CT densitometry as a predictor of pulmonary function in lung cancer patients.

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dc.contributor.author Moloney, Fiachra
dc.contributor.author McWilliams, Sebastian R.
dc.contributor.author McLaughlin, Patrick D.
dc.contributor.author Kennedy, Marcus P.
dc.contributor.author Henry, Michael T.
dc.contributor.author O'Connor, Owen J.
dc.contributor.author Maher, Michael M.
dc.date.accessioned 2018-08-14T12:01:16Z
dc.date.available 2018-08-14T12:01:16Z
dc.date.issued 2012-12
dc.identifier.citation Moloney F., McWilliams S., Crush L., McLaughlin P. D., Kennedy M. P., Henry M., O' Connor O. and Maher, M. M. (2012) 'CT Densitometry as a Predictor of Pulmonary Function in Lung Cancer Patients', The Open Respiratory Medicine Journal, 6, pp. 139-144. doi: 10.2174/1874306401206010139 en
dc.identifier.volume 6 en
dc.identifier.startpage 139 en
dc.identifier.endpage 144 en
dc.identifier.issn 1874-3064
dc.identifier.uri http://hdl.handle.net/10468/6606
dc.identifier.doi 10.2174/1874306401206010139
dc.description.abstract 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 FEV1 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. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Bentham Open en
dc.rights © Moloney et al.; Licensee Bentham Open. 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. en
dc.rights.uri http://creativecommons.org/licenses/by-nc/3.0/ en
dc.subject Computed tomography en
dc.subject Lung density en
dc.subject Pulmonary function en
dc.title CT densitometry as a predictor of pulmonary function in lung cancer patients. en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Owen O'Connor, Medicine , University College Cork, Cork, Ireland. +353-21-490-3000 Email: oj.oconnor@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2018-06-20T16:44:54Z
dc.description.version Published Version en
dc.internal.rssid 337699934
dc.internal.pmid 23264834
dc.description.status Peer reviewed en
dc.identifier.journaltitle The Open Respiratory Medicine Journal en
dc.internal.copyrightchecked No !!CORA!! en
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress oj.oconnor@ucc.ie en


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© Moloney et al.; Licensee Bentham Open. 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. Except where otherwise noted, this item's license is described as © Moloney et al.; Licensee Bentham Open. 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.
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