Xingqi Fan

BACKGROUND: This in vitro study aims to evaluate the accuracy of dental implant placement by a novel image-guided hybrid robotic system for dental implant surgery (HRS-DIS). METHODS: The HRS-DIS with a 5 degree of freedom (DOF) serial manipulator and a 6 DOF Stewart platform was developed. To evaluate the accuracy of repeated drilling, the holes were prepared twice with a 2.2 mm drill. To evaluate the accuracy of dental implant placement, the entry, exit and angle deviations of dental implants were measured. RESULTS: Twenty-four holes were prepared twice, and mean (±SD) of diameters were measured as 2.2 ± 0.02 mm. A total of 160 dental implants were placed in 32 phantoms by HRS-DIS. The mean (±SD) of the entry, exit and angle deviation were 0.8 ± 0.54 mm, 0.87 ± 0.54 mm and 1.0 1 ± 0.44°, respectively. CONCLUSIONS: The results of the in vitro study preliminarily validated that the HRS-DIS could provide a high accuracy for dental implant surgery.

Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in artificial intelligence (AI), deep learning (DL), augmented reality (AR) and robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and DL based medical image segmentation, 3D visualization and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with AR and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.

Augmented reality has been gradually applied in dental implant surgery. However, whether the dynamic navigation system integrated with augmented reality technology will further improve the accuracy is still unknown. The purpose of this study is to investigate the accuracy of dental implant placement using dynamic navigation and augmented reality-based dynamic navigation systems. Thirty-two cone-beam CT (CBCT) scans from clinical patients were collected and used to generate 64 phantoms that were allocated to the augmented reality-based dynamic navigation (ARDN) group or the conventional dynamic navigation (DN) group. The primary outcomes were global coronal, apical and angular deviations, and they were measured after image fusion. A linear mixed model with a random intercept was used. A P value < 0.05 was considered to indicate statistical significance. A total of 242 dental implants were placed in two groups. The global coronal, apical and angular deviations of the ARDN and DN groups were 1.31 ± 0.67 mm vs. 1.18 ± 0.59 mm, 1.36 ± 0.67 mm vs. 1.39 ± 0.55 mm, and 3.72 ± 2.13° vs. 3.1 ± 1.56°, respectively. No significant differences were found with regard to coronal and apical deviations (P = 0.16 and 0.6, respectively), but the DN group had a significantly lower angular deviation than the ARDN group (P = 0.02). The augmented reality-based dynamic navigation system yielded a similar accuracy to the conventional dynamic navigation system for dental implant placement in coronal and apical points, but the augmented reality-based dynamic navigation system yielded a higher angular deviation.