Accuracy of Bone Mapping and Guided Flapless Implant Placement in Human Cadavers Using a Model-Based Planning Procedure

Purpose: The objective of this study was to assess the accuracy of the model-based NobelGuide method in transferring preoperative planning and estimation of bone volume to the surgical situation. Materials and Methods: Thirteen implant replicas were placed in bounded edentulous spaces in nine human cadavers. Highly restrictive guides were fabricated using preoperative bone mapping data. A stone cast was modified to represent the bone contours at the implant site. Postoperative impressions were taken for comparison with the planning cast that had been used to generate the guides. Mucoperiosteal flaps were raised over each implant site, and the areas were inspected for fenestrations, thread exposures, or dehiscences. A coordinate measuring device was used to obtain positional and angular information from each implant placed in the planned and postsurgical casts. These were compared and analyzed for clinical and statistical significance. Results: The median value for linear accuracy in three dimensions for the model-based NobelGuide was 0.48 mm and the median angular deviation was 2.88 degrees. The greatest measured errors were still within clinically acceptable limits. The bone mapping was of sufficient diagnostic value for implant placement in sites with sufficient bone volume (greater than 5 mm buccolingually). In sites with insufficient bone volume, dehiscences were seen, but the accuracy was independent of bone volume. Conclusion: The use of the model-based NobelGuide encourages adherence to the restorative-driven approach. The accuracy of the method is within acceptable limits for guided surgery described in the literature, and the use of the bone mapping is satisfactory in cases with adequate bone volume. The technique can also be used in sites with insufficient bone volume, but a mucoperiosteal flap procedure is recommended. Keywords: bone mapping, computed tomography, dental implant placement, model-based planning