Comparative Analysis of AI-Generated and Manually Designed Approaches in Accuracy and Design Time for Surgical Path Planning of Dynamic Navigation-Aided Endodontic Microsurgery: A Retrospective Study.

IF 7.1 1区 医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE
Chen Chen, Xining Zhang, Li Qin, Liuyan Meng
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Abstract

Aim: To compare the accuracy and design time of artificial intelligence (AI)-generated and manually designed (MD) surgical pathways for osteotomies and root-end resections in dynamic navigation (DN)-aided endodontic microsurgery (EMS).

Methodology: Fifty-one surgical pathways were analysed, each planned using both AI and MD methodologies. Accuracy was assessed using the DCARE Navigation System (v3.2, MedNav Ltd) and AutoCAD (2023, Autodesk Inc.), evaluating five parameters: start deviation, end deviation, angular deviation, root-end resection length deviation, and root-end resection angulation deviation. Design time was measured from the point of CBCT dataset import to the finalisation of the surgical pathway design. Mann-Whitney U test was used to compare the accuracy and design time of the AI and MD groups, whereas the rank-based ANCOVA was used to assess deviations according to tooth type, jaw type, and root number. Statistical significance was set at p < 0.05.

Results: Compared with the MD group, the AI group exhibited significantly smaller root-end resection length deviations (AI: 0.01 [0.01, 0.02] mm; MD: 0.02 [0.01, 0.03] mm; p = 0.029) but significantly larger root-end resection angulation deviations (AI: 3.48 [1.01, 7.48]; MD: 0.35 [0.16, 0.73]; p < 0.001). There were no significant differences in the start deviation, end deviation, angular deviation, root-end resection length deviation, or root-end resection angulation deviation across tooth type, jaw type, or root number. The design time was significantly shorter in the AI group than in the MD group (55 [21, 74] s vs. 379 [215, 553] s; p < 0.001).

Conclusions: A clinically operational AI-based surgical path design approach is capable of minimising manual interventions and delivering time-efficient, accurate results for clinical use. The integration of AI with DN-aided EMS may contribute to the development of increasingly autonomous surgical procedures.

人工智能生成和人工设计方法在动态导航辅助牙髓显微外科手术路径规划的准确性和设计时间上的对比分析:一项回顾性研究。
目的:比较动态导航(DN)辅助牙髓显微外科(EMS)中人工智能(AI)生成和人工设计(MD)手术路径的截骨和根端切除的准确性和设计时间。方法:分析了51条手术路径,每条路径均采用人工智能和MD方法进行规划。使用DCARE导航系统(v3.2, MedNav Ltd)和AutoCAD (2023, Autodesk Inc.)评估精度,评估五个参数:开始偏差、结束偏差、角度偏差、根端切除长度偏差和根端切除角度偏差。从CBCT数据集导入到手术路径设计的最终完成,测量设计时间。使用Mann-Whitney U检验比较AI组和MD组的准确性和设计时间,而使用基于秩的ANCOVA评估根据牙型、颌型和根数的偏差。结果:与MD组相比,AI组根尖切除长度偏差明显小于MD组(AI: 0.01 [0.01, 0.02] mm; MD: 0.02 [0.01, 0.03] mm; p = 0.029),但根尖切除角度偏差明显大于MD组(AI: 3.48 [1.01, 7.48]; MD: 0.35 [0.16, 0.73];结论:临床可操作的基于人工智能的手术路径设计方法能够最大限度地减少人工干预,并为临床使用提供高效、准确的结果。人工智能与dn辅助EMS的整合可能有助于日益自主的外科手术的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International endodontic journal
International endodontic journal 医学-牙科与口腔外科
CiteScore
10.20
自引率
28.00%
发文量
195
审稿时长
4-8 weeks
期刊介绍: The International Endodontic Journal is published monthly and strives to publish original articles of the highest quality to disseminate scientific and clinical knowledge; all manuscripts are subjected to peer review. Original scientific articles are published in the areas of biomedical science, applied materials science, bioengineering, epidemiology and social science relevant to endodontic disease and its management, and to the restoration of root-treated teeth. In addition, review articles, reports of clinical cases, book reviews, summaries and abstracts of scientific meetings and news items are accepted. The International Endodontic Journal is essential reading for general dental practitioners, specialist endodontists, research, scientists and dental teachers.
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