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Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging

Background: To develop and validate a radiomic nomogram incorporating radiomic features with clinical variables for individual local recurrence risk assessment in nasopharyngeal carcinoma (NPC) patients before initial treatment. Methods: One hundred and forty patients were randomly divided into a tr...

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Autores principales: Zhang, Lu, Zhou, Hongyu, Gu, Dongsheng, Tian, Jie, Zhang, Bin, Dong, Di, Mo, Xiaokai, Liu, Jing, Luo, Xiaoning, Pei, Shufang, Dong, Yuhao, Huang, Wenhui, Chen, Qiuyin, Liang, Changhong, Lian, Zhouyang, Zhang, Shuixing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691694/
https://www.ncbi.nlm.nih.gov/pubmed/31413740
http://dx.doi.org/10.7150/jca.33345
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author Zhang, Lu
Zhou, Hongyu
Gu, Dongsheng
Tian, Jie
Zhang, Bin
Dong, Di
Mo, Xiaokai
Liu, Jing
Luo, Xiaoning
Pei, Shufang
Dong, Yuhao
Huang, Wenhui
Chen, Qiuyin
Liang, Changhong
Lian, Zhouyang
Zhang, Shuixing
author_facet Zhang, Lu
Zhou, Hongyu
Gu, Dongsheng
Tian, Jie
Zhang, Bin
Dong, Di
Mo, Xiaokai
Liu, Jing
Luo, Xiaoning
Pei, Shufang
Dong, Yuhao
Huang, Wenhui
Chen, Qiuyin
Liang, Changhong
Lian, Zhouyang
Zhang, Shuixing
author_sort Zhang, Lu
collection PubMed
description Background: To develop and validate a radiomic nomogram incorporating radiomic features with clinical variables for individual local recurrence risk assessment in nasopharyngeal carcinoma (NPC) patients before initial treatment. Methods: One hundred and forty patients were randomly divided into a training cohort (n = 80) and a validation cohort (n = 60). A total of 970 radiomic features were extracted from pretreatment magnetic resonance (MR) images of NPC patients from May 2007 to December 2013. Univariate and multivariate analyses were used for selecting radiomic features associated with local recurrence, and multivariate analyses was used for building radiomic nomogram. Results: Eight contrast-enhanced T1-weighted (CET1-w) image features and seven T2-weighted (T2-w) image features were selected to build a Cox proportional hazard model in the training cohort, respectively. The radiomic nomogram, which combined radiomic features and multiple clinical variables, had a good evaluation ability (C-index: 0.74 [95% CI: 0.58, 0.85]) in the validation cohort. The radiomic nomogram successfully categorized those patients into low- and high-risk groups with significant differences in the rate of local recurrence-free survival (P <0.05). Conclusions: This study demonstrates that MR imaging-based radiomics can be used as an aid tool for the evaluation of local recurrence, in order to develop tailored treatment targeting specific characteristics of individual patients.
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spelling pubmed-66916942019-08-14 Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging Zhang, Lu Zhou, Hongyu Gu, Dongsheng Tian, Jie Zhang, Bin Dong, Di Mo, Xiaokai Liu, Jing Luo, Xiaoning Pei, Shufang Dong, Yuhao Huang, Wenhui Chen, Qiuyin Liang, Changhong Lian, Zhouyang Zhang, Shuixing J Cancer Research Paper Background: To develop and validate a radiomic nomogram incorporating radiomic features with clinical variables for individual local recurrence risk assessment in nasopharyngeal carcinoma (NPC) patients before initial treatment. Methods: One hundred and forty patients were randomly divided into a training cohort (n = 80) and a validation cohort (n = 60). A total of 970 radiomic features were extracted from pretreatment magnetic resonance (MR) images of NPC patients from May 2007 to December 2013. Univariate and multivariate analyses were used for selecting radiomic features associated with local recurrence, and multivariate analyses was used for building radiomic nomogram. Results: Eight contrast-enhanced T1-weighted (CET1-w) image features and seven T2-weighted (T2-w) image features were selected to build a Cox proportional hazard model in the training cohort, respectively. The radiomic nomogram, which combined radiomic features and multiple clinical variables, had a good evaluation ability (C-index: 0.74 [95% CI: 0.58, 0.85]) in the validation cohort. The radiomic nomogram successfully categorized those patients into low- and high-risk groups with significant differences in the rate of local recurrence-free survival (P <0.05). Conclusions: This study demonstrates that MR imaging-based radiomics can be used as an aid tool for the evaluation of local recurrence, in order to develop tailored treatment targeting specific characteristics of individual patients. Ivyspring International Publisher 2019-07-10 /pmc/articles/PMC6691694/ /pubmed/31413740 http://dx.doi.org/10.7150/jca.33345 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Zhang, Lu
Zhou, Hongyu
Gu, Dongsheng
Tian, Jie
Zhang, Bin
Dong, Di
Mo, Xiaokai
Liu, Jing
Luo, Xiaoning
Pei, Shufang
Dong, Yuhao
Huang, Wenhui
Chen, Qiuyin
Liang, Changhong
Lian, Zhouyang
Zhang, Shuixing
Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging
title Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging
title_full Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging
title_fullStr Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging
title_full_unstemmed Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging
title_short Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging
title_sort radiomic nomogram: pretreatment evaluation of local recurrence in nasopharyngeal carcinoma based on mr imaging
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691694/
https://www.ncbi.nlm.nih.gov/pubmed/31413740
http://dx.doi.org/10.7150/jca.33345
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