Accuracy of Implant Placement using a Mixed Reality-Based Dynamic Navigation System versus Static Computer-Assisted and Freehand Surgery: an in Vitro Study

计算机辅助手术 导航系统 计算机科学 混合现实 植入 生物医学工程 外科 人机交互 虚拟现实 医学 计算机视觉 人工智能
作者
Ariel Shusterman,Rizan Nashef,Simona Tecco,Carlo Mangano,Henriette Lerner,Francesco Mangano
出处
期刊:Journal of Dentistry [Elsevier]
卷期号:146: 105052-105052 被引量:3
标识
DOI:10.1016/j.jdent.2024.105052
摘要

This in vitro study aimed to compare the accuracy of dental implant placement in partially edentulous maxillary models using a mixed reality-based dynamic navigation (MR-DN) system to conventional static computer-assisted implant surgery (s-CAIS) and a freehand (FH) method. Forty-five partially edentulous models (with teeth missing in positions #15, #16 and #25) were assigned to three groups (15 per group). The same experienced operator performed the model surgeries using an MR-DN system (group 1), s-CAIS (group 2) and FH (group 3). In total, 135 dental implants were placed (45 per group). The primary outcomes were the linear coronal deviation (entry error; En), apical deviation (apex error; Ap), XY and Z deviations, and angular deviation (An) between the implants' planned and actual (post-surgery) positions in the models. These deviations were computed as the distances between the stereolithographic (STL) files for the planned implants and placed implants captured with an intraoral scanner. Across the three implant sites, the MR-DN system was significantly more accurate than the FH method (in XY, Z, En, Ap and An) and s-CAIS (in Z, Ap and An), respectively. However, S-CAIS was more accurate than MR-DN in XY, and no difference was found between MR-DN and s-CAIS in En. Within the limits of this study (in vitro design, only partially edentulous models), implant placement accuracy with MR-DN was superior to that of FH and similar to that of s-CAIS. In vitro, MR-DN showed greater accuracy in implant positioning than FH, and similar accuracy to s-CAIS: it could, therefore, represent a new option for the surgeon. However, clinical studies are needed to determine the feasibility of MR-DN.
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