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Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System

OBJECTIVE: To evaluate the usefulness of an automated system for quantification and discrimination of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). MATERIALS AND METHODS: An automated system to quantify six regional high-resolution CT (HRCT) patterns: normal, NL;...

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Autores principales: Park, Sang Ok, Seo, Joon Beom, Kim, Namkug, Lee, Young Kyung, Lee, Jeongjin, Kim, Dong Soon
Formato: Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088847/
https://www.ncbi.nlm.nih.gov/pubmed/21603289
http://dx.doi.org/10.3348/kjr.2011.12.3.297
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author Park, Sang Ok
Seo, Joon Beom
Kim, Namkug
Lee, Young Kyung
Lee, Jeongjin
Kim, Dong Soon
author_facet Park, Sang Ok
Seo, Joon Beom
Kim, Namkug
Lee, Young Kyung
Lee, Jeongjin
Kim, Dong Soon
author_sort Park, Sang Ok
collection PubMed
description OBJECTIVE: To evaluate the usefulness of an automated system for quantification and discrimination of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). MATERIALS AND METHODS: An automated system to quantify six regional high-resolution CT (HRCT) patterns: normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EMPH; and consolidation, CONS, was developed using texture and shape features. Fifty-four patients with pathologically proven UIP (n = 26) and pathologically proven NSIP (n = 28) were included as part of this study. Inter-observer agreement in measuring the extent of each HRCT pattern between the system and two thoracic radiologists were assessed in 26 randomly selected subsets using an interclass correlation coefficient (ICC). A linear regression analysis was used to assess the contribution of each disease pattern to the pulmonary function test parameters. The discriminating capacity of the system between UIP and NSIP was evaluated using a binomial logistic regression. RESULTS: The overall ICC showed acceptable agreement among the system and the two radiologists (r = 0.895 for the abnormal lung volume fraction, 0.706 for the fibrosis fraction, 0.895 for NL, 0.625 for GGO, 0.626 for RO, 0.893 for HC, 0.800 for EMPH, and 0.430 for CONS). The volumes of NL, GGO, RO, and EMPH contribute to forced expiratory volume during one second (FEV(1)) (r = 0.72, β values, 0.84, 0.34, 0.34 and 0.24, respectively) and forced vital capacity (FVC) (r = 0.76, β values, 0.82, 0.28, 0.21 and 0.34, respectively). For diffusing capacity (DL(co)), the volumes of NL and HC were independent contributors in opposite directions (r = 0.65, β values, 0.64, -0.21, respectively). The automated system can help discriminate between UIP and NSIP with an accuracy of 82%. CONCLUSION: The automated quantification system of regional HRCT patterns can be useful in the assessment of disease severity and may provide reliable agreement with the radiologists' results. In addition, this system may be useful in differentiating between UIP and NSIP.
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spelling pubmed-30888472011-05-19 Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System Park, Sang Ok Seo, Joon Beom Kim, Namkug Lee, Young Kyung Lee, Jeongjin Kim, Dong Soon Korean J Radiol Original Article OBJECTIVE: To evaluate the usefulness of an automated system for quantification and discrimination of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). MATERIALS AND METHODS: An automated system to quantify six regional high-resolution CT (HRCT) patterns: normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EMPH; and consolidation, CONS, was developed using texture and shape features. Fifty-four patients with pathologically proven UIP (n = 26) and pathologically proven NSIP (n = 28) were included as part of this study. Inter-observer agreement in measuring the extent of each HRCT pattern between the system and two thoracic radiologists were assessed in 26 randomly selected subsets using an interclass correlation coefficient (ICC). A linear regression analysis was used to assess the contribution of each disease pattern to the pulmonary function test parameters. The discriminating capacity of the system between UIP and NSIP was evaluated using a binomial logistic regression. RESULTS: The overall ICC showed acceptable agreement among the system and the two radiologists (r = 0.895 for the abnormal lung volume fraction, 0.706 for the fibrosis fraction, 0.895 for NL, 0.625 for GGO, 0.626 for RO, 0.893 for HC, 0.800 for EMPH, and 0.430 for CONS). The volumes of NL, GGO, RO, and EMPH contribute to forced expiratory volume during one second (FEV(1)) (r = 0.72, β values, 0.84, 0.34, 0.34 and 0.24, respectively) and forced vital capacity (FVC) (r = 0.76, β values, 0.82, 0.28, 0.21 and 0.34, respectively). For diffusing capacity (DL(co)), the volumes of NL and HC were independent contributors in opposite directions (r = 0.65, β values, 0.64, -0.21, respectively). The automated system can help discriminate between UIP and NSIP with an accuracy of 82%. CONCLUSION: The automated quantification system of regional HRCT patterns can be useful in the assessment of disease severity and may provide reliable agreement with the radiologists' results. In addition, this system may be useful in differentiating between UIP and NSIP. The Korean Society of Radiology 2011 2011-04-25 /pmc/articles/PMC3088847/ /pubmed/21603289 http://dx.doi.org/10.3348/kjr.2011.12.3.297 Text en Copyright © 2011 The Korean Society of Radiology http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Park, Sang Ok
Seo, Joon Beom
Kim, Namkug
Lee, Young Kyung
Lee, Jeongjin
Kim, Dong Soon
Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
title Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
title_full Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
title_fullStr Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
title_full_unstemmed Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
title_short Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
title_sort comparison of usual interstitial pneumonia and nonspecific interstitial pneumonia: quantification of disease severity and discrimination between two diseases on hrct using a texture-based automated system
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3088847/
https://www.ncbi.nlm.nih.gov/pubmed/21603289
http://dx.doi.org/10.3348/kjr.2011.12.3.297
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