Impacts of clinical factors on accuracy in static, dynamic, and robotic-assisted implant surgery: A comparative narrative review.

Abstract

Purpose: This review examined clinical and technological factors that influence implant placement accuracy in computer-assisted implant surgery (CAIS) systems.

Study selection: A systematic search of PubMed, Scopus, and Embase identified English-language studies published between January 2015 and January 2025. The eligible studies included randomized controlled trials, observational studies, systematic reviews, in vitro investigations, and case reports. Data extraction focused on the coronal, apical, and angular deviations. Methodological quality was appraised using the Oxford Centre for Evidence-Based Medicine (CEBM) framework and validated bias assessment tools.

Results: Fifty-three studies were included. Accuracy was influenced by patient-related factors (arch type, bone density, and edentulous span), surgical variables (flap design, operator experience, and guide protocol), and technological parameters (imaging modality, fiducial markers, and calibration). Static systems achieved high accuracy in dentate cases with stable guide support, but were less reliable in posterior or edentulous jaws. Dynamic navigation provided intraoperative flexibility and consistent performance across arches, although outcomes depended on calibration precision and operator learning curves. Robotic-assisted systems achieved the lowest mean deviations through trajectory control and haptic feedback, although evidence remains limited to early clinical and in vitro studies.

Conclusions: Although all CAIS systems achieve high accuracy, their performance varies according to the design of the system and clinical context. Static systems are effective when stabilization is ensured, while dynamic navigation offers adaptable accuracy across scenarios, and robotics exhibit the greatest consistency by reducing operator variability. Further multicenter randomized trials and standardized reporting are needed to strengthen the available evidence and guide clinical selection.