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Review
. 2025 May 2:220:115345.
doi: 10.1016/j.ejca.2025.115345. Epub 2025 Mar 6.

AI integrations with lung cancer screening: Considerations in developing AI in a public health setting

James L Mulshine  1 , Ricardo S Avila  2 , Mario Silva  3 , Carolyn Aldige  4 , Torsten Blum  5 , Matthew Cham  6 , Harry J de Koning  7 , Sean B Fain  8 , John Field  9 , Raja Flores  10 , Maryellen L Giger  11 , Ilya Gipp  12 , Frederic W Grannis  13 , Jan Willem C Gratama  14 , Cheryl Healton  15 , Ella A Kazerooni  16 , Karen Kelly  17 , Harriet L Lancaster  18 , Luis M Montuenga  19 , Kyle J Myers  20 , Morteza Naghavi  21 , Raymond Osarogiagbon  22 , Ugo Pastorino  23 , Bruce S Pyenson  24 , Anthony P Reeves  25 , Albert Rizzo  26 , Sheila Ross  27 , Victoria Schneider  28 , Luis M Seijo  29 , Dorith Shaham  30 , Robert Smith  31 , Emanuela Taoli  32 , Kevin Ten Haaf  33 , Carlijn M van der Aalst  34 , Lucia Viola  35 , Jens Vogel-Claussen  36 , Anna N H Walstra  37 , Ning Wu  38 , Pan-Chyr Yang  39 , Rowena Yip  40 , Matthijs Oudkerk  41 , Claudia I Henschke  42 , David F Yankelelvitz  43
Affiliations
Review

AI integrations with lung cancer screening: Considerations in developing AI in a public health setting

James L Mulshine et al. Eur J Cancer. .

Abstract

Lung cancer screening implementation has led to expanded imaging of the chest in older, tobacco-exposed populations. Growing numbers of screening cases are also found to have CT-detectable emphysema or elevated levels of coronary calcium, indicating the presence of coronary artery disease. Early interventions based on these additional findings, especially with coronary calcium, are emerging and follow established protocols. Given the pace of diagnostic innovation and the potential public health impact, it is timely to review issues in developing useful chest CT screening infrastructure as chest CT screening will soon involve millions of participants worldwide. Lung cancer screening succeeds because it detects curable, early primary lung cancer by characterizing and measuring changes in non-calcified, lung nodules in the size-range from 3mm to 15 mm in diameter. Therefore, close attention to imaging methodology is essential to lung screening success and similar image quality issues are required for reliable quantitative characterization of early emphysema and coronary artery disease. Today's emergence of advanced image analysis using artificial intelligence (AI) is disrupting many aspects of medical imaging including chest CT screening. Given these emerging technological and volume trends, a major concern is how to balance the diverse needs of parties committed to building AI tools for precise, reproducible, and economical chest CT screening, while addressing the public health needs of screening participants receiving this service. A new consortium, the Alliance for Global Implementation of Lung and Cardiac Early Disease Detection and Treatment (AGILEDxRx) is committed to facilitate broad, equitable implementation of multi-disciplinary, high quality chest CT screening using advanced computational tools at accessible cost.

Keywords: Artificial intelligence; Chest CT scan; Chronic obstructive pulmonary disease; Coronary artery disease; Emphysema; Lung cancer; Lung cancer screening.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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