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Quantitative CT Variables Enabling Response Prediction in Neoadjuvant Therapy with EGFR-TKIs: Are They Different from Those in Neoadjuvant Concurrent Chemoradiotherapy?

BACKGROUND AND PURPOSE: 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...

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Autores principales: Chong, Yousun, Kim, Jae-Hun, Lee, Ho Yun, Ahn, Yong Chan, Lee, Kyung Soo, Ahn, Myung-Ju, Kim, Jhingook, Shim, Young Mog, Han, Joungho, Choi, Yoon-La
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3935840/
https://www.ncbi.nlm.nih.gov/pubmed/24586348
http://dx.doi.org/10.1371/journal.pone.0088598
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author Chong, Yousun
Kim, Jae-Hun
Lee, Ho Yun
Ahn, Yong Chan
Lee, Kyung Soo
Ahn, Myung-Ju
Kim, Jhingook
Shim, Young Mog
Han, Joungho
Choi, Yoon-La
author_facet Chong, Yousun
Kim, Jae-Hun
Lee, Ho Yun
Ahn, Yong Chan
Lee, Kyung Soo
Ahn, Myung-Ju
Kim, Jhingook
Shim, Young Mog
Han, Joungho
Choi, Yoon-La
author_sort Chong, Yousun
collection PubMed
description BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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 pubmed-39358402014-03-04 Quantitative CT Variables Enabling Response Prediction in Neoadjuvant Therapy with EGFR-TKIs: Are They Different from Those in Neoadjuvant Concurrent Chemoradiotherapy? Chong, Yousun Kim, Jae-Hun Lee, Ho Yun Ahn, Yong Chan Lee, Kyung Soo Ahn, Myung-Ju Kim, Jhingook Shim, Young Mog Han, Joungho Choi, Yoon-La PLoS One Research Article BACKGROUND AND PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. Public Library of Science 2014-02-26 /pmc/articles/PMC3935840/ /pubmed/24586348 http://dx.doi.org/10.1371/journal.pone.0088598 Text en © 2014 Chong et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chong, Yousun
Kim, Jae-Hun
Lee, Ho Yun
Ahn, Yong Chan
Lee, Kyung Soo
Ahn, Myung-Ju
Kim, Jhingook
Shim, Young Mog
Han, Joungho
Choi, Yoon-La
Quantitative CT Variables Enabling Response Prediction in Neoadjuvant Therapy with EGFR-TKIs: Are They Different from Those in Neoadjuvant Concurrent Chemoradiotherapy?
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?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3935840/
https://www.ncbi.nlm.nih.gov/pubmed/24586348
http://dx.doi.org/10.1371/journal.pone.0088598
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