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Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes
OBJECTIVES: To investigate relationships between histogram-based high-resolution CT (HRCT) indexes and pulmonary function tests (PFTs) in interstitial lung diseases. METHODS: Forty-nine patients having baseline and 1-year HRCT examinations and PFTs were investigated. Histogram-based HRCT indexes wer...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The British Institute of Radiology.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10607396/ https://www.ncbi.nlm.nih.gov/pubmed/37660683 http://dx.doi.org/10.1259/bjr.20221160 |
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author | Palmucci, Stefano Tiralongo, Francesco Galioto, Federica Toscano, Stefano Reali, Linda Scavone, Carlotta Fazio, Giulia Ferlito, Agata Sambataro, Gianluca Vancheri, Ada Sciacca, Enrico Vignigni, Giovanna Spadaro, Carla Mauro, Letizia Antonella Foti, Pietro Valerio Vancheri, Carlo Basile, Antonio |
author_facet | Palmucci, Stefano Tiralongo, Francesco Galioto, Federica Toscano, Stefano Reali, Linda Scavone, Carlotta Fazio, Giulia Ferlito, Agata Sambataro, Gianluca Vancheri, Ada Sciacca, Enrico Vignigni, Giovanna Spadaro, Carla Mauro, Letizia Antonella Foti, Pietro Valerio Vancheri, Carlo Basile, Antonio |
author_sort | Palmucci, Stefano |
collection | PubMed |
description | OBJECTIVES: To investigate relationships between histogram-based high-resolution CT (HRCT) indexes and pulmonary function tests (PFTs) in interstitial lung diseases. METHODS: Forty-nine patients having baseline and 1-year HRCT examinations and PFTs were investigated. Histogram-based HRCT indexes were calculated; strength of associations with PFTs was investigated using Pearson correlation. Patients were divided into progressive and non-progressive groups. HRCT indexes were compared between the two groups using the U-test; within each group, baseline and follow-up Wilcoxon analysis was performed. Receiver operating characteristic analysis was used for predicting disease progression. RESULTS: At baseline, moderate correlations were observed considering kurtosis and diffusion capacity of the lungs for carbon monoxide (DLCO) (r = 0.54) and skewness and DLCO (r = 0.559), whereas weak but significant correlations were observed between forced vital capacity and kurtosis (r = 0.368, p = 0.009) and forced vital capacity and skewness (r = 0.391, p = 0.005). Negative correlations were reported between HAA% and PFTs (from r = −0.418 up to r = −0.507). At follow-up correlations between quantitative indexes and PFTs were also moderate, except for high attenuation area (HAA)% −700 and DLCO (r = −0.397). In progressive subgroup, moderate and strong correlations were found between DLCO and HRCT indexes (r = 0.595 kurtosis, r = 0.672 skewness, r=-0. 598 HAA% −600 and r = −0.626 HAA% −700). At follow-up, we observed significant differences between the two groups for kurtosis (p = 0.029), HAA% −600 (p = 0.04) and HAA% −700 (p = 0.02). To predict progression, ROC analysis reported sensitivity of 90.9% and specificity of 51.9% using a threshold value of δ kurtosis <0.03. CONCLUSION: At one year, moderate correlations suggest that progression could be assessed through HRCT quantification. ADVANCES IN KNOWLEDGE: This study promotes histogram-based HRCT indexes in the assessment of progressive pulmonary fibrosis. |
format | Online Article Text |
id | pubmed-10607396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The British Institute of Radiology. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106073962023-10-28 Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes Palmucci, Stefano Tiralongo, Francesco Galioto, Federica Toscano, Stefano Reali, Linda Scavone, Carlotta Fazio, Giulia Ferlito, Agata Sambataro, Gianluca Vancheri, Ada Sciacca, Enrico Vignigni, Giovanna Spadaro, Carla Mauro, Letizia Antonella Foti, Pietro Valerio Vancheri, Carlo Basile, Antonio Br J Radiol Full Paper OBJECTIVES: To investigate relationships between histogram-based high-resolution CT (HRCT) indexes and pulmonary function tests (PFTs) in interstitial lung diseases. METHODS: Forty-nine patients having baseline and 1-year HRCT examinations and PFTs were investigated. Histogram-based HRCT indexes were calculated; strength of associations with PFTs was investigated using Pearson correlation. Patients were divided into progressive and non-progressive groups. HRCT indexes were compared between the two groups using the U-test; within each group, baseline and follow-up Wilcoxon analysis was performed. Receiver operating characteristic analysis was used for predicting disease progression. RESULTS: At baseline, moderate correlations were observed considering kurtosis and diffusion capacity of the lungs for carbon monoxide (DLCO) (r = 0.54) and skewness and DLCO (r = 0.559), whereas weak but significant correlations were observed between forced vital capacity and kurtosis (r = 0.368, p = 0.009) and forced vital capacity and skewness (r = 0.391, p = 0.005). Negative correlations were reported between HAA% and PFTs (from r = −0.418 up to r = −0.507). At follow-up correlations between quantitative indexes and PFTs were also moderate, except for high attenuation area (HAA)% −700 and DLCO (r = −0.397). In progressive subgroup, moderate and strong correlations were found between DLCO and HRCT indexes (r = 0.595 kurtosis, r = 0.672 skewness, r=-0. 598 HAA% −600 and r = −0.626 HAA% −700). At follow-up, we observed significant differences between the two groups for kurtosis (p = 0.029), HAA% −600 (p = 0.04) and HAA% −700 (p = 0.02). To predict progression, ROC analysis reported sensitivity of 90.9% and specificity of 51.9% using a threshold value of δ kurtosis <0.03. CONCLUSION: At one year, moderate correlations suggest that progression could be assessed through HRCT quantification. ADVANCES IN KNOWLEDGE: This study promotes histogram-based HRCT indexes in the assessment of progressive pulmonary fibrosis. The British Institute of Radiology. 2023-11 2023-10-03 /pmc/articles/PMC10607396/ /pubmed/37660683 http://dx.doi.org/10.1259/bjr.20221160 Text en © 2023 The Authors. Published by the British Institute of Radiology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial reuse, provided the original author and source are credited. |
spellingShingle | Full Paper Palmucci, Stefano Tiralongo, Francesco Galioto, Federica Toscano, Stefano Reali, Linda Scavone, Carlotta Fazio, Giulia Ferlito, Agata Sambataro, Gianluca Vancheri, Ada Sciacca, Enrico Vignigni, Giovanna Spadaro, Carla Mauro, Letizia Antonella Foti, Pietro Valerio Vancheri, Carlo Basile, Antonio Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes |
title | Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes |
title_full | Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes |
title_fullStr | Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes |
title_full_unstemmed | Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes |
title_short | Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes |
title_sort | histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and hrct indexes |
topic | Full Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10607396/ https://www.ncbi.nlm.nih.gov/pubmed/37660683 http://dx.doi.org/10.1259/bjr.20221160 |
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