Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction.

Journal: European journal of cancer (Oxford, England : 1990)
PMID: 40022836

Abstract

PURPOSE: Artificial intelligence (AI) could reduce lung cancer screening computer tomography (CT)-reading workload if used as a first-reader, ruling-out negative CT-scans at baseline. Evidence is lacking to support AI performance when compared to gold-standard lung cancer outcomes. This study validated the performance of a commercially available AI software in the UK lung cancer screening (UKLS) trial dataset, with comparison to human reads and histological lung cancer outcomes, and estimated CT-reading workload reduction.

Authors

  • Harriet L Lancaster
    Institute for Diagnostic Accuracy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands.
  • Beibei Jiang
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.
  • Michael P A Davies
    Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom.
  • Jan Willem C Gratama
  • Mario Silva
    Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Jaeyoun Yi
    Coreline Soft, Co., Ltd., Sung-Myung B/D 5F, World Cup buk-ro 6-gil 49, Mapo-Gu, Seoul 03991, South Korea.
  • Marjolein A Heuvelmans
    University Medical Center Groningen, Department of Epidemiology, University of Groningen, 9700 RB Groningen, Netherlands; Department of Pulmonology, Medisch Spectrum Twente, Enschede, Netherlands. Electronic address: m.a.heuvelmans@umcg.nl.
  • Geertruida H de Bock
    University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Anand Devaraj
    Department of Radiology, Royal Brompton and Harefield NHS Foundation Trust,, London, UK; National Heart and Lung Institute, Imperial College London, London, UK.
  • John K Field
    Roy Castle Lung Cancer Research Programme, The University of Liverpool, Department of Molecular and Clinical Cancer Medicine, Liverpool, United Kingdom.
  • Matthijs Oudkerk
    University Medical Center, Groningen, The Netherlands.

Keywords

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