A systematic review of image-guided, surgical robot-assisted percutaneous puncture: Challenges and benefits.

Journal: Mathematical biosciences and engineering : MBE
PMID:

Abstract

Percutaneous puncture is a common medical procedure that involves accessing an internal organ or tissue through the skin. Image guidance and surgical robots have been increasingly used to assist with percutaneous procedures, but the challenges and benefits of these technologies have not been thoroughly explored. The aims of this systematic review are to furnish an overview of the challenges and benefits of image-guided, surgical robot-assisted percutaneous puncture and to provide evidence on this approach. We searched several electronic databases for studies on image-guided, surgical robot-assisted percutaneous punctures published between January 2018 and December 2022. The final analysis refers to 53 studies in total. The results of this review suggest that image guidance and surgical robots can improve the accuracy and precision of percutaneous procedures, decrease radiation exposure to patients and medical personnel and lower the risk of complications. However, there are many challenges related to the use of these technologies, such as the integration of the robot and operating room, immature robotic perception, and deviation of needle insertion. In conclusion, image-guided, surgical robot-assisted percutaneous puncture offers many potential benefits, but further research is needed to fully understand the challenges and optimize the utilization of these technologies in clinical practice.

Authors

  • Kai Cheng
    Department of Radiation Oncology, Stanford University, Stanford, California.
  • Lixia Li
    Department of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Yanmin Du
    Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China.
  • Jiangtao Wang
    Henan Children's Hospital, No.33, Longhu Outer Ring Road, Zheng Dong New District, Zhengzhou, Henan, China.
  • Zhenghua Chen
  • Jian Liu
    Department of Rheumatology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China.
  • Xiangsheng Zhang
    Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China.
  • Lin Dong
    Environmental Exposures Vascular Disease Institute, Shanxi Medical University, Taiyuan, Shanxi, China.
  • Yuanyuan Shen
    Knowledge Engineering and Discovery Research Institute (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.
  • Zhenlin Yang
    Yantai Affiliated Hospital of Binzhou Medical University, Yantai, Shandong 264100, China.