ArticleJournal of the Korean Society of Radiology2024
Long-Term Follow-Up of Interstitial Lung Abnormalities in Low-Dose Chest CT in Health Screening: Exploring the Predictors of Clinically Significant Interstitial Lung Diseases Using Artificial Intelligence-Based Quantitative CT Analysis.
Article in Journal of the Korean Society of Radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Unsupervised segmentation of dynamic pulmonary MRI using cross-modality adaptation with annotated CT images.International journal of computer assisted radiology and surgery · 2026Article
- Current diagnosis, epidemiology, and management of interstitial lung abnormalities.Frontiers in medicine · 2026Review
- Effect of contrast enhancement on diagnosis of interstitial lung abnormality in automatic quantitative CT measurement.European radiology · 2025Article
- [Annual Report ofJournal of the Korean Society of Radiology · 2025Article
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9 authors.
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Abstract
Purpose: This study examined longitudinal changes in interstitial lung abnormalities (ILAs) and predictors of clinically significant interstitial lung diseases (ILDs) in a screening population with ILAs. Materials and Methods: We retrieved 36891 low-dose chest CT records from screenings between January 2003 and May 2021. After identifying 101 patients with ILAs, the clinical findings, spirometry results, and initial and follow-up CT findings, including visual and artificial intelligence-based quantitative analyses, were compared between patients diagnosed with ILD ( Results: Twenty-three patients ( Conclusion: Clinically significant ILD was subsequently diagnosed in approximately one-quarter of the screened population with ILAs. Emerging respiratory symptoms and progression of ILAs at follow-up chest CT can be predictors of clinically significant ILDs.
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