Applying artificial intelligence algorithm in the design of a guide plate for mandibular angle ostectomy

Abstract

Surgical guide plates can improve the accuracy of surgery, although their design process is complex and time-consuming. This study aimed to use artificial intelligence (AI) to design standardized mandibular angle ostectomy guide plates and reduce clinician workload. An intelligence algorithm was designed and trained to design guide plates, with a safety-ensuring penalty factor added. A single-center retrospective cohort study was conducted to test the algorithm among patients who had visited our hospital between 2020 and 2021 for mandibular angle ostectomy. We included patients diagnosed with mandibular angle hypertrophy and excluded those combined with other facial malformations. The guide plate design method acted as the primary predictor, which was AI algorithm vs. experienced residents. Moreover, the symmetry of plate-guided ostectomy was chosen as the primary outcome. The safety, shape, location, effectiveness, and design duration of the guide plate were also recorded. The independent samples t-test and Pearson's chi-squared test were used and P-values <0.05 were considered significant. Fifty patients (7 men, 43 women; 27±4 years) were included. The two groups differed significantly in terms of safety (7.02 vs. 5.25, P<0.05) and design duration (24.98 vs. 1685.08, P ＜ 0.05). The ostectomy symmetry and shape, location, and effectiveness of the guide plates did not differ significantly between the two groups. The intelligent algorithm can improve safety and save time for guide plate design, ensuring other quality of the guide plates. It has good potential applicability in accurate mandibular angle ostectomy.