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Predictive Modelling of Lung Function using Emphysematous Density Distribution
Target lung tissue selection remains a challenging task to perform for treating severe emphysema with lung volume reduction (LVR). In order to target the treatment candidate, the percentage of low attenuation volume (LAV%) representing the proportion of emphysema volume to whole lung volume is measu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930211/ https://www.ncbi.nlm.nih.gov/pubmed/31875053 http://dx.doi.org/10.1038/s41598-019-56351-9 |
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author | Lor, Kuo-Lung Liu, Cheng-Pei Chang, Yeun-Chung Yu, Chong-Jen Wang, Cheng-Yi Chung, Ming-Jui Lin, Fan-Ya Chen, Chung-Ming |
author_facet | Lor, Kuo-Lung Liu, Cheng-Pei Chang, Yeun-Chung Yu, Chong-Jen Wang, Cheng-Yi Chung, Ming-Jui Lin, Fan-Ya Chen, Chung-Ming |
author_sort | Lor, Kuo-Lung |
collection | PubMed |
description | Target lung tissue selection remains a challenging task to perform for treating severe emphysema with lung volume reduction (LVR). In order to target the treatment candidate, the percentage of low attenuation volume (LAV%) representing the proportion of emphysema volume to whole lung volume is measured using computed tomography (CT) images. Although LAV% have shown to have a correlation with lung function in patients with chronic obstructive pulmonary disease (COPD), similar measurements of LAV% in whole lung or lobes may have large variations in lung function due to emphysema heterogeneity. The functional information of regional emphysema destruction is required for supporting the choice of optimal target. The purpose of this study is to develop an emphysema heterogeneity descriptor for the three-dimensional emphysematous bullae according to the size variations of emphysematous density (ED) and their spatial distribution. The second purpose is to derive a predictive model of airflow limitation based on the regional emphysema heterogeneity. Deriving the bullous representation and grouping them into four scales in the upper and lower lobes, a predictive model is computed using the linear model fitting to estimate the severity of lung function. A total of 99 subjects, 87 patients with mild to very severe COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I~IV) and 12 control participants with normal lung functions (forced expiratory volume in one second (FEV(1))/forced vital capacity (FVC) > 0.7) were evaluated. The final model was trained with stratified cross-validation on randomly selected 75% of the dataset (n = 76) and tested on the remaining dataset (n = 23). The dispersed cases of LAV% inconsistent with their lung function outcome were evaluated, and the correlation study suggests that comparing to LAV of larger bullae, the widely spread smaller bullae with equivalent LAV has a larger impact on lung function. The testing dataset has the correlation of r = −0.76 (p < 0.01) between the whole lung LAV% and FEV(1)/FVC, whereas using two ED % of scales and location-dependent variables to predict the emphysema-associated FEV(1)/FVC, the results shows their correlation of 0.82 (p < 0.001) with clinical FEV(1)/FVC. |
format | Online Article Text |
id | pubmed-6930211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69302112019-12-27 Predictive Modelling of Lung Function using Emphysematous Density Distribution Lor, Kuo-Lung Liu, Cheng-Pei Chang, Yeun-Chung Yu, Chong-Jen Wang, Cheng-Yi Chung, Ming-Jui Lin, Fan-Ya Chen, Chung-Ming Sci Rep Article Target lung tissue selection remains a challenging task to perform for treating severe emphysema with lung volume reduction (LVR). In order to target the treatment candidate, the percentage of low attenuation volume (LAV%) representing the proportion of emphysema volume to whole lung volume is measured using computed tomography (CT) images. Although LAV% have shown to have a correlation with lung function in patients with chronic obstructive pulmonary disease (COPD), similar measurements of LAV% in whole lung or lobes may have large variations in lung function due to emphysema heterogeneity. The functional information of regional emphysema destruction is required for supporting the choice of optimal target. The purpose of this study is to develop an emphysema heterogeneity descriptor for the three-dimensional emphysematous bullae according to the size variations of emphysematous density (ED) and their spatial distribution. The second purpose is to derive a predictive model of airflow limitation based on the regional emphysema heterogeneity. Deriving the bullous representation and grouping them into four scales in the upper and lower lobes, a predictive model is computed using the linear model fitting to estimate the severity of lung function. A total of 99 subjects, 87 patients with mild to very severe COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I~IV) and 12 control participants with normal lung functions (forced expiratory volume in one second (FEV(1))/forced vital capacity (FVC) > 0.7) were evaluated. The final model was trained with stratified cross-validation on randomly selected 75% of the dataset (n = 76) and tested on the remaining dataset (n = 23). The dispersed cases of LAV% inconsistent with their lung function outcome were evaluated, and the correlation study suggests that comparing to LAV of larger bullae, the widely spread smaller bullae with equivalent LAV has a larger impact on lung function. The testing dataset has the correlation of r = −0.76 (p < 0.01) between the whole lung LAV% and FEV(1)/FVC, whereas using two ED % of scales and location-dependent variables to predict the emphysema-associated FEV(1)/FVC, the results shows their correlation of 0.82 (p < 0.001) with clinical FEV(1)/FVC. Nature Publishing Group UK 2019-12-24 /pmc/articles/PMC6930211/ /pubmed/31875053 http://dx.doi.org/10.1038/s41598-019-56351-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lor, Kuo-Lung Liu, Cheng-Pei Chang, Yeun-Chung Yu, Chong-Jen Wang, Cheng-Yi Chung, Ming-Jui Lin, Fan-Ya Chen, Chung-Ming Predictive Modelling of Lung Function using Emphysematous Density Distribution |
title | Predictive Modelling of Lung Function using Emphysematous Density Distribution |
title_full | Predictive Modelling of Lung Function using Emphysematous Density Distribution |
title_fullStr | Predictive Modelling of Lung Function using Emphysematous Density Distribution |
title_full_unstemmed | Predictive Modelling of Lung Function using Emphysematous Density Distribution |
title_short | Predictive Modelling of Lung Function using Emphysematous Density Distribution |
title_sort | predictive modelling of lung function using emphysematous density distribution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930211/ https://www.ncbi.nlm.nih.gov/pubmed/31875053 http://dx.doi.org/10.1038/s41598-019-56351-9 |
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