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

Area of Science:

• Oral and Maxillofacial Surgery
• Medical Imaging
• Computational Anatomy

Background:

• Zygomatic implants are crucial for rehabilitating atrophic maxillae.
• Implant placement can significantly alter maxillary sinus anatomy and surgical results.
• Accurate assessment of sinus volume changes is clinically important.

Purpose of the Study:

• To develop and validate a computational algorithm for automated maxillary sinus segmentation and volumetric assessment.
• To provide a reproducible and clinically relevant tool for analyzing sinus anatomy changes.
• To evaluate the algorithm's efficacy in assessing volume reduction post-zygomatic implant surgery.

Main Methods:

• Analysis of six sinus samples from four patients using cone-beam computed tomography (CBCT) data.
• Development of an algorithm integrating image binarization, surface detection, and iterative reconstruction.
• Minimal operator dependence in delineating sinus boundaries and computing volumes.

Main Results:

• Consistent reductions in maxillary sinus volume were observed post-surgery.
• Relative volume changes ranged from 1.1% to 24.5%.
• Results were validated through expert review, confirming the algorithm's accuracy.

Conclusions:

• Algorithm-driven volumetric assessment is a feasible, non-invasive method for surgical planning.
• The computational approach supports monitoring anatomical changes in the maxillary sinus.
• This pilot study highlights the potential of computational methods to enhance precision and safety in zygomatic implantology.