Conference Agenda

The use of surgical cutting guides for mandibular osteotomies is a consolidated approach in maxillo-facial surgery, typically based on patient-specific designs relying on anatomical fitting. However, these solutions may be limited by intraoperative variability and reduced flexibility.

The present study proposes and experimentally investigates an AR-guided hybrid cutting guide combining a physical constraint with augmented reality support for guide positioning and alignment.

A full-factorial Design of Experiments was defined to evaluate the influence of key design parameters on system performance, including the tracking modality for pose estimation (marker), the adjustment strategy of the guide (adjustment), and the type of physical constraint provided to the cutting instrument (guide).

A total of 27 configurations were tested with 40 replications each on mockups replicating irregular bone-like surfaces, considering geometric deviation, quantified through the Hausdorff distance between the planned cutting profile and the executed cut, and total task time as response variables.

The results show that the configuration combining a cubic marker, rigid adjustment, and linear guide provides the best performance, while more complex adjustment strategies and geometries lead to increased variability and execution time.

A desirability-based multi-response optimization confirmed this configuration as the optimal solution, with a global desirability index superior to all remaining alternatives.