Potential to improve early detection of lung cancer through expansion of focused and opportunistic screening approaches: a scoping review focusing on potential expansion of screening risk factors and adoption of artificial intelligence models
Year: 2026
Type: review
Abstract: BACKGROUND: Low-dose computerized tomography (LDCT) is the gold standard for lung cancer (LC) screening, but access is hindered by strict eligibility criteria and limited infrastructure in low/middle-income countries. A combination of approaches, including expanded screening eligibility criteria and artificial intelligence (AI), could improve detection of early LC in patients excluded by current screening criteria. AREAS COVERED: A scoping review was conducted (PubMed, Cochrane library, congresses) to explore two potentially complementary approaches to enhance LC screening. The first identified LC risk factors and their potential inclusion in expanded screening criteria, allowing more people at risk to become eligible for screening; the second examined studies involving AI-augmented imaging (CXR or LDCT) to improve workflow, triage, and opportunistic nodule detection. EXPERT OPINION/COMMENTARY: Several robustly evidenced risk factors for LC were identified that are not included in current screening programs; widening of eligibility criteria could be considered based on local risk profile but requires further research to demonstrate benefit. Opportunistic use of AI-tools to assess incidental chest images may identify patients with pulmonary nodules requiring further investigation but their role in population-level LC screening requires prospective validation in diverse healthcare systems.
Source: Lung Cancer Management
Institutions: Chinese University of Hong Kong, McMaster University, Hacettepe University, NYU Langone Health, NYU Langone’s Laura and Isaac Perlmutter Cancer Center, Kaiser Permanente, University of California, San Francisco, University of California San Francisco Medical Center, Kaiser Permanente Bernard J. Tyson School of Medicine, Kaiser Permanente Northern California, National Taiwan University
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7221678156