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Computer quantification of airway collapse on forced expiration to predict the presence of emphysema
BACKGROUND: Spirometric parameters are the mainstay for diagnosis of COPD, but cannot distinguish airway obstruction from emphysema. We aimed to develop a computer model that quantifies airway collapse on forced expiratory flow–volume loops. We then explored and validated the relationship of airway...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3870969/ https://www.ncbi.nlm.nih.gov/pubmed/24251975 http://dx.doi.org/10.1186/1465-9921-14-131 |
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author | Topalovic, Marko Exadaktylos, Vasileios Peeters, Anneleen Coolen, Johan Dewever, Walter Hemeryck, Martijn Slagmolen, Pieter Janssens, Karl Berckmans, Daniel Decramer, Marc Janssens, Wim |
author_facet | Topalovic, Marko Exadaktylos, Vasileios Peeters, Anneleen Coolen, Johan Dewever, Walter Hemeryck, Martijn Slagmolen, Pieter Janssens, Karl Berckmans, Daniel Decramer, Marc Janssens, Wim |
author_sort | Topalovic, Marko |
collection | PubMed |
description | BACKGROUND: Spirometric parameters are the mainstay for diagnosis of COPD, but cannot distinguish airway obstruction from emphysema. We aimed to develop a computer model that quantifies airway collapse on forced expiratory flow–volume loops. We then explored and validated the relationship of airway collapse with computed tomography (CT) diagnosed emphysema in two large independent cohorts. METHODS: A computer model was developed in 513 Caucasian individuals with ≥15 pack-years who performed spirometry, diffusion capacity and CT scans to quantify emphysema presence. The model computed the two best fitting regression lines on the expiratory phase of the flow-volume loop and calculated the angle between them. The collapse was expressed as an Angle of collapse (AC) which was then correlated with the presence of emphysema. Findings were validated in an independent group of 340 individuals. RESULTS: AC in emphysema subjects (N = 251) was significantly lower (131° ± 14°) compared to AC in subjects without emphysema (N = 223), (152° ± 10°) (p < 0.0001). Multivariate regression analysis revealed AC as best indicator of visually scored emphysema (R(2) = 0.505, p < 0.0001) with little significant contribution of K(CO,) %predicted and FEV(1,) %predicted to the total model (total R(2) = 0.626, p < 0.0001). Similar associations were obtained when using CT-automated density scores for emphysema assessment. Receiver operating characteristic (ROC) curves pointed to 131° as the best cut-off for emphysema (95.5% positive predictive value, 97% specificity and 51% sensitivity). Validation in a second group confirmed the significant difference in mean AC between emphysema and non-emphysema subjects. When applying the 131° cut-off, a positive predictive value of 95.6%, a specificity of 96% and a sensitivity of 59% were demonstrated. CONCLUSIONS: Airway collapse on forced expiration quantified by a computer model correlates with emphysema. An AC below 131° can be considered as a specific cut-off for predicting the presence of emphysema in heavy smokers. |
format | Online Article Text |
id | pubmed-3870969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-38709692013-12-25 Computer quantification of airway collapse on forced expiration to predict the presence of emphysema Topalovic, Marko Exadaktylos, Vasileios Peeters, Anneleen Coolen, Johan Dewever, Walter Hemeryck, Martijn Slagmolen, Pieter Janssens, Karl Berckmans, Daniel Decramer, Marc Janssens, Wim Respir Res Research BACKGROUND: Spirometric parameters are the mainstay for diagnosis of COPD, but cannot distinguish airway obstruction from emphysema. We aimed to develop a computer model that quantifies airway collapse on forced expiratory flow–volume loops. We then explored and validated the relationship of airway collapse with computed tomography (CT) diagnosed emphysema in two large independent cohorts. METHODS: A computer model was developed in 513 Caucasian individuals with ≥15 pack-years who performed spirometry, diffusion capacity and CT scans to quantify emphysema presence. The model computed the two best fitting regression lines on the expiratory phase of the flow-volume loop and calculated the angle between them. The collapse was expressed as an Angle of collapse (AC) which was then correlated with the presence of emphysema. Findings were validated in an independent group of 340 individuals. RESULTS: AC in emphysema subjects (N = 251) was significantly lower (131° ± 14°) compared to AC in subjects without emphysema (N = 223), (152° ± 10°) (p < 0.0001). Multivariate regression analysis revealed AC as best indicator of visually scored emphysema (R(2) = 0.505, p < 0.0001) with little significant contribution of K(CO,) %predicted and FEV(1,) %predicted to the total model (total R(2) = 0.626, p < 0.0001). Similar associations were obtained when using CT-automated density scores for emphysema assessment. Receiver operating characteristic (ROC) curves pointed to 131° as the best cut-off for emphysema (95.5% positive predictive value, 97% specificity and 51% sensitivity). Validation in a second group confirmed the significant difference in mean AC between emphysema and non-emphysema subjects. When applying the 131° cut-off, a positive predictive value of 95.6%, a specificity of 96% and a sensitivity of 59% were demonstrated. CONCLUSIONS: Airway collapse on forced expiration quantified by a computer model correlates with emphysema. An AC below 131° can be considered as a specific cut-off for predicting the presence of emphysema in heavy smokers. BioMed Central 2013 2013-11-19 /pmc/articles/PMC3870969/ /pubmed/24251975 http://dx.doi.org/10.1186/1465-9921-14-131 Text en Copyright © 2013 Topalovic et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Topalovic, Marko Exadaktylos, Vasileios Peeters, Anneleen Coolen, Johan Dewever, Walter Hemeryck, Martijn Slagmolen, Pieter Janssens, Karl Berckmans, Daniel Decramer, Marc Janssens, Wim Computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
title | Computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
title_full | Computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
title_fullStr | Computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
title_full_unstemmed | Computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
title_short | Computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
title_sort | computer quantification of airway collapse on forced expiration to predict the presence of emphysema |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3870969/ https://www.ncbi.nlm.nih.gov/pubmed/24251975 http://dx.doi.org/10.1186/1465-9921-14-131 |
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