Accuracy of Dynamic vs. Static Implant Placement: A Meta-Analysis

Objectives: Recently, a growing interest is evolved in Guided Implant Surgery. Both Dynamic and Static Navigation allow to virtually plan the procedure before surgery and help placing implants as planned into the desired prosthetically- driven positions. Our aim is to conduct a systematic review to evaluate the accuracy of Dental Implant placement using Dynamic Navigation (DN) vs. Static Navigation (SN).
Methods: A literature search of indexed databases (PubMed and Cochrane) without language restriction, up to and including September 1, 2019, was conducted according to a predefined eligibility criteria. We selected articles that met our inclusion criteria and abstracted data on metrics including study design, demographics, sample size, number of implants placed, type of implant system, and outcomes assessed. We analyzed deviation at implant platform and implant apex for both dynamic and static implant placement.
Results: A total of 191 articles were reviewed, and 31clinical studies fulfilled our eligibility criteria. Information about 2,281 implants that had been placed using SN in 24 articles and 467 implants that had been placed using DN in 7 articles were available for review. The surgeon’s experience varied considerably in the included articles. Both half-guided or full-guided SN were reported. Various DN (including DenX Advanced, VISIT, Treon, Navident, and ImplaNav) were used. Results of the meta-analysis indicated significant heterogeneity. Regarding SN, mean deviation at implant platform and implant apex was 1.1mm (95% confidence intervals (CI) 0.85, 1.36) and 1.4mm (95%CI 1.11, 1.67) while that in DN was 1mm (95%CI 0.81, 1.08) and 1mm (95%CI 0.81, 1.15), respectively.
Conclusions: Within the limitations of this study, DN seems to have comparable accuracy to SN. However; clinicians should approach this with care because of 1) Limited evidence available regarding to the accuracy of dynamic implant placement as most studies available had modest sample sizes 2) Significant heterogeneity of the available data.