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Automatic surgical planning based on bone density assessment and path integral in cone space for reverse shoulder arthroplasty

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Reverse shoulder arthroplasty (RSA) is an effective surgery for severe shoulder joint diseases. Traditionally, the preoperative planning procedure of RSA is manually conducted by experienced surgeons, resulting in prolonged operating time and unreliable drilling paths of the prosthetic fixation screws. In this study, an automatic surgical planning algorithm for RSA was proposed to compute the optimal path of screw implantation.

Methods

Firstly, a cone-shaped space containing alternative paths for each screw is generated using geometric parameters. Then, the volume constraint is applied to automatically remove inappropriate paths outside the bone boundary. Subsequently, the integral of grayscale value of the CT is used to evaluate the bone density and to compute the optimal solution. An automatic surgical planning software for RSA was also developed with the aforementioned algorithms.

Results

Twenty-four clinical cases were used for preoperative planning to evaluate the accuracy and efficiency of the system. Results demonstrated that the angles among the prosthetic fixation screws were all within constraint angle(45°), and the stability rate of the planned prosthesis was 94.92%. The average time for the automatic planning algorithm was 4.39 s, and 83.96 s for the whole procedure. Repetitive experiments were also conducted to demonstrate the robustness of our system, and the variance of the stability coefficient was 0.027%.

Conclusions

In contrast to the cumbersome manual planning of the existing methods for RSA, our method requires only simple interaction operations. It enables efficient and precise automatic preoperative planning to simulate the ideal placement of the long prosthetic screws for the long-term stability of the prosthesis. In the future, it will have great clinical application prospects in RSA.

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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 (19510712200; 20490740700), Shanghai Jiao Tong University Foundation on Medical and Technological Joint Science Research (YG2019ZDA06; YG2021ZD21; YG2021QN72; YG2022QN056), the Program of Shanghai Academic/Technology Research Leader (19XD1402800), the Shanghai Municipal Education Commission Scientific Research and Innovation Program (2021-01-07-00-02-E00082), the Clinical Research Center of Shanghai University of Medicine & Health Sciences (20MC2020003), the Academician Expert Workstation of the Jinshan District (jszjz2020007Y), the Plan of Medical Key Specialty Construction, and the Shanghai Health Committee (ZK2019B03).

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Author notes

  1. Haitao Li and Jiangchang Xu contributed equally to the present study.

Authors and Affiliations

  1. Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Room A-925, Dongchuan Road 800, Minhang District, Shanghai, 200240, China

    Haitao Li, Jiangchang Xu, Dingzhong Zhang & Xiaojun Chen

  2. Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 600 Yishan Road, Shanghai, 200233, China

    Yaohua He

  3. Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China

    Xiaojun Chen

  4. Department of Orthopaedics, Jinshan Branch of Shanghai Sixth People’s Hospital Affiliated to Shanghai University of Medicine & Health Sciences, 147 Jiankang Road, Shanghai, 201503, China

    Yaohua He

Authors
  1. Haitao Li
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  2. Jiangchang Xu
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Correspondence to Yaohua He or Xiaojun Chen.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Li, H., Xu, J., Zhang, D. et al. Automatic surgical planning based on bone density assessment and path integral in cone space for reverse shoulder arthroplasty. Int J CARS 17, 1017–1027 (2022). https://doi.org/10.1007/s11548-022-02633-z

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  • DOI: https://doi.org/10.1007/s11548-022-02633-z

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