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CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients

PURPOSE: Preoperative pulmonary assessment is undertaken in patients with resectable lung cancer to identify those at increased risk of perioperative complications. Guidelines from the American College of Chest Physicians indicate that if the FEV(1) and DLCO are ≥60% of predicted, patients are suita...

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Autores principales: Moloney, Fiachra, McWilliams, Sebastian, Crush, Lee, Laughlin, Patrick D Mc, Kenneddy, Marcus, Henry, Michael, O’ Connor, OJ, Maher, Michael M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Open 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3527876/
https://www.ncbi.nlm.nih.gov/pubmed/23264834
http://dx.doi.org/10.2174/1874306401206010139
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author Moloney, Fiachra
McWilliams, Sebastian
Crush, Lee
Laughlin, Patrick D Mc
Kenneddy, Marcus
Henry, Michael
O’ Connor, OJ
Maher, Michael M
author_facet Moloney, Fiachra
McWilliams, Sebastian
Crush, Lee
Laughlin, Patrick D Mc
Kenneddy, Marcus
Henry, Michael
O’ Connor, OJ
Maher, Michael M
author_sort Moloney, Fiachra
collection PubMed
description PURPOSE: Preoperative pulmonary assessment is undertaken in patients with resectable lung cancer to identify those at increased risk of perioperative complications. Guidelines from the American College of Chest Physicians indicate that if the FEV(1) and DLCO are ≥60% of predicted, patients are suitable for resection without further evaluation. The aim of our study is to determine if quantitative measures of lung volume and density obtained from pre-operative CT scans correlate with pulmonary function tests. This may allow us to predict pulmonary function in patients with lung cancer and identify patients who would tolerate surgical resection. MATERIALS AND METHODS: Patients were identified retrospectively from the lung cancer database of a tertiary hospital. Image segmentation software was utilized to estimate total lung volume, normal lung volume (values -500 HU to -910 HU), emphysematous volume (values less than -910 HU), and mean lung density from pre-operative CT studies for each patient and these values were compared to contemporaneous pulmonary function tests. RESULTS: A total of 77 patients were enrolled. FEV1 was found to correlate significantly with the mean lung density (r=.762, p<.001) and the volume of emphysema (r= -.678, p<.001). DLCO correlated significantly with the mean lung density (r =.648, p<.001) and the volume of emphysematous lung (r= -.535, p<.001). CONCLUSION: The results of this study suggest that both FEV1 and DLCO correlate significantly with volume of emphysema and mean lung density. We now plan to prospectively compare these CT parameters with measures of good and poor outcome postoperatively to identify CT measures that may predict surgical outcome preoperatively
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spelling pubmed-35278762012-12-21 CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients Moloney, Fiachra McWilliams, Sebastian Crush, Lee Laughlin, Patrick D Mc Kenneddy, Marcus Henry, Michael O’ Connor, OJ Maher, Michael M Open Respir Med J Article PURPOSE: Preoperative pulmonary assessment is undertaken in patients with resectable lung cancer to identify those at increased risk of perioperative complications. Guidelines from the American College of Chest Physicians indicate that if the FEV(1) and DLCO are ≥60% of predicted, patients are suitable for resection without further evaluation. The aim of our study is to determine if quantitative measures of lung volume and density obtained from pre-operative CT scans correlate with pulmonary function tests. This may allow us to predict pulmonary function in patients with lung cancer and identify patients who would tolerate surgical resection. MATERIALS AND METHODS: Patients were identified retrospectively from the lung cancer database of a tertiary hospital. Image segmentation software was utilized to estimate total lung volume, normal lung volume (values -500 HU to -910 HU), emphysematous volume (values less than -910 HU), and mean lung density from pre-operative CT studies for each patient and these values were compared to contemporaneous pulmonary function tests. RESULTS: A total of 77 patients were enrolled. FEV1 was found to correlate significantly with the mean lung density (r=.762, p<.001) and the volume of emphysema (r= -.678, p<.001). DLCO correlated significantly with the mean lung density (r =.648, p<.001) and the volume of emphysematous lung (r= -.535, p<.001). CONCLUSION: The results of this study suggest that both FEV1 and DLCO correlate significantly with volume of emphysema and mean lung density. We now plan to prospectively compare these CT parameters with measures of good and poor outcome postoperatively to identify CT measures that may predict surgical outcome preoperatively Bentham Open 2012-12-11 /pmc/articles/PMC3527876/ /pubmed/23264834 http://dx.doi.org/10.2174/1874306401206010139 Text en © Moloney et al.; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed 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 work is properly cited.
spellingShingle Article
Moloney, Fiachra
McWilliams, Sebastian
Crush, Lee
Laughlin, Patrick D Mc
Kenneddy, Marcus
Henry, Michael
O’ Connor, OJ
Maher, Michael M
CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients
title CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients
title_full CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients
title_fullStr CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients
title_full_unstemmed CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients
title_short CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients
title_sort ct densitometry as a predictor of pulmonary function in lung cancer patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3527876/
https://www.ncbi.nlm.nih.gov/pubmed/23264834
http://dx.doi.org/10.2174/1874306401206010139
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