Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.

The purpose of this study was to assess whether homology-based emphysema quantification (HEQ) is significantly associated with lung cancer risk. This retrospective study was approved by our institutional review board. We included 576 patients with lung nodules (317 men and 259 women; age, 66.8 ± 12....

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Main Authors: Mizuho Nishio, Takeshi Kubo, Kaori Togashi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0210720
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spelling doaj-fe9a711c02bc402f9baa2d02f71deb962021-03-03T20:57:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01141e021072010.1371/journal.pone.0210720Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.Mizuho NishioTakeshi KuboKaori TogashiThe purpose of this study was to assess whether homology-based emphysema quantification (HEQ) is significantly associated with lung cancer risk. This retrospective study was approved by our institutional review board. We included 576 patients with lung nodules (317 men and 259 women; age, 66.8 ± 12.3 years), who were selected from a database previously generated for computer-aided diagnosis. Of these, 283 were diagnosed with lung cancer, whereas the remaining 293 showed benign lung nodules. HEQ was performed and percentage of low-attenuation lung area (LAA%) was calculated on the basis of computed tomography scans. Statistical models were constructed to estimate lung cancer risk using logistic regression; sex, age, smoking history (Brinkman index), LAA%, and HEQ were considered independent variables. The following three models were evaluated: the base model (sex, age, and smoking history); the LAA% model (the base model + LAA%); and the HEQ model (the base model + HEQ). Model performance was assessed using receiver operating characteristic analysis and the associated area under the curve (AUC). Differences in AUCs among the models were evaluated using Delong's test. AUCs of the base, LAA%, and HEQ models were 0.585, 0.593, and 0.622, respectively. HEQ coefficient was statistically significant in the HEQ model (P = 0.00487), but LAA% coefficient was not significant in the LAA% model (P = 0.199). Delong's test revealed significant difference in AUCs between the LAA% and HEQ models (P = 0.0455). In conclusion, after adjusting for age, sex, and smoking history (Brinkman index), HEQ was significantly associated with lung cancer risk.https://doi.org/10.1371/journal.pone.0210720
collection DOAJ
language English
format Article
sources DOAJ
author Mizuho Nishio
Takeshi Kubo
Kaori Togashi
spellingShingle Mizuho Nishio
Takeshi Kubo
Kaori Togashi
Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
PLoS ONE
author_facet Mizuho Nishio
Takeshi Kubo
Kaori Togashi
author_sort Mizuho Nishio
title Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
title_short Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
title_full Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
title_fullStr Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
title_full_unstemmed Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
title_sort estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description The purpose of this study was to assess whether homology-based emphysema quantification (HEQ) is significantly associated with lung cancer risk. This retrospective study was approved by our institutional review board. We included 576 patients with lung nodules (317 men and 259 women; age, 66.8 ± 12.3 years), who were selected from a database previously generated for computer-aided diagnosis. Of these, 283 were diagnosed with lung cancer, whereas the remaining 293 showed benign lung nodules. HEQ was performed and percentage of low-attenuation lung area (LAA%) was calculated on the basis of computed tomography scans. Statistical models were constructed to estimate lung cancer risk using logistic regression; sex, age, smoking history (Brinkman index), LAA%, and HEQ were considered independent variables. The following three models were evaluated: the base model (sex, age, and smoking history); the LAA% model (the base model + LAA%); and the HEQ model (the base model + HEQ). Model performance was assessed using receiver operating characteristic analysis and the associated area under the curve (AUC). Differences in AUCs among the models were evaluated using Delong's test. AUCs of the base, LAA%, and HEQ models were 0.585, 0.593, and 0.622, respectively. HEQ coefficient was statistically significant in the HEQ model (P = 0.00487), but LAA% coefficient was not significant in the LAA% model (P = 0.199). Delong's test revealed significant difference in AUCs between the LAA% and HEQ models (P = 0.0455). In conclusion, after adjusting for age, sex, and smoking history (Brinkman index), HEQ was significantly associated with lung cancer risk.
url https://doi.org/10.1371/journal.pone.0210720
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AT takeshikubo estimationoflungcancerriskusinghomologybasedemphysemaquantificationinpatientswithlungnodules
AT kaoritogashi estimationoflungcancerriskusinghomologybasedemphysemaquantificationinpatientswithlungnodules
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