## 4 Discussion  
This paper proposes a method for developing a VR-based maxillofacial reconstruction surgery simulator and verifies the performance, accuracy, and usability of the implemented simulator. The performance validation results show that the VR simulator efficiently utilizes resources and provides a stable and consistent user experience during model cutting and interaction. Specifically, even during resource-intensive tasks (such as model data processing, model cutting, and model data exporting), the tasks were completed smoothly without excessive computational load. This indicates that the simulator operates stably without excessive resource consumption, and that interaction and model cutting are effectively implemented, providing a consistent experience for the user. The accuracy validation results confirmed a high similarity between the reconstruction models generated by the CAD software and the simulator, demonstrating the accuracy of the simulator-based reconstruction models. However, some areas showed larger differences than the average. It was found that these discrepancies could potentially be improved through adjustments in cutting positions and mesh refinement techniques. These results suggest that, with minor improvements and refinements, the simulator in this study has the potential to generate clinically applicable reconstruction models, and it could be used for surgical-planning and educational purposes. The usability validation results showed that some difficulties were observed in the initial learning curve for users who were unfamiliar with VR content and interactive devices. However, overall, high evaluation results were obtained, and the reliability of the students' responses was confirmed. These results demonstrate the potential for the simulator to be used for educational and surgical-planning purposes, and it is expected that, with some improvements and refinements based on feedback, it can be utilized more effectively. The simulator developed in this study is closely related to existing VR-based medical education and surgical-planning research. Previous studies on medical education [17; 18; 19; 26; 27; 28] have confirmed that VR-based medical education and training methods can yield high effectiveness, demonstrating the value of VR in the field of medical education and training. Additionally, existing research on surgical planning [22; 23; 24; 25; 29; 30; 31] has confirmed that VR-based surgical planning has high reliability and clinical applicability. The developed simulator aligns with these previous studies and can function as both an educational tool for learning the complex process of maxillofacial reconstruction model generation and a surgical-planning tool. Specifically, it is designed to provide immersion through interaction with CT-based 3D models and to precisely simulate the cutting and reconstruction processes. This differentiates it from existing VR education and surgical-planning tools, enhancing the educational and clinical potential of VR technology and suggesting that the proposed simulator has competitive advantages as a tool for education and surgical-planning support. However, while the simulator implemented the maxillofacial reconstruction surgery model using a plane-based cutting algorithm and mesh regeneration method, its application was limited in complex patient cases requiring curved cuts. Future research plans include developing algorithms capable of curved cutting and surface mesh regeneration techniques to enable the creation of more refined and flexible reconstruction models. Additionally, to enhance the applicability of the generated maxillofacial reconstruction models, we aim to integrate AR technology. Recently, AR has been used for surgical navigation and educational purposes, and its importance in the medical field is gradually increasing. Existing research on AR-based surgical navigation [39; 40; 43; 44; 45; 46; 47; 48] has proven the effectiveness and potential of navigation systems in the medical and dental fields.