Robot-assisted autotransplantation of third molars in the maxilla: two case reports

机器人辅助上颌第三磨牙自体移植术:两例病例报告

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Abstract

Autotransplantation of teeth has attracted increasing attention due to its excellent biocompatibility and ability to preserve natural dentition. However, conventional autotransplantation of tooth techniques are highly technique-sensitive and reliant on clinician experience, limiting their predictability and broader clinical application. With the advancement of digital dentistry and surgical robotics, robot-assisted autotransplantation of teeth offers a new approach that enhances precision and consistency. In these two reports, digital intraoral scans and cone-beam computed tomography data were processed through AI-assisted segmentation, surgical path planning, and 3D printing technologies. Prior to robotic surgery, surgical guides were installed in the patient's oral cavity to perform calibration and ensure accurate alignment. During the procedure, an autonomous surgical robot was employed to prepare the recipient sites in the upper first molar regions. Following socket preparation, tooth replicas were used to simulate the transplantation process, allowing confirmation of fit and orientation before proceeding with the actual implantation. The transplantation of upper third molars was performed following a standardized digital protocol, involving one-time root canal treatment, 3 mm apicoectomy, and retrograde filling immediately after extraction. The treated teeth were then implanted into fresh extraction socket within the optimal time window, with the total duration from endodontic treatment to implantation not exceeding 15 min. The cases were followed up for three and six months, respectively, postoperative follow-ups showed favorable outcomes, including stable fixation, healthy surrounding soft tissues, and progressive bone healing as confirmed by radiographic imaging. These findings suggest that the integration of AI-based planning and robotic assistance significantly improves the predictability and clinical outcomes of autotransplantation of teeth, supporting its potential as a standardized and intelligent solution in modern dental surgery.

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