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Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features

PURPOSE: Explore the longitudinal CT-based radiomics to demonstrate the changing trend of radiotherapy response and to determine at which point after the onset of treatment radiomics exhibit the greatest change for stage III NSCLC patients. METHODS AND MATERIALS: Ten stage III NSCLC patients in line...

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Autores principales: Zhang, Ruiping, Cai, Zhengting, Luo, Yan’an, Wang, Zhizhen, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688890/
https://www.ncbi.nlm.nih.gov/pubmed/34977279
http://dx.doi.org/10.1016/j.ejro.2021.100391
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author Zhang, Ruiping
Cai, Zhengting
Luo, Yan’an
Wang, Zhizhen
Wang, Wei
author_facet Zhang, Ruiping
Cai, Zhengting
Luo, Yan’an
Wang, Zhizhen
Wang, Wei
author_sort Zhang, Ruiping
collection PubMed
description PURPOSE: Explore the longitudinal CT-based radiomics to demonstrate the changing trend of radiotherapy response and to determine at which point after the onset of treatment radiomics exhibit the greatest change for stage III NSCLC patients. METHODS AND MATERIALS: Ten stage III NSCLC patients in line with inclusion criteria were enrolled retrospectively, each of whom received radiotherapy or concurrent chemo-radiotherapy and performed eight series of follow-up CT imaging. Longitudinal radiomics were extracted on region of interest from the eight registered images, then two steps were conducted to select significant features as indicators of tumor change: 1) stable features were selected by Kendall rank correlation; 2) texture feature types with a steadily changing trend were retained and intensity features with stable change trends were selected to represent the large number of them. Next, the trend and rate of tumor change were analyzed using the Delta method and Curve-fitting method. Finally, the statistics in the distribution of stable features in patients were calculated. RESULTS: 675 stable features were selected from a total number of 1371 radiomics features, then 12 texture features types were retained and three intensity features were chosen to represent their own category. Among the final selected feature types, it was found that the two time points were weeks 1 and 3 with the higher rate of change. One patient had very few stable tumor features out of a total of 101 features, and the rate of change of features of another patient was conspicuously higher than the average level with number of 301 features. CONCLUSION: The longitudinal CT radiomics could demonstrate the change trend of tumor and at which point exhibit the greatest change during radiotherapy, and potentially be used for treatment decisions concerning adaptive radiotherapy.
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spelling pubmed-86888902021-12-30 Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features Zhang, Ruiping Cai, Zhengting Luo, Yan’an Wang, Zhizhen Wang, Wei Eur J Radiol Open Article PURPOSE: Explore the longitudinal CT-based radiomics to demonstrate the changing trend of radiotherapy response and to determine at which point after the onset of treatment radiomics exhibit the greatest change for stage III NSCLC patients. METHODS AND MATERIALS: Ten stage III NSCLC patients in line with inclusion criteria were enrolled retrospectively, each of whom received radiotherapy or concurrent chemo-radiotherapy and performed eight series of follow-up CT imaging. Longitudinal radiomics were extracted on region of interest from the eight registered images, then two steps were conducted to select significant features as indicators of tumor change: 1) stable features were selected by Kendall rank correlation; 2) texture feature types with a steadily changing trend were retained and intensity features with stable change trends were selected to represent the large number of them. Next, the trend and rate of tumor change were analyzed using the Delta method and Curve-fitting method. Finally, the statistics in the distribution of stable features in patients were calculated. RESULTS: 675 stable features were selected from a total number of 1371 radiomics features, then 12 texture features types were retained and three intensity features were chosen to represent their own category. Among the final selected feature types, it was found that the two time points were weeks 1 and 3 with the higher rate of change. One patient had very few stable tumor features out of a total of 101 features, and the rate of change of features of another patient was conspicuously higher than the average level with number of 301 features. CONCLUSION: The longitudinal CT radiomics could demonstrate the change trend of tumor and at which point exhibit the greatest change during radiotherapy, and potentially be used for treatment decisions concerning adaptive radiotherapy. Elsevier 2021-12-16 /pmc/articles/PMC8688890/ /pubmed/34977279 http://dx.doi.org/10.1016/j.ejro.2021.100391 Text en © 2021 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Zhang, Ruiping
Cai, Zhengting
Luo, Yan’an
Wang, Zhizhen
Wang, Wei
Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features
title Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features
title_full Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features
title_fullStr Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features
title_full_unstemmed Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features
title_short Preliminary exploration of response the course of radiotherapy for stage III non-small cell lung cancer based on longitudinal CT radiomics features
title_sort preliminary exploration of response the course of radiotherapy for stage iii non-small cell lung cancer based on longitudinal ct radiomics features
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688890/
https://www.ncbi.nlm.nih.gov/pubmed/34977279
http://dx.doi.org/10.1016/j.ejro.2021.100391
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