ArticleJapanese journal of radiology2016
Multicenter study of quantitative computed tomography analysis using a computer-aided three-dimensional system in patients with idiopathic pulmonary fibrosis.
Article in Japanese journal of radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 24 citations in OpenAlex.
- 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
- Quantitative analysis of high-resolution computed tomography features of idiopathic pulmonary fibrosis: a structure-function correlation study.Quantitative imaging in medicine and surgery · 2022Article
- Standardised 3D-CT lung volumes for patients with idiopathic pulmonary fibrosis.Respiratory research · 2022Article
- Review
- Smoking-related lung abnormalities on computed tomography images: comparison with pathological findings.Japanese journal of radiology · 2018Review
- Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.The British journal of radiology · 2018Review
- Extraction of the subpleural lung region from computed tomography images to detect interstitial lung disease.Japanese journal of radiology · 2017Article
- Serum KL-6 and surfactant protein-D as monitoring and predictive markers of interstitial lung disease in patients with systemic sclerosis and mixed connective tissue disease.Journal of thoracic disease · 2017Article
- Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. MATERIALS AND
methodsEach institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC).
resultsFor each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners.
conclusionGaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.
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