Extraction of the subpleural lung region from computed tomography images to detect interstitial lung disease
Abstract
PURPOSE: To 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 METHODS: The 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.
RESULTS: The 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.
CONCLUSION: The SubPL extraction method may be helpful for distinguishing patients with ILD from those without ILD.
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 40 participants or records.
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