Whole slide image-level classification of malignant effusion cytology using clustering-constrained attention multiple instance learning.

Journal: Lung cancer (Amsterdam, Netherlands)
Published Date: Apr 21, 2025

Abstract

BACKGROUND: Cytological diagnosis of pleural effusion plays an important role in the early detection and diagnosis of lung cancers. Recently, attempts have been made to overcome low diagnostic accuracy and interobserver variability using artificial intelligence-based image analysis. However, such analysis is primarily performed at the image-patch level and not at the whole-slide image (WSI) level. This study aims to develop a WSI-level classification of malignant effusions in metastatic lung cancer based on pleural fluid cytology using a quality-controlled, nationwide dataset.

Authors

  • Dongwoo Kim
    From the Department of Nuclear Medicine, Yonsei University College of Medicine.
  • Jongwon Lee
    Center for Single Atom-based Semiconductor Device and Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.
  • Minsoo Jung
    The Catholic University of Korea College of Medicine, Seoul, South Korea.
  • Kwangil Yim
    Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
  • Gisu Hwang
    AI Team, DeepNoid Inc., Seoul 08376, Republic of Korea.
  • Hongjun Yoon
    Innovative Medical Engineering and Technology Branch, Research Institute and Hospital, National Cancer Center, Goyang, Gyeonggi, South Korea.
  • Daeky Jeong
    AI Research Lab, DEEPNOID Inc., Seoul, South Korea.
  • Won June Cho
    AI Research Lab, DEEPNOID Inc., Seoul, South Korea.
  • Mohammad Rizwan Alam
    Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
  • Gyungyub Gong
    Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Nam Hoon Cho
    Department of Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea. cho1988@yuhs.ac.
  • Chong Woo Yoo
    Department of Pathology, National Cancer Center, Ilsan, Goyang-si 10408, Gyeonggi-do, Republic of Korea.
  • Yosep Chong
    Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, 271, Cheonbo-ro, Uijeongbu, 11765, Gyeonggi-do, Republic of Korea. ychong@catholic.ac.kr.
  • Kyung Jin Seo
    Department of Hospital Pathology, Uijeongbu St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals