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Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients
This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814843/ https://www.ncbi.nlm.nih.gov/pubmed/31653909 http://dx.doi.org/10.1038/s41598-019-51629-4 |
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author | Wang, Jiazhou Shen, Lijun Zhong, Haoyu Zhou, Zhen Hu, Panpan Gan, Jiayu Luo, Ruiyan Hu, Weigang Zhang, Zhen |
author_facet | Wang, Jiazhou Shen, Lijun Zhong, Haoyu Zhou, Zhen Hu, Panpan Gan, Jiayu Luo, Ruiyan Hu, Weigang Zhang, Zhen |
author_sort | Wang, Jiazhou |
collection | PubMed |
description | This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients’ radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment. |
format | Online Article Text |
id | pubmed-6814843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68148432019-10-30 Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients Wang, Jiazhou Shen, Lijun Zhong, Haoyu Zhou, Zhen Hu, Panpan Gan, Jiayu Luo, Ruiyan Hu, Weigang Zhang, Zhen Sci Rep Article This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients’ radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment. Nature Publishing Group UK 2019-10-25 /pmc/articles/PMC6814843/ /pubmed/31653909 http://dx.doi.org/10.1038/s41598-019-51629-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Wang, Jiazhou Shen, Lijun Zhong, Haoyu Zhou, Zhen Hu, Panpan Gan, Jiayu Luo, Ruiyan Hu, Weigang Zhang, Zhen Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients |
title | Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients |
title_full | Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients |
title_fullStr | Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients |
title_full_unstemmed | Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients |
title_short | Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients |
title_sort | radiomics features on radiotherapy treatment planning ct can predict patient survival in locally advanced rectal cancer patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814843/ https://www.ncbi.nlm.nih.gov/pubmed/31653909 http://dx.doi.org/10.1038/s41598-019-51629-4 |
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