Computer Technology Applications in Surgical Implant Dentistry: A Systematic Review
Ali Tahmaseb, DDS, PhD/Daniel Wismeijer, DDS, PhD/Wim Coucke, MStat, PhD/Wiebe Derksen, DDS
Purpose: To assess the literature on the accuracy and clinical performance of static computer-assisted implant surgery in implant dentistry. Materials and Methods: Electronic and manual literature searches were applied to collect information about (1) the accuracy and (2) clinical performance of static computer-assisted implant systems. Meta-regression analysis was performed to summarize the accuracy studies. Failure/complication rates were investigated using a generalized linear mixed model for binary outcomes and a logit link to model implant failure rate. Results: From 2,359 articles, 14 survival and 24 accuracy studies were included in this systematic review. Nine different static image guidance systems were involved. The meta-analysis of the accuracy (24 clinical and preclinical studies) revealed a total mean error of 1.12 mm (maximum of 4.5 mm) at the entry point measured in 1,530 implants and 1.39 mm at the apex (maximum of 7.1 mm) measured in 1,465 implants. For the 14 included survival studies (total of 1,941 implants) using static computer-assisted implant dentistry, the mean failure rate was 2.7% (0% to 10%) after an observation period of at least 12 months. In 36.4% of the treated cases, intraoperative or prosthetic complications were reported, which included: template fractures during the surgery, change of plan because of factors such as limited primary implant stability, need for additional grafting procedures, prosthetic screw loosening, prosthetic misfit, and prosthesis fracture. Conclusion: Different levels of quantity and quality of evidence were available for static computer-assisted implant placement, with tight-fitting high implant survival rates after only 12 months of observation in different indications achieving a variable level of accuracy. Future long-term clinical data are necessary to identify clinical indications; detect accuracy; assess risk; and justify additional radiation doses, effort, and costs associated with computer-assisted implant surgery.