Automated Preoperative Planning Algorithm for Mandibular Angle Osteotomy Based on Anatomical Landmarks Detection: A Retrospective Study.

OBJECTIVE

The aim of the study was to develop and evaluate an automated preoperative planning algorithm based on anatomical landmark point recognition for enhancing the efficiency and intelligence of preoperative planning for mandibular angle osteotomy.

METHODS

A retrospective cohort of 34 patients underwent preoperative planning with this algorithm. The present algorithm was developed using a method based on anatomical marker point recognition. The efficiency, symmetry, and safety of the automated preoperative planning and esthetics were statistically analyzed by paired t test and χ2 test.

RESULTS

The results showed that the automated planning algorithm was able to achieve a great improvement in preoperative planning efficiency as well as safety and symmetry. A prospective case report of 2 patients is then reported, illustrating the safety and esthetics of the algorithm with 1-year postoperative follow-up and postoperative esthetic scores.

CONCLUSION

This algorithm can help to improve the efficiency of preoperative planning for surgeons while ensuring safety and esthetics and can be further applied to other craniomaxillofacial personalized design surgeries in the preoperative design in the future.