Deep-learning based electromagnetic navigation system for transthoracic percutaneous puncture of small pulmonary nodules.

Journal: Scientific reports
PMID: 39833245

Abstract

Percutaneous transthoracic puncture of small pulmonary nodules is technically challenging. We developed a novel electromagnetic navigation puncture system for the puncture of sub-centimeter lung nodules by combining multiple deep learning models with electromagnetic and spatial localization technologies. We compared the performance of DL-EMNS and conventional CT-guided methods in percutaneous lung punctures using phantom and animal models. In the phantom study, the DL-EMNS group showed a higher technical success rate (95.6% vs. 77.8%, p = 0.027), smaller error (1.47 ± 1.62 mm vs. 3.98 ± 2.58 mm, p < 0.001), shorter procedure duration (291.56 ± 150.30 vs. 676.44 ± 246.12 s, p < 0.001), and fewer number of CT acquisitions (1.2 ± 0.66 vs. 2.93 ± 0.98, p < 0.001) compared to the traditional CT-guided group. In the animal study, DL-EMNS significantly improved technical success rate (100% vs. 84.0%, p = 0.015), reduced operation time (121.36 ± 38.87 s vs. 321.60 ± 129.12 s, p < 0.001), number of CT acquisitions (1.09 ± 0.29 vs. 2.96 ± 0.73, p < 0.001) and complication rate (0% vs. 20%, p = 0.002). In conclusion, with the assistance of DL-EMNS, the operators got better performance in the percutaneous puncture of small pulmonary nodules.

Authors

  • Muyun Peng
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Xinyi Fan
    Infervision Medical Technology Co., Ltd., Beijing, China.
  • Qikang Hu
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Xilong Mei
    Department of Radiology, The Second Xiangya Hospital of Central South University.
  • Bin Wang
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China; New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga 2650, Australia. Electronic address: bin.a.wang@dpi.nsw.gov.au.
  • Zeyu Wu
    School of Food and Biological Engineering, Hefei University of Technology, Hefei 230601, China; Engineering Research Center of Bio-Process, Ministry of Education, Hefei University of Technology, Hefei 230601, China. Electronic address: wuzeyu@hfut.edu.cn.
  • Huali Hu
    Department of Thoracic Surgery, Hunan Rehabilitation Hospital, Changsha, China.
  • Lei Tang
    Department of Neurology, Xiangya Hospital, Central South University, Jiangxi, Nanchang, 330006, Jiangxi, China.
  • Xinhang Hu
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, 139 Renmin Road, Changsha, 410011, Hunan, China.
  • Yanyi Yang
    Health Management Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
  • Chunxia Qin
    Infervision Medical Technology Co., Ltd., Beijing, China.
  • Huajie Zhang
    Infervision Medical Technology Co., Ltd., Beijing, China.
  • Qun Liu
    Department of Burn and Plastic Surgery, the Fourth Hospital of Tianjin, Tianjin 300222, China; Email: 1502831499@qq.com.
  • Xiaofeng Chen
    Department of Mathematics, Chongqing Jiaotong University, Chongqing, 400074, China; Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30302, USA. Electronic address: xxffch@126.com.
  • Fenglei Yu
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China. yufenglei@csu.edu.cn.

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