Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.

Journal: BMC pulmonary medicine
Published Date: Jul 2, 2025

Abstract

BACKGROUND: Endobronchial ultrasound (EBUS) is a widely used imaging modality for evaluating thoracic lymph nodes (LNs), particularly in the staging of lung cancer. Artificial intelligence (AI)-assisted EBUS has emerged as a promising tool to enhance diagnostic accuracy. However, its effectiveness in differentiating benign from malignant thoracic LNs remains uncertain. This meta-analysis aimed to evaluate the diagnostic performance of AI-assisted EBUS compared to the pathological reference standards.

Authors

  • Fei Tang
    Division of Biostatistics, University of Miami.
  • Xian-Kui Zha
    Respiratory and Critical Care Medicine Department and Endoscopic Diagnosis and Treatment Center, Anhui Chest Hospital, Hefei, 230022, Anhui Province, China.
  • Wei Ye
    AliveX Biotech, Shanghai, China.
  • Yue-Ming Wang
    Respiratory and Critical Care Medicine Department and Endoscopic Diagnosis and Treatment Center, Anhui Chest Hospital, Hefei, 230022, Anhui Province, China.
  • Ying-Feng Wu
    Respiratory and Critical Care Medicine Department and Endoscopic Diagnosis and Treatment Center, Anhui Chest Hospital, Hefei, 230022, Anhui Province, China.
  • Li-Na Wang
    College of Chemistry, Nanchang University, Nanchang, 330031, China.
  • Li-Ping Lyu
    Respiratory and Critical Care Medicine Department and Endoscopic Diagnosis and Treatment Center, Anhui Chest Hospital, Hefei, 230022, Anhui Province, China.
  • Xiao-Mei Lyu
    Respiratory and Critical Care Medicine Department and Endoscopic Diagnosis and Treatment Center, Anhui Chest Hospital, Hefei, 230022, Anhui Province, China.

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