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

Area of Science:

• Computer-aided surgery
• Craniomaxillofacial surgery
• Medical artificial intelligence

Background:

• Preoperative planning for mandibular angle osteotomy is crucial for surgical outcomes.
• Current planning methods can be time-consuming and subjective.
• Enhancing efficiency and accuracy in planning is a key goal in craniomaxillofacial surgery.

Purpose of the Study:

• To develop and evaluate an automated preoperative planning algorithm for mandibular angle osteotomy.
• The algorithm utilizes anatomical landmark point recognition.
• The goal is to improve the efficiency, intelligence, safety, and esthetics of preoperative planning.

Main Methods:

• A retrospective cohort of 34 patients was analyzed.
• The algorithm was developed based on anatomical marker point recognition.
• Statistical analysis included paired t-tests and chi-squared tests to assess efficiency, symmetry, safety, and esthetics.

Main Results:

• The automated algorithm significantly improved preoperative planning efficiency.
• The algorithm demonstrated enhanced safety and symmetry in planning.
• A prospective case report of 2 patients confirmed the algorithm's safety and esthetic outcomes after a 1-year follow-up.

Conclusions:

• The developed algorithm enhances preoperative planning efficiency for surgeons.
• It ensures improved safety and esthetic results in mandibular angle osteotomy.
• The algorithm shows potential for broader application in personalized craniomaxillofacial surgeries.