Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks.

Journal: BMC cancer
PMID: 40211197

Abstract

OBJECTIVE: The infiltration status of pulmonary ground-glass nodules (GGNs) exhibits significant variability, demanding tailored surgical strategies and individualized postoperative adjuvant therapies. This study explored the preoperative assessment of GGN infiltration status using computed tomography (CT) imaging integrated with a neural network to enhance the precision of clinical decision-making in surgical planning and therapeutic interventions.

Authors

  • Kun Mei
    Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Soochow University, Changzhou, China.
  • Zikang Feng
    School of Computer Science and Technology, Nanjing Tech University, Nanjing, China.
  • Hui Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Min Wang
    National and Local Joint Engineering Research Center of Ecological Treatment Technology for Urban Water Pollution, Wenzhou University, Wenzhou 325035, China.
  • Chao Ce
    Department of Cardiothoracic Surgery, The Third Affiliated Hospital of Soochow University, Changzhou, China.
  • Shi Yin
    School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, United States.
  • Xiaoying Zhang
    College of Veterinary Medicine, Northwest A&F UniversityYangling, China; Chinese-German Joint Laboratory for Natural Product Research, Qinling-Bashan Mountains Bioresources Comprehensive Development C.I.C., College of Biological Science and Engineering, Shaanxi University of TechnologyHanzhong, China.
  • 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.

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