ArticleJapanese journal of radiology2017
Extraction of the subpleural lung region from computed tomography images to detect interstitial lung disease.
Article in Japanese journal of radiology, 2017. 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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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Integrating CT-Based Lung Fibrosis and MRI-Derived Right Ventricular Function for the Detection of Pulmonary Hypertension in Interstitial Lung Disease.Journal of clinical medicine · 2025Article
- Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis.Diagnostics (Basel, Switzerland) · 2022Article
- Boundary Restored Network for Subpleural Pulmonary Lesion Segmentation on Ultrasound Images at Local and Global Scales.Journal of digital imaging · 2020Article
- Smoking-related lung abnormalities on computed tomography images: comparison with pathological findings.Japanese journal of radiology · 2018Review
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8 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo quantify lesions in the subpleural lung region (SubPL) on computed tomography (CT) images and to evaluate whether they are useful for detecting interstitial lung disease (ILD). MATERIALS AND
methodsThe subjects were 40 patients with idiopathic pulmonary fibrosis (IPF) diagnosed by multidisciplinary methods and 35 age-matched patients without ILDs. The lungs and SubPL were extracted from CT images using a Gaussian histogram normalized correlation system and evaluated for the mean CT attenuation value (CTmean) and the percentage of high attenuation area (%HAA), exceeding -700 Hounsfield units. The H pattern was defined as a honeycomb appearance and/or fibrosis with traction bronchiectasis, and the H-pattern volume ratios for the whole lung and the 2-mm-wide SubPL were measured. The utility of the SubPL for detecting ILD was evaluated by receiver operating characteristic (ROC) analysis.
resultsThe areas under the ROC curves (AUCs) of CTmean and %HAA for the SubPL were greater than those for the whole lung. The AUCs for the whole lung and the SubPL were 0.990 and 0.994, respectively, for H-pattern volume; 0.875 and 0.994, respectively, for CTmean; and 0.965 and 0.991, respectively, for %HAA.
conclusionThe SubPL extraction method may be helpful for distinguishing patients with ILD from those without ILD.
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