MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma

Abstract This study aimed to develop prognosis signatures through a radiomics analysis for patients with nasopharyngeal carcinoma (NPC) by their pretreatment diagnosis magnetic resonance imaging (MRI). A total of 208 radiomics features were extracted for each patient from a database of 303 patients....

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Autores principales:	Xue Ming, Ronald Wihal Oei, Ruiping Zhai, Fangfang Kong, Chengrun Du, Chaosu Hu, Weigang Hu, Zhen Zhang, Hongmei Ying, Jiazhou Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5b57ecb155e2412fbdb5f7480718207d
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spelling	oai:doaj.org-article:5b57ecb155e2412fbdb5f7480718207d2021-12-02T15:09:13ZMRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma10.1038/s41598-019-46985-02045-2322https://doaj.org/article/5b57ecb155e2412fbdb5f7480718207d2019-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-019-46985-0https://doaj.org/toc/2045-2322Abstract This study aimed to develop prognosis signatures through a radiomics analysis for patients with nasopharyngeal carcinoma (NPC) by their pretreatment diagnosis magnetic resonance imaging (MRI). A total of 208 radiomics features were extracted for each patient from a database of 303 patients. The patients were split into the training and validation cohorts according to their pretreatment diagnosis date. The radiomics feature analysis consisted of cluster analysis and prognosis model analysis for disease free-survival (DFS), overall survival (OS), distant metastasis-free survival (DMFS) and locoregional recurrence-free survival (LRFS). Additionally, two prognosis models using clinical features only and combined radiomics and clinical features were generated to estimate the incremental prognostic value of radiomics features. Patients were clustered by non-negative matrix factorization (NMF) into two groups. It showed high correspondence with patients’ T stage (p < 0.00001) and overall stage information (p < 0.00001) by chi-squared tests. There were significant differences in DFS (p = 0.0052), OS (p = 0.033), and LRFS (p = 0.037) between the two clustered groups but not in DMFS (p = 0.11) by log-rank tests. Radiomics nomograms that incorporated radiomics and clinical features could estimate DFS with the C-index of 0.751 [0.639, 0.863] and OS with the C-index of 0.845 [0.752, 0.939] in the validation cohort. The nomograms improved the prediction accuracy with the C-index value of 0.029 for DFS and 0.107 for OS compared with clinical features only. The DFS and OS radiomics nomograms developed in our study demonstrated the excellent prognostic estimation for NPC patients with a noninvasive way of MRI. The combination of clinical and radiomics features can provide more information for precise treatment decision.Xue MingRonald Wihal OeiRuiping ZhaiFangfang KongChengrun DuChaosu HuWeigang HuZhen ZhangHongmei YingJiazhou WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xue Ming Ronald Wihal Oei Ruiping Zhai Fangfang Kong Chengrun Du Chaosu Hu Weigang Hu Zhen Zhang Hongmei Ying Jiazhou Wang MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
description	Abstract This study aimed to develop prognosis signatures through a radiomics analysis for patients with nasopharyngeal carcinoma (NPC) by their pretreatment diagnosis magnetic resonance imaging (MRI). A total of 208 radiomics features were extracted for each patient from a database of 303 patients. The patients were split into the training and validation cohorts according to their pretreatment diagnosis date. The radiomics feature analysis consisted of cluster analysis and prognosis model analysis for disease free-survival (DFS), overall survival (OS), distant metastasis-free survival (DMFS) and locoregional recurrence-free survival (LRFS). Additionally, two prognosis models using clinical features only and combined radiomics and clinical features were generated to estimate the incremental prognostic value of radiomics features. Patients were clustered by non-negative matrix factorization (NMF) into two groups. It showed high correspondence with patients’ T stage (p < 0.00001) and overall stage information (p < 0.00001) by chi-squared tests. There were significant differences in DFS (p = 0.0052), OS (p = 0.033), and LRFS (p = 0.037) between the two clustered groups but not in DMFS (p = 0.11) by log-rank tests. Radiomics nomograms that incorporated radiomics and clinical features could estimate DFS with the C-index of 0.751 [0.639, 0.863] and OS with the C-index of 0.845 [0.752, 0.939] in the validation cohort. The nomograms improved the prediction accuracy with the C-index value of 0.029 for DFS and 0.107 for OS compared with clinical features only. The DFS and OS radiomics nomograms developed in our study demonstrated the excellent prognostic estimation for NPC patients with a noninvasive way of MRI. The combination of clinical and radiomics features can provide more information for precise treatment decision.
format	article
author	Xue Ming Ronald Wihal Oei Ruiping Zhai Fangfang Kong Chengrun Du Chaosu Hu Weigang Hu Zhen Zhang Hongmei Ying Jiazhou Wang
author_facet	Xue Ming Ronald Wihal Oei Ruiping Zhai Fangfang Kong Chengrun Du Chaosu Hu Weigang Hu Zhen Zhang Hongmei Ying Jiazhou Wang
author_sort	Xue Ming
title	MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
title_short	MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
title_full	MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
title_fullStr	MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
title_full_unstemmed	MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
title_sort	mri-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/5b57ecb155e2412fbdb5f7480718207d
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MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma

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