Influence of implant diameter on accuracy of static implant guided surgery: An in vitro study

In vitro and in vivo accuracy of autonomous robotic vs. fully guided static computer-assisted implant surgery

OBJECTIVES

To assess the accuracy of autonomous robotic and fully guided static computer-assisted implant surgery (sCAIS) performed on models and patients.

MATERIALS AND METHODS

This study was divided into in vitro and in vivo sections. In vitro, 80 operators were assigned to two groups randomly. Forty operators performed forty autonomous robotic implant (ARI group) surgeries and the remaining forty operators carried out forty fully guided sCAIS (FGI group) surgeries on maxillary models, respectively. Each operator placed an implant in one maxillary model. In vivo, 60 patients with 113 implants from 2019 to 2023 (ARI group: 32 patients, 58 implants; FGI group: 28 patients, 55 implants) receiving implant surgeries were incorporated in this retrospective research. The preoperative and postoperative cone beam computer tomographs (CBCTs) were utilized to estimate the linear deviations and angular deviations in two-dimensional (2D) and three-dimensional (3D) space. The Pearson's chi-square test, Shapiro-Wilk test, Student's t test, Mann-Whitney U test and mixed models were applied, and p <0.05 was considered statistically significant.

RESULTS

In vitro, a total of 80 implants were enrolled and significant differences were found between the two groups (p < 0.001): The 3D deviation at the platform of ARI and FGI group was 0.58 ± 0.60 mm and 1.50 ± 1.46 mm, respectively, at the apex was 0.58 ± 0.60 mm and 1.78 ± 1.35 mm, respectively, and angle was 1.01 ± 0.87° and 2.93 ± 1.59°, respectively. Also, except for mesiodistal deviation at the implant platform, the rest linear and angular deviations in the ARI group were significantly lower than those in the FGI group in 2D space (p < 0.001). In vivo, a significantly lower mean of angular deviation (0.95 ± 0.50°, p < 0.001) and the linear deviation at both platform (0.45 ± 0.28 mm, p < 0.001) and apex (0.47 ± 0.28 mm, p < 0.001) were observed in ARI group when compared to the FGI group (4.31 ± 2.60°; 1.45 ± 1.27 mm; 1.77 ± 1.14 mm).

CONCLUSIONS

The use of autonomous robotic technology showed significantly higher accuracy than the fully guided sCAIS.

Toward Digital Twin Development for Implant Placement Planning Using a Parametric Reduced-Order Model

Real-time stress distribution data for implants and cortical bones can aid in determining appropriate implant placement plans and improving the post-placement success rate. This study aims to achieve these goals via a parametric reduced-order model (ROM) method based on stress distribution data obtained using finite element analysis. For the first time, the finite element analysis cases for six design variables related to implant placement were determined simultaneously via the design of experiments and a sensitivity analysis. The differences between the minimum and maximum stresses obtained for the six design variables confirm that the order of their influence is: Young's modulus of the cancellous bone > implant thickness > front-rear angle > left-right angle > implant length. Subsequently, a one-dimensional (1-D) CAE solver was created using the ROM with the highest coefficient of determination and prognosis accuracy. The proposed 1-D CAE solver was loaded into the Ondemand3D program and used to implement a digital twin that can aid with dentists' decision making by combining various tooth image data to evaluate and visualize the adequacy of the placement plan in real time. Because the proposed ROM method does not rely entirely on the doctor's judgment, it ensures objectivity.

Advancing accuracy in guided implant placement: A comprehensive meta-analysis: Meta-Analysis evaluation of the accuracy of available implant placement Methods

OBJECTIVES

This meta-analysis aimed to determine the accuracy of currently available computer-assisted implant surgery (CAIS) modalities under in vitro conditions and investigate whether these novel techniques can achieve clinically acceptable accuracy.

DATA

In vitro studies comparing the postoperative implant position with the preoperative plan were included. Risk of bias was assessed using the Quality Assessment Tool For In Vitro Studies (QUIN Tool) and a sensitivity analysis was conducted using funnel plots.

SOURCES

A systematic search was performed on April 18, 2023, using the following three databases: MEDLINE (via PubMed), EMBASE, and Cochrane Central Register of Controlled Trials. No filters or restrictions were applied during the search.

RESULTS

A total of 5,894 studies were included following study selection. Robotic- and static CAIS (sCAIS) had the most accurate and clinically acceptable outcomes. sCAIS was further divided according to the guidance level. Among the sCAIS groups, fully guided implant placement had the greatest accuracy. Augmented reality-based CAIS (AR-based CAIS) had clinically acceptable results for all the outcomes except for apical global deviation. Dynamic CAIS (dCAIS) demonstrated clinically safe results, except for horizontal apical deviation. Freehand implant placement was associated with the greatest number of errors.

CONCLUSIONS

Fully guided sCAIS demonstrated the most predictable outcomes, whereas freehand sCAIS demonstrated the lowest accuracy. AR-based and robotic CAIS may be promising alternatives.

CLINICAL SIGNIFICANCE

To our knowledge, this is the first meta-analysis to evaluate the accuracy of robotic CAIS and investigate the accuracy of various CAIS modalities.