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CT-Based Local Distribution Metric Improves Characterization of COPD
Parametric response mapping (PRM) of paired CT lung images has been shown to improve the phenotyping of COPD by allowing for the visualization and quantification of non-emphysematous air trapping component, referred to as functional small airways disease (fSAD). Although promising, large variability...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5462827/ https://www.ncbi.nlm.nih.gov/pubmed/28592874 http://dx.doi.org/10.1038/s41598-017-02871-1 |
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author | Hoff, Benjamin A. Pompe, Esther Galbán, Stefanie Postma, Dirkje S. Lammers, Jan-Willem J. ten Hacken, Nick H. T. Koenderman, Leo Johnson, Timothy D. Verleden, Stijn E. de Jong, Pim A. Mohamed Hoesein, Firdaus A. A. van den Berge, Maarten Ross, Brian D. Galbán, Craig J. |
author_facet | Hoff, Benjamin A. Pompe, Esther Galbán, Stefanie Postma, Dirkje S. Lammers, Jan-Willem J. ten Hacken, Nick H. T. Koenderman, Leo Johnson, Timothy D. Verleden, Stijn E. de Jong, Pim A. Mohamed Hoesein, Firdaus A. A. van den Berge, Maarten Ross, Brian D. Galbán, Craig J. |
author_sort | Hoff, Benjamin A. |
collection | PubMed |
description | Parametric response mapping (PRM) of paired CT lung images has been shown to improve the phenotyping of COPD by allowing for the visualization and quantification of non-emphysematous air trapping component, referred to as functional small airways disease (fSAD). Although promising, large variability in the standard method for analyzing PRM(fSAD) has been observed. We postulate that representing the 3D PRM(fSAD) data as a single scalar quantity (relative volume of PRM(fSAD)) oversimplifies the original 3D data, limiting its potential to detect the subtle progression of COPD as well as varying subtypes. In this study, we propose a new approach to analyze PRM. Based on topological techniques, we generate 3D maps of local topological features from 3D PRM(fSAD) classification maps. We found that the surface area of fSAD (S(fSAD)) was the most robust and significant independent indicator of clinically meaningful measures of COPD. We also confirmed by micro-CT of human lung specimens that structural differences are associated with unique S(fSAD) patterns, and demonstrated longitudinal feature alterations occurred with worsening pulmonary function independent of an increase in disease extent. These findings suggest that our technique captures additional COPD characteristics, which may provide important opportunities for improved diagnosis of COPD patients. |
format | Online Article Text |
id | pubmed-5462827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54628272017-06-08 CT-Based Local Distribution Metric Improves Characterization of COPD Hoff, Benjamin A. Pompe, Esther Galbán, Stefanie Postma, Dirkje S. Lammers, Jan-Willem J. ten Hacken, Nick H. T. Koenderman, Leo Johnson, Timothy D. Verleden, Stijn E. de Jong, Pim A. Mohamed Hoesein, Firdaus A. A. van den Berge, Maarten Ross, Brian D. Galbán, Craig J. Sci Rep Article Parametric response mapping (PRM) of paired CT lung images has been shown to improve the phenotyping of COPD by allowing for the visualization and quantification of non-emphysematous air trapping component, referred to as functional small airways disease (fSAD). Although promising, large variability in the standard method for analyzing PRM(fSAD) has been observed. We postulate that representing the 3D PRM(fSAD) data as a single scalar quantity (relative volume of PRM(fSAD)) oversimplifies the original 3D data, limiting its potential to detect the subtle progression of COPD as well as varying subtypes. In this study, we propose a new approach to analyze PRM. Based on topological techniques, we generate 3D maps of local topological features from 3D PRM(fSAD) classification maps. We found that the surface area of fSAD (S(fSAD)) was the most robust and significant independent indicator of clinically meaningful measures of COPD. We also confirmed by micro-CT of human lung specimens that structural differences are associated with unique S(fSAD) patterns, and demonstrated longitudinal feature alterations occurred with worsening pulmonary function independent of an increase in disease extent. These findings suggest that our technique captures additional COPD characteristics, which may provide important opportunities for improved diagnosis of COPD patients. Nature Publishing Group UK 2017-06-07 /pmc/articles/PMC5462827/ /pubmed/28592874 http://dx.doi.org/10.1038/s41598-017-02871-1 Text en © The Author(s) 2017 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 Hoff, Benjamin A. Pompe, Esther Galbán, Stefanie Postma, Dirkje S. Lammers, Jan-Willem J. ten Hacken, Nick H. T. Koenderman, Leo Johnson, Timothy D. Verleden, Stijn E. de Jong, Pim A. Mohamed Hoesein, Firdaus A. A. van den Berge, Maarten Ross, Brian D. Galbán, Craig J. CT-Based Local Distribution Metric Improves Characterization of COPD |
title | CT-Based Local Distribution Metric Improves Characterization of COPD |
title_full | CT-Based Local Distribution Metric Improves Characterization of COPD |
title_fullStr | CT-Based Local Distribution Metric Improves Characterization of COPD |
title_full_unstemmed | CT-Based Local Distribution Metric Improves Characterization of COPD |
title_short | CT-Based Local Distribution Metric Improves Characterization of COPD |
title_sort | ct-based local distribution metric improves characterization of copd |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5462827/ https://www.ncbi.nlm.nih.gov/pubmed/28592874 http://dx.doi.org/10.1038/s41598-017-02871-1 |
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