ArticleJournal of digital imaging2014
Automated 3D ιnterstitial lung disease εxtent quantification: performance evaluation and correlation to PFTs.
Article in Journal of digital imaging, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Emphysema progression is visually detectable in low-dose CT in continuous but not in former smokers.European radiology · 2014Trial
- Computed tomography-based quantitative scoring system for rheumatoid arthritis-associated interstitial lung disease: a retrospective diagnostic accuracy study for progressive fibrosis detection.Clinical rheumatology · 2025Article
- Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.Respiratory research · 2025Article
- Assessment of cardiopulmonary manifestations and its correlation with semi-quantitative scoring of high-resolution computed tomography in patients with autoimmune rheumatic diseases.BMC pulmonary medicine · 2023Article
- [Artificial intelligence-based algorithms : Decision-making support for computed tomography of the chest].Der Radiologe · 2020Review
- Quantitative computed tomography assessment for systemic sclerosis-related interstitial lung disease: comparison of different methods.European radiology · 2020Article
- Outcome Measures for Clinical Trials in Interstitial Lung Diseases.Current respiratory medicine reviewsArticle
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8 authors.
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Abstract
In this study, the performance of a recently proposed computer-aided diagnosis (CAD) scheme in detection and 3D quantification of reticular and ground glass pattern extent in chest computed tomography of interstitial lung disease (ILD) patients is evaluated. CAD scheme performance was evaluated on a dataset of 37 volumetric chest scans, considering five representative axial anatomical levels per scan. CAD scheme reliability analysis was performed by estimating agreement (intraclass correlation coefficient, ICC) of automatically derived ILD pattern extent to semi-quantitative disease extent assessment in terms of 29-point rating scale provided by two expert radiologists. Receiver operating characteristic (ROC) analysis was employed to assess CAD scheme accuracy in ILD pattern detection in terms of area under ROC curve (A z ). Correlation of reticular and ground glass volumetric pattern extent to pulmonary function tests (PFTs) was also investigated. CAD scheme reliability was substantial for ILD extent (ICC = 0.809) and distinct reticular pattern extent (0.806) and moderate for distinct ground glass pattern extent (0.543), performing within inter-observer agreement. CAD scheme demonstrated high accuracy in detecting total ILD (A z = 0.950 ± 0.018), while accuracy in detecting distinct reticular and ground glass patterns was 0.920 ± 0.023 and 0.883 ± 0.024, respectively. Moderate and statistically significant negative correlation was found between reticular volumetric pattern extent and diffusing capacity, forced expiratory volume in 1 s, forced vital capacity, and total lung capacity (R = -0.581, -0.513, -0.494, and -0.446, respectively), similar to correlations found between radiologists' semi-quantitative ratings with PFTs. CAD-based quantification of disease extent is in agreement with radiologists' semi-quantitative assessment and correlates to specific PFTs, suggesting a potential imaging biomarker for ILD staging and management.
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