Abstract
Purpose
Free fibula flap is the gold standard for the treatment of mandibular defects. However, the existing preoperative planning protocol is cumbersome to execute, costly to learn, and poorly collaborative with the robot-assisted cutting of the fibular osteotomy plane.
Methods
A surgical planning system for robotic assisted mandibular reconstruction with fibula free flap is proposed in this study. A fibular osteotomy planning algorithm is presented so that the virtual surgical planning of the fibular osteotomy segments can be obtained automatically with selected mandibular anatomical landmarks. The planned osteotomy planes are then converted into the motion path of the robotic arm, and the automatic fibula osteotomy is completed under optical navigation.
Results
Surgical planning was performed on 35 patients to verify the feasibility of our system’s virtual surgical planning module, with an average time of 13 min. Phantom experiments were performed to evaluate the reliability and stability of this system. The average distance and angular deviations of the osteotomy planes are 1.04 ± 0.68 mm and 1.56 ±1.10°, respectively.
Conclusions
Our system can achieve not only precise and convenient preoperative planning, but also safe and reliable osteotomy trajectory. The clinical applications of our system for mandibular reconstruction surgery are expected soon.
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Acknowledgements
This work was supported by grants from the National Natural Science Foundation of China (81971709; M-0019; 82011530141), the Foundation of Science and Technology Commission of Shanghai Municipality (20490740700), Shanghai Jiao Tong University Foundation on Medical and Technological Joint Science Research (YG2019ZDA06; YG2021ZD21; YG2021QN72; YG2022QN056), and Hospital Funded Clinical Research (21XJMR02), Xinhua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine.
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Guo, Y., Xu, W., Tu, P. et al. Design and implementation of a surgical planning system for robotic assisted mandible reconstruction with fibula free flap. Int J CARS 17, 2291–2303 (2022). https://doi.org/10.1007/s11548-022-02748-3
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DOI: https://doi.org/10.1007/s11548-022-02748-3