Review

.2024 Jan;19(1):36-51.

doi: 10.1016/j.jtho.2023.07.019. Epub 2023 Jul 23.

Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer

Stephen Lam¹, Chunxue Bai², David R Baldwin³, Yan Chen⁴, Casey Connolly⁵, Harry de Koning⁶, Marjolein A Heuvelmans⁷, Ping Hu⁸, Ella A Kazerooni⁹, Harriet L Lancaster⁷, Georg Langs¹⁰, Annette McWilliams¹¹, Raymond U Osarogiagbon¹², Matthijs Oudkerk¹³, Matthew Peters¹⁴, Hilary A Robbins¹⁵, Liora Sahar¹⁶, Robert A Smith¹⁷, Natthaya Triphuridet¹⁸, John Field¹⁹

Affiliations

¹ Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. Electronic address: slam2@bccancer.bc.ca.
² Shanghai Respiratory Research Institute and Chinese Alliance Against Cancer, Shanghai, People's Republic of China.
³ Nottingham University Hospitals National Health Services (NHS) Trust, Nottingham, United Kingdom.
⁴ Digital Screening, Faculty of Medicine & Health Sciences, University of Nottingham Medical School, Nottingham, United Kingdom.
⁵ International Association for the Study of Lung Cancer, Denver, Colorado.
⁶ Department of Public Health, Erasmus MC University Medical Centre Rotterdam, The Netherlands.
⁷ University of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands.
⁸ Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
⁹ Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.
¹⁰ Computational Imaging Research Laboratory, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
¹¹ Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia; Australia University of Western Australia, Nedlands, Western Australia.
¹² Thoracic Oncology Research Group, Baptist Cancer Center, Memphis, Tennessee.
¹³ Center for Medical Imaging and The Institute for Diagnostic Accuracy, Faculty of Medical Sciences, University of Groningen, Groningen, The Netherlands.
¹⁴ Woolcock Institute of Respiratory Medicine, Macquarie University, Sydney, New South Wales, Australia.
¹⁵ Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
¹⁶ Data Science, American Cancer Society, Atlanta, Georgia.
¹⁷ Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia.
¹⁸ Department of Medicine, Chulabhorn Hospital, Bangkok, Thailand.
¹⁹ Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, Liverpool, United Kingdom.

PMID:37487906
PMCID: PMC11253723
DOI: 10.1016/j.jtho.2023.07.019

Review

Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer

Stephen Lam et al. J Thorac Oncol.2024 Jan.

.2024 Jan;19(1):36-51.

doi: 10.1016/j.jtho.2023.07.019. Epub 2023 Jul 23.

Authors

Affiliations

¹ Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. Electronic address: slam2@bccancer.bc.ca.
² Shanghai Respiratory Research Institute and Chinese Alliance Against Cancer, Shanghai, People's Republic of China.
³ Nottingham University Hospitals National Health Services (NHS) Trust, Nottingham, United Kingdom.
⁴ Digital Screening, Faculty of Medicine & Health Sciences, University of Nottingham Medical School, Nottingham, United Kingdom.
⁵ International Association for the Study of Lung Cancer, Denver, Colorado.
⁶ Department of Public Health, Erasmus MC University Medical Centre Rotterdam, The Netherlands.
⁷ University of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands.
⁸ Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
⁹ Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan.
¹⁰ Computational Imaging Research Laboratory, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
¹¹ Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia; Australia University of Western Australia, Nedlands, Western Australia.
¹² Thoracic Oncology Research Group, Baptist Cancer Center, Memphis, Tennessee.
¹³ Center for Medical Imaging and The Institute for Diagnostic Accuracy, Faculty of Medical Sciences, University of Groningen, Groningen, The Netherlands.
¹⁴ Woolcock Institute of Respiratory Medicine, Macquarie University, Sydney, New South Wales, Australia.
¹⁵ Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
¹⁶ Data Science, American Cancer Society, Atlanta, Georgia.
¹⁷ Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia.
¹⁸ Department of Medicine, Chulabhorn Hospital, Bangkok, Thailand.
¹⁹ Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, Liverpool, United Kingdom.

PMID:37487906
PMCID: PMC11253723
DOI: 10.1016/j.jtho.2023.07.019

Abstract

Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting.

Keywords: Incidentally detected lung nodules; Lung cancer LDCT screening; Never-smokers; Quality indicators.

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Figures

**Figure 1.**
Cochrane library: lung cancer-related mortality in eight RCTs. Bonney et al., 2022 permission by John Wiley and Sons. CI, confidence interval; LDCT, low-dose computed tomography; M-H, Mantel-Haenszel; RCT, randomized controlled trials; RR, risk ratio.

**Figure 2.**
A wide range of biospecimens and approaches proposed for lung cancer screening (Seijo, L.M., et al., Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges, 2019). miRNA, microRNA.

**Figure 3.**
Role of AI in lung cancer screening. AI, artificial intelligence.

**Figure 4.**
Five-year roadmap to advance global implementation of lung cancer screening. AI, artificial intelligence, CT, computed tomography; IASLC, International Association for the Study of Lung Cancer.

See this image and copyright information in PMC

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Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer

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Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer

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