Comparative Study on AI-Based Computer-Guided Implant Placement and Manual Surgical Planning

Abstract

Background: The precision of dental implant placement is critical for long-term prosthetic success and the avoidance of anatomical complications. While Computer-Guided Surgery (CGS) has improved accuracy, the planning phase remains time-consuming and operator-dependent. Recently, Artificial Intelligence (AI) algorithms have been integrated into planning software to automate implant positioning and guide design.

Methods: A randomized controlled clinical trial was conducted involving 60 patients requiring single-tooth implants in the posterior mandible. Patients were randomly assigned to two groups: Group A (AI-Guided, n=30) utilized AI-based software for automatic nerve tracing, implant positioning, and 3D-printed guide fabrication; Group B (Manual/Freehand, n=30) underwent standard CBCT-based manual planning and freehand surgical placement. Post-operative CBCT scans were superimposed on pre-operative plans to measure deviations at the entry point, apex, and angulation. Surgical duration and visual analog scale (VAS) pain scores were also recorded.

Results: Group A demonstrated significantly lower mean deviations compared to Group B. The mean angular deviation was 〖2.14〗^∘±〖0.76〗^∘ for the AI-Guided group versus 〖6.82〗^∘±〖2.41〗^∘ for the Manual group (p<0.001). Global deviation at the apex was 0.85±0.32 mm for Group A and 2.15±0.88 mm for Group B (p<0.001). The mean surgical time was significantly shorter in Group A (14.2±3.5 min) compared to Group B (26.8±5.2 min) (p=0.002). No nerve injuries occurred in either group.

Conclusion: AI-based computer-guided implant surgery significantly outperforms manual freehand placement in terms of three-dimensional accuracy and surgical efficiency. The integration of AI reduces the margin of error inherent in manual execution, offering a safer and more predictable workflow for posterior mandibular rehabilitation.