Early-stage lung cancer detection via thin-section low-dose CT reconstruction combined with AI in non-high risk populations: a large-scale real-world retrospective cohort study.
Authors
Affiliations (16)
Affiliations (16)
- Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu 610041, China.
- State Key Laboratory of Respiratory Health and Multimorbidity, West China Hospital, Sichuan University, Chengdu 610041, China.
- Department of Pulmonary and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
- Institute of Respiratory Health, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.
- Precision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China.
- Engineering Research Center of Medical Information Technology, Ministry of Education, West China Hospital, Sichuan University, Chengdu 610041, China.
- Information Center, West China Hospital, Sichuan University, Chengdu 610041, China.
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China.
- National Clinical Research Center for Geriatrics (WCH), West China Hospital, Sichuan University, Chengdu 610041, China.
- Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China.
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China.
- Health Management Center, First Affiliated Hospital of Army Medical University (Third Military Medical University), Chongqing 400900, China.
- General Practice Ward/International Medical Center Ward, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu 610041, China.
- Integrated care management center, West China Hospital, Sichuan University, Chengdu 610041, China.
- Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu 610041, China.
- The Research Units of West China, Chinese Academy of Medical Sciences, West China Hospital, Sichuan University, Chengdu 610041, China.
Abstract
Current lung cancer screening guidelines recommend annual low-dose computed tomography (LDCT) for high-risk individuals. However, the effectiveness of LDCT in non-high-risk individuals remains inadequately explored. With the incidence of lung cancer steadily increasing among non-high-risk individuals, this study aims to assess the risk of lung cancer in non-high-risk individuals and evaluate the potential of thin-section LDCT reconstruction combined with artificial intelligence (LDCT-TRAI) as a screening tool. A real-world cohort study on lung cancer screening was conducted at the West China Hospital of Sichuan University from January 2010 to July 2021. Participants were screened using either LDCT-TRAI or traditional thick-section LDCT without AI (traditional LDCT) . The AI system employed was the uAI-ChestCare software. Lung cancer diagnoses were confirmed through pathological examination. Among the 259 121 enrolled non-high-risk participants, 87 260 (33.7%) had positive screening results. Within 1 year, 728 (0.3%) participants were diagnosed with lung cancer, of whom 87.1% (634/728) were never-smokers, and 92.7% (675/728) presented with stage I disease. Compared with traditional LDCT, LDCT-TRAI demonstrated a higher lung cancer detection rate (0.3% vs. 0.2%, <i>P</i> < 0.001), particularly for stage I cancers (94.4% vs. 83.2%, <i>P</i> < 0.001), and was associated with improved survival outcomes (5-year overall survival rate: 95.4% vs. 81.3%, <i>P</i> < 0.0001). These findings highlight the importance of expanding lung cancer screening to non-high-risk populations, especially never-smokers. LDCT-TRAI outperformed traditional LDCT in detecting early-stage cancers and improving survival outcomes, underscoring its potential as a more effective screening tool for early lung cancer detection in this population.