Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200011, China.
College of Mechanical Engineering, Donghua University, Shanghai 201620, China.
J Plast Reconstr Aesthet Surg. 2023 Sep;84:595-604. doi: 10.1016/j.bjps.2023.05.030. Epub 2023 May 26.
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.
尽管外科导板可以提高手术的准确性，但设计过程复杂且耗时。本研究旨在使用人工智能（AI）设计标准化下颌角截骨导板，以减少临床医生的工作量。
设计并训练智能算法来设计导板，并添加了安全保障罚分因素。对 2020 年至 2021 年间因下颌角截骨术来我院就诊的患者进行了一项单中心回顾性队列研究，以测试该算法。我们纳入了诊断为下颌角肥大的患者，并排除了伴有其他面部畸形的患者。导板设计方法是主要预测指标，分为 AI 算法与有经验的住院医师。此外，我们选择了以导板指导下截骨的对称性作为主要结果。还记录了导板的安全性、形状、位置、有效性和设计时间。使用独立样本 t 检验和 Pearson's 卡方检验，P 值＜0.05 被认为具有统计学意义。
共纳入 50 例患者（7 名男性，43 名女性；27±4 岁）。两组在安全性（7.02 比 5.25，P＜0.05）和设计时间（24.98 比 1685.08，P＜0.05）方面差异有统计学意义。两组患者的截骨对称性以及导板的形状、位置和有效性差异无统计学意义。
智能算法可以提高导板设计的安全性并节省时间，同时保证导板的其他质量。它在准确的下颌角截骨术中具有良好的潜在适用性。
