Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Lor, Kuo-Lung, Liu, Cheng-Pei, Chang, Yeun-Chung, Yu, Chong-Jen, Wang, Cheng-Yi, Chung, Ming-Jui, Lin, Fan-Ya, Chen, Chung-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
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
_version_ 1783482846976933888
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
work_keys_str_mv AT lorkuolung predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT liuchengpei predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT changyeunchung predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT yuchongjen predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT wangchengyi predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT chungmingjui predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT linfanya predictivemodellingoflungfunctionusingemphysematousdensitydistribution
AT chenchungming predictivemodellingoflungfunctionusingemphysematousdensitydistribution