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Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma

Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two inde...

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Autores principales: Grove, Olya, Berglund, Anders E., Schabath, Matthew B., Aerts, Hugo J. W. L., Dekker, Andre, Wang, Hua, Velazquez, Emmanuel Rios, Lambin, Philippe, Gu, Yuhua, Balagurunathan, Yoganand, Eikman, Edward, Gatenby, Robert A., Eschrich, Steven, Gillies, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349806/
https://www.ncbi.nlm.nih.gov/pubmed/25739030
http://dx.doi.org/10.1371/journal.pone.0118261
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author Grove, Olya
Berglund, Anders E.
Schabath, Matthew B.
Aerts, Hugo J. W. L.
Dekker, Andre
Wang, Hua
Velazquez, Emmanuel Rios
Lambin, Philippe
Gu, Yuhua
Balagurunathan, Yoganand
Eikman, Edward
Gatenby, Robert A.
Eschrich, Steven
Gillies, Robert J.
author_facet Grove, Olya
Berglund, Anders E.
Schabath, Matthew B.
Aerts, Hugo J. W. L.
Dekker, Andre
Wang, Hua
Velazquez, Emmanuel Rios
Lambin, Philippe
Gu, Yuhua
Balagurunathan, Yoganand
Eikman, Edward
Gatenby, Robert A.
Eschrich, Steven
Gillies, Robert J.
author_sort Grove, Olya
collection PubMed
description Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were segmented semi-automatically. Segmented tumor regions were further subdivided into core and boundary sub-regions, to quantify intensity variations across the tumor. Reproducibility of the features was evaluated in an independent test-retest dataset of 32 patients. The proposed metrics showed high degree of reproducibility in a repeated experiment (concordance, CCC≥0.897; dynamic range, DR≥0.92). Association with overall survival was evaluated by Cox proportional hazard regression, Kaplan-Meier survival curves, and the log-rank test. Both features were associated with overall survival (convexity: p = 0.008; entropy ratio: p = 0.04) in Cohort 1 but not in Cohort 2 (convexity: p = 0.7; entropy ratio: p = 0.8). In both cohorts, these features were found to be descriptive and demonstrated the link between imaging characteristics and patient survival in lung adenocarcinoma.
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spelling pubmed-43498062015-03-17 Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma Grove, Olya Berglund, Anders E. Schabath, Matthew B. Aerts, Hugo J. W. L. Dekker, Andre Wang, Hua Velazquez, Emmanuel Rios Lambin, Philippe Gu, Yuhua Balagurunathan, Yoganand Eikman, Edward Gatenby, Robert A. Eschrich, Steven Gillies, Robert J. PLoS One Research Article Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were segmented semi-automatically. Segmented tumor regions were further subdivided into core and boundary sub-regions, to quantify intensity variations across the tumor. Reproducibility of the features was evaluated in an independent test-retest dataset of 32 patients. The proposed metrics showed high degree of reproducibility in a repeated experiment (concordance, CCC≥0.897; dynamic range, DR≥0.92). Association with overall survival was evaluated by Cox proportional hazard regression, Kaplan-Meier survival curves, and the log-rank test. Both features were associated with overall survival (convexity: p = 0.008; entropy ratio: p = 0.04) in Cohort 1 but not in Cohort 2 (convexity: p = 0.7; entropy ratio: p = 0.8). In both cohorts, these features were found to be descriptive and demonstrated the link between imaging characteristics and patient survival in lung adenocarcinoma. Public Library of Science 2015-03-04 /pmc/articles/PMC4349806/ /pubmed/25739030 http://dx.doi.org/10.1371/journal.pone.0118261 Text en © 2015 Grove 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
Grove, Olya
Berglund, Anders E.
Schabath, Matthew B.
Aerts, Hugo J. W. L.
Dekker, Andre
Wang, Hua
Velazquez, Emmanuel Rios
Lambin, Philippe
Gu, Yuhua
Balagurunathan, Yoganand
Eikman, Edward
Gatenby, Robert A.
Eschrich, Steven
Gillies, Robert J.
Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
title Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
title_full Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
title_fullStr Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
title_full_unstemmed Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
title_short Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
title_sort quantitative computed tomographic descriptors associate tumor shape complexity and intratumor heterogeneity with prognosis in lung adenocarcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4349806/
https://www.ncbi.nlm.nih.gov/pubmed/25739030
http://dx.doi.org/10.1371/journal.pone.0118261
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