MRI-based radiomics models can improve prognosis prediction for nasopharyngeal carcinoma with neoadjuvant chemotherapy

被引:10
作者
Zeng, Fan [1 ,2 ,3 ]
Lin, Kai-Rong [3 ,4 ]
Jin, Ya-Bin [3 ,4 ]
Li, Hao-Jiang [5 ]
Quan, Qiang [2 ,3 ]
Su, Jian-Chun [2 ,3 ]
Chen, Kai [2 ,3 ]
Zhang, Jing [2 ,3 ]
Han, Chen [2 ,3 ]
Zhang, Guo-Yi [2 ,3 ]
机构
[1] Guangdong Med Univ, Zhanjiang 524000, Peoples R China
[2] Sun Yat Sen Univ, Foshan Hosp, Foshan Acad Med Sci, Dept Radiat Oncol, Foshan 528000, Guangdong, Peoples R China
[3] First Peoples Hosp Foshan, Foshan 528000, Guangdong, Peoples R China
[4] Sun Yat Sen Univ, Foshan Hosp, Foshan Acad Med Sci, Clin Res Inst, Foshan 528000, Guangdong, Peoples R China
[5] Sun Yat Sen Univ, Guangdong Key Lab Nasopharyngeal Carcinoma Diag &, Collaborat Innovat Ctr Canc Med,Canc Ctr, Dept Radiol,State Key Lab Oncol Southern China, Guangzhou 510060, Guangdong, Peoples R China
关键词
Nasopharyngeal carcinoma; Magnetic resonance imaging; Radiomics; Neoadjuvant chemotherapy; BARR-VIRUS DNA; TREATMENT RESPONSE; PHASE-III; CHEMORADIOTHERAPY; RADIOTHERAPY;
D O I
10.1016/j.mri.2022.02.005
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: The purpose of this study was to explore the prognostic value of imaging features and related models in nasopharyngeal carcinoma (NPC) patients that received neoadjuvant chemotherapy. Materials and methods: We systematically reviewed the data of 110 NPC patients who received radiotherapy and neoadjuvant chemotherapy. The patients were randomly divided into the training cohort (n = 88) and the verification cohort (n = 22). The imaging data collected in this study were screened via Pyramidics and used to construct prediction models based on histology and clinical nomographs. The models' accuracy was evaluated via calibration curves and the consistency index (C-index). In addition, we also explored the correlation between radiomics expression patterns, quantitative histological characteristics, and clinical data and then constructed a model to predict the prognosis of NPC. Results: The models that integrated radiomics contours with all the clinical data were superior to those based on the clinical data alone (C-index 0.746 vs. C-index 0.814, respectively) and the calibration curves showed good consistency. The heat map showed that the radiomics expression pattern and selected histological characteristics were correlated with the clinical stage, T stage, and N stage (p < 0.05), and no radiomics feature was associated with lactate dehydrogenase expression, lymphocyte count, or mononuclear cell count. Conclusion: MRI-based radiomics can significantly improve the efficacy of traditional TNM staging and clinical data in predicting the progression-free survival (PFS) of patients with advanced NPC, which may provide an opportunity for precision medicine.
引用
收藏
页码:108 / 115
页数:8
相关论文
共 19 条
[1]   The Evolving Status of Radiomics [J].
Alderson, Philip O. ;
Summers, Ronald M. .
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2020, 112 (09) :869-870
[2]   Pretreatment platelet count as a predictor for survival and distant metastasis in nasopharyngeal carcinoma patients [J].
Chen, Yu-Pei ;
Chen, Chen ;
Mai, Zhuo-Yao ;
Gao, Jin ;
Shen, Lu-Jun ;
Zhao, Bing-Cheng ;
Chen, Meng-Kun ;
Chen, Gang ;
Yan, Fang ;
Huang, Tong-Yi ;
Xia, Yun-Fei .
ONCOLOGY LETTERS, 2015, 9 (03) :1458-1466
[3]   CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma [J].
Coroller, Thibaud P. ;
Grossmann, Patrick ;
Hou, Ying ;
Velazquez, Emmanuel Rios ;
Leijenaar, Ralph T. H. ;
Hermann, Gretchen ;
Lambin, Philippe ;
Haibe-Kains, Benjamin ;
Mak, Raymond H. ;
Aerts, Hugo J. W. L. .
RADIOTHERAPY AND ONCOLOGY, 2015, 114 (03) :345-350
[4]   Gastric cancer: texture analysis from multidetector computed tomography as a potential preoperative prognostic biomarker [J].
Giganti, Francesco ;
Antunes, Sofia ;
Salerno, Annalaura ;
Ambrosi, Alessandro ;
Marra, Paolo ;
Nicoletti, Roberto ;
Orsenigo, Elena ;
Chiari, Damiano ;
Albarello, Luca ;
Staudacher, Carlo ;
Esposito, Antonio ;
Del Maschio, Alessandro ;
De Cobelli, Francesco .
EUROPEAN RADIOLOGY, 2017, 27 (05) :1831-1839
[5]   Radiomic analysis in contrast-enhanced CT: predict treatment response to chemoradiotherapy in esophageal carcinoma [J].
Hou, Zhen ;
Ren, Wei ;
Li, Shuangshuang ;
Liu, Juan ;
Sun, Yu ;
Yan, Jing ;
Wan, Suiren .
ONCOTARGET, 2017, 8 (61) :104444-104454
[6]   Radiomics: Extracting more information from medical images using advanced feature analysis [J].
Lambin, Philippe ;
Rios-Velazquez, Emmanuel ;
Leijenaar, Ralph ;
Carvalho, Sara ;
van Stiphout, Ruud G. P. M. ;
Granton, Patrick ;
Zegers, Catharina M. L. ;
Gillies, Robert ;
Boellard, Ronald ;
Dekker, Andre ;
Aerts, Hugo J. W. L. .
EUROPEAN JOURNAL OF CANCER, 2012, 48 (04) :441-446
[7]   A novel peptide specifically binding to nasopharyngeal carcinoma for targeted drug delivery [J].
Lee, TY ;
Wu, HC ;
Tseng, YL ;
Lin, CT .
CANCER RESEARCH, 2004, 64 (21) :8002-8008
[8]   Pretherapy quantitative measurement of circulating Epstein-Barr virus DNA is predictive of posttherapy distant failure in patients with early-stage nasopharyngeal carcinoma of undifferentiated type [J].
Leung, SF ;
Chan, ATC ;
Zee, B ;
Ma, B ;
Chan, LYS ;
Johnson, PJ ;
Lo, YMD .
CANCER, 2003, 98 (02) :288-291
[9]   Dosiomics: Extracting 3D Spatial Features From Dose Distribution to Predict Incidence of Radiation Pneumonitis [J].
Liang, Bin ;
Yan, Hui ;
Tian, Yuan ;
Chen, Xinyuan ;
Yan, Lingling ;
Zhang, Tao ;
Zhou, Zongmei ;
Wang, Lvhua ;
Dai, Jianrong .
FRONTIERS IN ONCOLOGY, 2019, 9
[10]   Phase III study of concurrent chemoradiotherapy versus radiotherapy alone for advanced nasopharyngeal carcinoma: Positive effect on overall and progression-free survival [J].
Lin, JC ;
Jan, JS ;
Hsu, CY ;
Liang, WM ;
Jiang, RS ;
Wang, WY .
JOURNAL OF CLINICAL ONCOLOGY, 2003, 21 (04) :631-637