A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma

doi:10.1186/s13014-023-02257-w

科研成果详情

题名	A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma
作者	Sun, Mi-Xue1; Zhao, Meng-Jing 2; Zhao, Li-Hao1; Jiang, Hao-Ran1; Duan, Yu-Xia2; Li, Gang1
发表日期	2023-04-11
发表期刊	RADIATION ONCOLOGY 影响因子和分区
语种	英语
原始文献类型	Article
关键词	Nasopharyngeal carcinoma Magnetic resonance imaging Radiomics Nomogram Progression-free survival Prognosis
其他关键词	INTENSITY-MODULATED RADIOTHERAPY ; RADIATION-THERAPY ; HETEROGENEITY ; REGRESSION ; ONCOLOGY ; RISK
摘要	BackgroundTo establish a novel model using radiomics analysis of pre-treatment and post-treatment magnetic resonance (MR) images for prediction of progression-free survival in the patients with stage II-IVA nasopharyngeal carcinoma (NPC) in South China.MethodsOne hundred and twenty NPC patients who underwent chemoradiotherapy were enrolled (80 in the training cohort and 40 in the validation cohort). Acquiring data and screening features were performed successively. Totally 1133 radiomics features were extracted from the T2-weight images before and after treatment. Least absolute shrinkage and selection operator regression, recursive feature elimination algorithm, random forest, and minimum-redundancy maximum-relevancy (mRMR) method were used for feature selection. Nomogram discrimination and calibration were evaluated. Harrell's concordance index (C-index) and receiver operating characteristic (ROC) analyses were applied to appraise the prognostic performance of nomograms. Survival curves were plotted using Kaplan-Meier method.ResultsIntegrating independent clinical predictors with pre-treatment and post-treatment radiomics signatures which were calculated in conformity with radiomics features, we established a clinical-and-radiomics nomogram by multivariable Cox regression. Nomogram consisting of 14 pre-treatment and 7 post-treatment selected features has been proved to yield a reliable predictive performance in both training and validation groups. The C-index of clinical-and-radiomics nomogram was 0.953 (all P < 0.05), which was higher than that of clinical (0.861) or radiomics nomograms alone (based on pre-treatment statistics: 0.942; based on post-treatment statistics: 0.944). Moreover, we received Rad-score of pre-treatment named RS1 and post-treatment named RS2 and all were used as independent predictors to divide patients into high-risk and low-risk groups. Kaplan-Meier analysis showed that lower RS1 (less than cutoff value, - 1.488) and RS2 (less than cutoff value, - 0.180) were easier to avoid disease progression (all P < 0.01). It showed clinical benefit with decision curve analysis.ConclusionsMR-based radiomics measured the burden on primary tumor before treatment and the tumor regression after chemoradiotherapy, and was used to build a model to predict progression-free survival (PFS) in the stage II-IVA NPC patients. It can also help to distinguish high-risk patients from low-risk patients, thus guiding personalized treatment decisions effectively.
出版者	BMC
ISSN	1748-717X
EISSN	1748-717X
卷号	18 期号:1
DOI	10.1186/s13014-023-02257-w
页数	21
WOS类目	Oncology ; Radiology, Nuclear Medicine & Medical Imaging
WOS研究方向	Oncology ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000967202800001
收录类别	SCIE ; PUBMED ; SCOPUS
URL	查看原文
PubMed ID	37041545
SCOPUSEID	2-s2.0-85152293753
通讯作者地址	[Li, Gang]Department of Radiation Oncology,The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,China ; [Duan, Yu-Xia]Department of Radiology,The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,China
Scopus学科分类	Oncology;Radiology, Nuclear Medicine and Imaging
引用统计
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/174886
专题	附属第一医院第一临床医学院（信息与工程学院）、附属第一医院_影像医学与核医学_放射科
通讯作者	Duan, Yu-Xia; Li, Gang
作者单位	1.Department of Radiation Oncology,The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,China; 2.Department of Radiology,The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,China
第一作者单位	附属第一医院; 第一临床医学院（信息与工程学院）、附属第一医院
通讯作者单位	附属第一医院; 第一临床医学院（信息与工程学院）、附属第一医院
第一作者的第一单位	附属第一医院
推荐引用方式 GB/T 7714	Sun, Mi-Xue,Zhao, Meng-Jing,Zhao, Li-Hao,et al. A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma[J]. RADIATION ONCOLOGY,2023,18(1).
APA	Sun, Mi-Xue, Zhao, Meng-Jing, Zhao, Li-Hao, Jiang, Hao-Ran, Duan, Yu-Xia, & Li, Gang. (2023). A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma. RADIATION ONCOLOGY, 18(1).
MLA	Sun, Mi-Xue,et al."A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma".RADIATION ONCOLOGY 18.1(2023).