ArticlePrecision clinical medicine2025
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.
Article in Precision clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparative effectiveness and safety of robotic versus laparoscopic liver resection for benign liver diseases: a systematic review and meta-analysis.BMC gastroenterology · 2026Pooled it
- LungGPT: A unified multimodal system for interpretable diagnosis and clinical decision support of respiratory diseases.Cell reports. Medicine · 2026Article
- Anatomical-Contextual YOLOv8-YOLOv12 Framework for Pulmonary Nodule Detection in CT: Multi-Organ Learning and Cross-Dataset Validation.Diagnostics (Basel, Switzerland) · 2026Article
- Multi-omics profiling of recurrence-associated extrachromosomal circular DNA characteristics and its prognostic potential in lung adenocarcinoma.Precision clinical medicine · 2026Article
- Clinical features and prognostic factor of small (≤2 cm) lung cancer associated with cystic airspaces.Journal of thoracic disease · 2026Article
- Imaging features of lung cancer with cystic airspaces: clinical utility, challenges, and perspectives.Frontiers in oncology · 2026Review
- Radiographic evidence of thymic involution in hepatocellular carcinoma: a propensity score-matched study in viral cirrhosis.Frontiers in immunology · 2026Article
- Association of physical component score with high-risk lung nodules among Chinese Urban sanitation workers: a sex-specific analysis.Frontiers in public health · 2026Article
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24 authors.
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Abstract
Background: 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. Methods: 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. Results: 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%, Conclusion: 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.
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