ArticleFrontiers in physiology2025
Longitudinal analysis of coal workers' pneumoconiosis using enhanced resolution-computed tomography images: unveiling patterns in lung structure, function, and clinical correlations.
Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Artificial intelligence in quantitative chest imaging analysis for occupational lung disease: appraisal of its current status.Current opinion in pulmonary medicine · 2026Review
- Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.Frontiers in medicine · 2025Article
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3 authors.
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Abstract
Rationale: Pneumoconiosis, caused by prolonged exposure to mineral dust, leads to progressive structural and functional lung alterations. Quantitative computed tomography (qCT) has emerged as a critical tool for assessing these changes, yet there is limited research on the longitudinal patterns in pneumoconiosis patients. Methods: This study examined a cohort of 31 former coal workers with pneumoconiosis over a 1-year period. Inspiratory qCT images were enhanced using a deep learning-based super-resolution model and then processed to extract lung functional and airway structural metrics. A non-rigid image registration process was performed with baseline images as fixed and follow-up images as moving. Registration-derived metrics, including anisotropic deformation index (ADI), slab rod index (SRI), and Jacobian (J), were extracted to quantify regional deformation longitudinally. Pulmonary function tests, including forced expiratory volume in one second (FEV Results: The study identified significant airway changes in angles, diameters, and geometry, with a decrease in normal lung tissue in the right upper lobe. Blood vessel volumes declined, indicating vascular remodeling. Registration metrics revealed regional heterogeneity, with higher ADI and SRI values and localized volume loss (J) in the lower lobes. FEV Conclusion: qCT imaging and registration metrics effectively monitor structural and functional lung changes in pneumoconiosis. Registering baseline and follow-up inspiration images offers additionally valuable insights into disease progression.
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