Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?

<h4>Background and purpose</h4>To correlate changes of various CT parameters after the neoadjuvant treatment in patients with lung adenocarcinoma with pathologic responses, focused on their relationship with different therapeutic options, particularly of EGFR-TKI and concurrent chemoradi...

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Main Authors: Yousun Chong, Jae-Hun Kim, Ho Yun Lee, Yong Chan Ahn, Kyung Soo Lee, Myung-Ju Ahn, Jhingook Kim, Young Mog Shim, Joungho Han, Yoon-La Choi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0088598&type=printable
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author Yousun Chong
Jae-Hun Kim
Ho Yun Lee
Yong Chan Ahn
Kyung Soo Lee
Myung-Ju Ahn
Jhingook Kim
Young Mog Shim
Joungho Han
Yoon-La Choi
author_facet Yousun Chong
Jae-Hun Kim
Ho Yun Lee
Yong Chan Ahn
Kyung Soo Lee
Myung-Ju Ahn
Jhingook Kim
Young Mog Shim
Joungho Han
Yoon-La Choi
author_sort Yousun Chong
collection DOAJ
description <h4>Background and purpose</h4>To correlate changes of various CT parameters after the neoadjuvant treatment in patients with lung adenocarcinoma with pathologic responses, focused on their relationship with different therapeutic options, particularly of EGFR-TKI and concurrent chemoradiation therapy (CCRT) settings.<h4>Materials and methods</h4>We reviewed pre-operative CT images of primary tumors and surgical specimens obtained after neoadjuvant therapy (TKI, n = 23; CCRT, n = 28) from 51 patients with lung adenocarcinoma. Serial changes in tumor volume, density, mass, skewness/kurtosis, and size-zone variability/intensity variability) were assessed from CT datasets. The changes in CT parameters were correlated with histopathologic responses, and the relationship between CT variables and histopathologic responses was compared between TKI and CCRT groups.<h4>Results</h4>Tumor volume, mass, kurtosis, and skewness were significant predictors of pathologic response in CCRT group in univariate analysis. Using multivariate analysis, kurtosis was found to be independent predictor. In TKI group, intensity variability and size-zone variability were significantly decreased in pathologic responder group. Intensity variability was found to be an independent predictor for pathologic response on multivariate analysis.<h4>Conclusions</h4>Quantitative CT variables including histogram or texture analysis have potential as a predictive tool for response evaluation, and it may better reflect treatment response than standard response criteria based on size changes.
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spelling doaj-art-4d4e4ff41fbc49c38c54584031b183702025-08-20T02:15:24ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0192e8859810.1371/journal.pone.0088598Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?Yousun ChongJae-Hun KimHo Yun LeeYong Chan AhnKyung Soo LeeMyung-Ju AhnJhingook KimYoung Mog ShimJoungho HanYoon-La Choi<h4>Background and purpose</h4>To correlate changes of various CT parameters after the neoadjuvant treatment in patients with lung adenocarcinoma with pathologic responses, focused on their relationship with different therapeutic options, particularly of EGFR-TKI and concurrent chemoradiation therapy (CCRT) settings.<h4>Materials and methods</h4>We reviewed pre-operative CT images of primary tumors and surgical specimens obtained after neoadjuvant therapy (TKI, n = 23; CCRT, n = 28) from 51 patients with lung adenocarcinoma. Serial changes in tumor volume, density, mass, skewness/kurtosis, and size-zone variability/intensity variability) were assessed from CT datasets. The changes in CT parameters were correlated with histopathologic responses, and the relationship between CT variables and histopathologic responses was compared between TKI and CCRT groups.<h4>Results</h4>Tumor volume, mass, kurtosis, and skewness were significant predictors of pathologic response in CCRT group in univariate analysis. Using multivariate analysis, kurtosis was found to be independent predictor. In TKI group, intensity variability and size-zone variability were significantly decreased in pathologic responder group. Intensity variability was found to be an independent predictor for pathologic response on multivariate analysis.<h4>Conclusions</h4>Quantitative CT variables including histogram or texture analysis have potential as a predictive tool for response evaluation, and it may better reflect treatment response than standard response criteria based on size changes.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0088598&type=printable
spellingShingle Yousun Chong
Jae-Hun Kim
Ho Yun Lee
Yong Chan Ahn
Kyung Soo Lee
Myung-Ju Ahn
Jhingook Kim
Young Mog Shim
Joungho Han
Yoon-La Choi
Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?
PLoS ONE
title Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?
title_full Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?
title_fullStr Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?
title_full_unstemmed Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?
title_short Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?
title_sort quantitative ct variables enabling response prediction in neoadjuvant therapy with egfr tkis are they different from those in neoadjuvant concurrent chemoradiotherapy
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0088598&type=printable
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