an effective solution for the prosthetic rehabilitation of atrophic maxillae, but their placement can alter maxillary sinus anatomy and influence surgical outcomes. This study presents a computational algorithm for automated segmentation and volumetric assessment of the maxillary sinus from cone-beam computed tomography (CBCT) images, offering a reproducible and clinically oriented tool. Methods: Six sinus samples from four patients undergoing pterygoid or zygomatic implant surgery were analyzed. The algorithm was designed to integrate image binarization, surface detection, and iterative reconstruction to delineate sinus boundaries and compute volumes with minimal operator dependence. Results: Postoperative analyses consistently revealed reductions in sinus volume, with relative changes ranging from 1.1% to 24.5%, validated by expert review. Conclusions: These results demonstrate the feasibility of algorithm-driven volumetric assessment as a non-invasive approach to support surgical planning and monitor anatomical changes. Although limited by the small sample size, this pilot study establishes a foundation for further research and highlights the clinical potential of computational methods to enhance precision and safety in zygomatic implantology.

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