Abstract
Objectives: To assess the accuracy of bone-supported static surgical guides designed with the assistance of artificial intelligence in full-arch implant rehabilitation cases. Methods: This clinical study involved 10 patients, aged 45–60 years, who required full mouth implant rehabilitation. With the assistance of artificial intelligence, automatic bone segmentation was performed on one or both jaws, thereby enabling the design and fabrication of patient-specific bone-supported surgical guides for a fully guided bone reduction and implant placement protocol. Four patients underwent treatment in both arches, whereas six patients underwent a single arch treatment. Postoperative cone beam computed tomography scans were used to assess deviations in actual implant placement compared with the virtual plan. Results: A total of 80 implants were placed (36 in the maxilla and 44 in the mandible). The mean global deviations at the implant platform and apex were 1.24 mm (SD: 1.27 mm) and 1.29 mm (SD: 0.95 mm), respectively. The mean angle deviation of the long axis of the implant was 3.63° (SD: 2.91°). Deviations were observed to be within the clinically acceptable range. For the 3D deviation analysis, there was no statistically significant difference observed between implants placed in the maxilla and those placed in the mandible. Conclusion: Within the limitations of this study, automatic bone segmentation using artificial intelligence can serve as a very useful tool for planning full-mouth implant rehabilitation cases using a fully digital workflow. Clinical significance: Automatic bone segmentation is a novel, time-saving feature that allows for the production of bone-supported guides with accurate fitting, which can be used for complex full-mouth implant rehabilitation cases.