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Accuracy of autonomous robotic surgery for single-tooth implant placement: A case series

Shuo Yang, Jiahao Chen, Anxue Li, Kevin J. Deng, Ping Li, Shu-Lan Xu

E -journal of dentistry, 2023

103 citations

Abstract

OBJECTIVES

This study aimed to investigate the accuracy of the autonomous robotic computer-assisted implant surgery (r-CAIS) for single-tooth implant placement.

METHODS

Patients with a single missing tooth were enrolled for the autonomous robotic implant surgery. The patients underwent a cone-beam computed tomography (CBCT) scan with a positioning marker. Virtual preoperative implant placement and a drilling plan were created before surgery. The robotic system automatically performed the implant osteotomy and placement intraoperatively under the surgeon's supervision. A postoperative CBCT scan was performed to evaluate the deviations between the planned and placed implants.

RESULTS

Ten patients with single dental implant placement were enrolled. No adverse surgical events and postoperative complications (i.e., infection and early implant failure) were reported. The autonomous robotic implant surgery exhibited a mean global coronal deviation of 0.74 mm (95% CI: 0.53 to 0.94 mm), a mean global apical deviation of 0.73 mm (95% CI: 0.53 to 0.93 mm), and an angular deviation of 1.11° (95% CI: 0.78 to 1.44°), respectively.

CONCLUSIONS

The high accuracy of autonomous r-CAIS technology in single-tooth implant placement was attributed to the control of the angular deviation and axial errors.

CLINICAL SIGNIFICANCE

The main findings of this study provide significant evidence to support the autonomous robotic implant surgery system as a potential alternative in dental implant surgery.

How strong is the evidence?

Evidence Hub reads this as a case series, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

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