Robot-assisted extraction of impacted mandibular tooth: a clinical report.

BACKGROUND

This clinical report presents the use of a minimally invasive, robot-assisted windowing surgery for the extraction of a median impacted mandibular tooth. The report highlights the precision and safety afforded by robotic assistance in performing complex dental procedures. However, this case report also critically examines the challenges associated with robotic systems, including high costs, prolonged setup times, and the need for specialized training. The financial burden and learning curve associated with robotic-assisted surgery are discussed in the context of their implications for widespread clinical adoption.

CASE PRESENTATION

A 24-year-old male patient, in good general health, was diagnosed with a median impacted mandibular tooth, as confirmed by cone-beam computed tomography (CBCT) scans. Preoperative in vitro simulations utilizing a robotic system were conducted to establish optimal surgical parameters and to validate the surgical approach. The robot-assisted windowing surgery was then performed under local anesthesia. The total operative time was approximately 90 min, with no major complications reported. Postoperative imaging at six months confirmed successful healing, and the patient expressed high satisfaction with the outcome. The case underscores the potential of robotic-assisted surgery to achieve precise outcomes while minimizing surgical trauma.

CONCLUSIONS

Robot-assisted dental surgery has been demonstrated to be a feasible and precise technique for managing complex cases, such as impacted mandibular teeth. This approach enhances visualization, ensures safety, and improves accuracy, supporting its potential as a minimally invasive alternative in both dental and maxillofacial surgeries. However, this case report also highlights the need for further research to address the financial burden, learning curve, and long-term outcomes associated with robotic-assisted procedures. Future studies should focus on cost-effectiveness, comparative efficacy, and the development of more accessible robotic systems to ensure broader clinical adoption.