TY - JOUR
T1 - AI integrations with lung cancer screening
T2 - Considerations in developing AI in a public health setting
AU - Mulshine, James L.
AU - Avila, Ricardo S.
AU - Silva, Mario
AU - Aldige, Carolyn
AU - Blum, Torsten
AU - Cham, Matthew
AU - de Koning, Harry J.
AU - Fain, Sean B.
AU - Field, John
AU - Flores, Raja
AU - Giger, Maryellen L.
AU - Gipp, Ilya
AU - Grannis, Frederic W.
AU - Gratama, Jan Willem C.
AU - Healton, Cheryl
AU - Kazerooni, Ella A.
AU - Kelly, Karen
AU - Lancaster, Harriet L.
AU - Montuenga, Luis M.
AU - Myers, Kyle J.
AU - Naghavi, Morteza
AU - Osarogiagbon, Raymond
AU - Pastorino, Ugo
AU - Pyenson, Bruce S.
AU - Reeves, Anthony P.
AU - Rizzo, Albert
AU - Ross, Sheila
AU - Schneider, Victoria
AU - Seijo, Luis M.
AU - Shaham, Dorith
AU - Smith, Robert
AU - Taoli, Emanuela
AU - Tenhaaf,
AU - van der Aalst, Carlijn M.
AU - Viola, Lucia
AU - Vogel-Claussen, Jens
AU - Walstra, Anna N.H.
AU - Wu, Ning
AU - Yang, Pan Chyr
AU - Yip, Rowena
AU - Oudkerk, Matthijs
AU - Henschke, Claudia I.
AU - Yankelelvitz, David F.
N1 - Publisher Copyright:
© 2025 Elsevier Ltd
PY - 2025/5/2
Y1 - 2025/5/2
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Chest CT scan
KW - Chronic obstructive pulmonary disease
KW - Coronary artery disease
KW - Emphysema
KW - Lung cancer
KW - Lung cancer screening
UR - https://www.scopus.com/pages/publications/105000074739
U2 - 10.1016/j.ejca.2025.115345
DO - 10.1016/j.ejca.2025.115345
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.systematicreview???
C2 - 40090215
AN - SCOPUS:105000074739
SN - 0959-8049
VL - 220
JO - European Journal of Cancer
JF - European Journal of Cancer
M1 - 115345
ER -
SDG 3 Good Health and Well-being