Automatic robot-world calibration in an optical-navigated surgical robot system and its application for oral implant placement

Yang, Li; Hu, Junlei; Tao, Baoxin; Yu, Dian; Shen, Yihan; Fan, Shengchi; Wu, Yiqun; Chen, Xiaojun

doi:10.1007/s11548-020-02232-w

Cited by 30 publications

(6 citation statements)

References 22 publications

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“…Due to the limited clinical evidence, further studies should be conducted to confirm the accuracy results and the safety of autonomous robots in the clinic. The comparison results between the present study and other studies using robotic systems are presented in Table 5 (Bolding & Reebye, 2022;Cao et al, 2020;Cheng et al, 2021;Kan et al, 2022;Li et al, 2020;Rawal et al, 2020;Tao et al, 2022Tao et al, , 2023Yang et al, 2022). c Implant location (posterior vs. anterior).…”

Section: Mean (Sd) Median (Iqr) 95% CI Minimum Maximummentioning

confidence: 78%

Accuracy of dental implant placement with a robotic system in partially edentulous patients: A prospective, single‐arm clinical trial

Chen,

Al‐Taezi,

Chu

et al. 2023

Clinical Oral Implants Res

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Objectives This clinical study aimed to assess the accuracy of implant positions using a robotic system in partially edentulous patients. Materials and Methods Twenty‐eight partially edentulous patients received 31 implants using the robotic system. Deviations between the planned and placed implants were calculated after surgery. The deviations were compared with objective performance goals (OPGs) from reported studies of fully guided static computer‐assisted implant surgery (CAIS) and dynamic CAIS. A multiple linear regression analysis was performed to investigate the possible effects of the type and side of the arch, implant location, and implant dimensions on the deviations. Results The evaluation of 31 implants resulted in a mean angle deviation of 2.81 ± 1.13° (95% confidence interval (CI): 2.40–3.23°), while the 3D deviations at the implant shoulder and apex were 0.53 ± 0.23 mm (95% CI 0.45–0.62 mm) and 0.53 ± 0.24 mm (95% CI 0.44–0.61 mm), respectively. The upper limits of the 95% CI of 3D deviations were lower than those of the corresponding OPGs; however, the angle deviation was similar to that of the OPG. No statistically significant differences were found for the type and side of the arch, implant location, and implant dimensions to the deviations (p > .05). Conclusions The robotic system appears to achieve higher accuracy in implant positions than static and dynamic CAIS in partially edentulous patients (Chinese Clinical Trial Registry ChiCTR2300067587).

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Section: Mean (Sd) Median (Iqr) 95% CI Minimum Maximummentioning

confidence: 78%

Accuracy of dental implant placement with a robotic system in partially edentulous patients: A prospective, single‐arm clinical trial

Chen,

Al‐Taezi,

Chu

et al. 2023

Clinical Oral Implants Res

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“…These errors eventually accumulate in the screen coordinate system and affect dental implant guidance. Third, operators-related errors [ 29 , 30 ]. The operator handles surgical instruments with the guidance of the DINS.…”

Section: Discussionmentioning

confidence: 99%

Dental Implant Navigation System Based on Trinocular Stereo Vision

Wang

Zou

et al. 2022

Sensors

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Traditional dental implant navigation systems (DINS) based on binocular stereo vision (BSV) have limitations, for example, weak anti-occlusion abilities, as well as problems with feature point mismatching. These shortcomings limit the operators’ operation scope, and the instruments may even cause damage to the adjacent important blood vessels, nerves, and other anatomical structures. Trinocular stereo vision (TSV) is introduced to DINS to improve the accuracy and safety of dental implants in this study. High positioning accuracy is provided by adding cameras. When one of the cameras is blocked, spatial positioning can still be achieved, and doctors can adjust to system tips; thus, the continuity and safety of the surgery is significantly improved. Some key technologies of DINS have also been updated. A bipolar line constraint algorithm based on TSV is proposed to eliminate the feature point mismatching problem. A reference template with active optical markers attached to the jaw measures head movement. A T-type template with active optical markers is used to obtain the position and direction of surgery instruments. The calibration algorithms of endpoint, axis, and drill are proposed for 3D display of the surgical instrument in real time. With the preoperative path planning of implant navigation software, implant surgery can be carried out. Phantom experiments are carried out based on the system to assess the feasibility and accuracy. The results show that the mean entry deviation, exit deviation, and angle deviation are 0.55 mm, 0.88 mm, and 2.23 degrees, respectively.

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“…Hand search did not identify additional studies. Finally, 20 studies were included in this review (Bolding & Reebye, 2022;Cao et al, 2020;Chen, al-Taezi, et al, 2023;Chen, Bai, et al, 2023;Chen, Zhuang, et al, 2023;Feng et al, 2022;Jia et al, 2023;Kan et al, 2022;Li et al, 2020;Li, Chen, et al, 2023;Li, Wang, et al, 2023;Linn et al, 2023;Qiao et al, 2023;Shi et al, 2023;Tao et al, 2022Tao et al, , 2023Wang et al, 2023;Xu et al, 2023;Yang et al, 2023;Zhao et al, 2023).…”

Section: Study Selectionmentioning

confidence: 99%

Accuracy of robotic surgery for dental implant placement: A systematic review and meta‐analysis

Wu,

Shi,

Qiao

et al. 2024

Clinical Oral Implants Res

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ObjectivesTo systematically analyze the accuracy of robotic surgery for dental implant placement.Materials and MethodsPubMed, Embase, and Cochrane CENTRAL were searched on October 25, 2023. Model studies or clinical studies reporting the accuracy of robotic surgery for dental implant placement among patients with missing or hopeless teeth were included. Risks of bias in clinical studies were assessed. Meta‐analyses were undertaken.ResultsData from 8 clinical studies reporting on 109 patients and 242 implants and 13 preclinical studies were included. Positional accuracy was measured by comparing the implant plan in presurgery CBCT and the actual implant position in postsurgery CBCT. For clinical studies, the pooled (95% confidence interval) platform deviation, apex deviation, and angular deviation were 0.68 (0.57, 0.79) mm, 0.67 (0.58, 0.75) mm, and 1.69 (1.25, 2.12)°, respectively. There was no statistically significant difference between the accuracy of implants placed in partially or fully edentulous patients. For model studies, the pooled platform deviation, apex deviation, and angular deviation were 0.72 (0.58, 0.86) mm, 0.90 (0.74, 1.06) mm, and 1.46 (1.22, 1.70)°, respectively. No adverse event was reported.ConclusionWithin the limitation of the present systematic review, robotic surgery for dental implant placement showed suitable implant positional accuracy and had no reported obvious harm. Both robotic systems and clinical studies on robotic surgery for dental implant placement should be further developed.

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Automatic robot-world calibration in an optical-navigated surgical robot system and its application for oral implant placement

Cited by 30 publications

References 22 publications

Accuracy of dental implant placement with a robotic system in partially edentulous patients: A prospective, single‐arm clinical trial

Accuracy of dental implant placement with a robotic system in partially edentulous patients: A prospective, single‐arm clinical trial

Dental Implant Navigation System Based on Trinocular Stereo Vision

Accuracy of robotic surgery for dental implant placement: A systematic review and meta‐analysis

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