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Preoperative planning method based on a MOPSO algorithm for robot-assisted cholecystectomy

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

Abstract

Purpose

Surgical robots have multiple manipulators with complex mechanisms and need to work in a narrow space in the patient’s body. Therefore, for robot-assisted minimally invasive surgery (RMIS), it is very important to develop a reasonable preoperative planning before surgery.

Methods

A preoperative planning method based on the premise of no collision between surgical instruments and endoscope, an evaluation index with visibility, operability and hand–eye coordination was proposed in this paper. To consider the balance relationship of global optimization index, a multi-objective particle swarm optimization (MOPSO) algorithm was adopted. Because the physical characteristics of each patient are different, the method can determine the selectable area of the incision based on the relevant knowledge of anatomy.

Results

The simulation taking the cholecystectomy as an example was performed on a minimally invasive surgical robotic system. The analysis result showed that the proposed preoperative planning method based on the MOPSO could provide surgeons with a reasonable and effective preoperative planning.

Conclusions

The proposed preoperative planning method based on the MOPSO is suitable for patients with different physical characteristics, and can provide a guidance for surgeons and effectively reduce the preoperative planning time and improve the safety and efficiency of the operation, especially a novice surgeon who lacks robot-assisted minimally invasive surgery experience.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (NSFC) (Grant No. 51975409).

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Authors and Affiliations

  1. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao, 266061, China

    Yan Yang

  2. School of Mechanical Engineering and Tianjin Key Laboratory of Advanced Mechatronic Equipment Technology, Tiangong University, No.399, Binshui West Road, Xiqing District, Tianjin, 300387, China

    Shuai Han, Hongqiang Sang & Fen Liu

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  1. Yan Yang
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  2. Shuai Han
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  4. Fen Liu
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Correspondence to Hongqiang Sang.

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Yang, Y., Han, S., Sang, H. et al. Preoperative planning method based on a MOPSO algorithm for robot-assisted cholecystectomy. Int J CARS 17, 731–744 (2022). https://doi.org/10.1007/s11548-021-02547-2

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  • DOI: https://doi.org/10.1007/s11548-021-02547-2

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