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Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma

  • Bin Zhang
  • , Jie Tian
  • , Di Dong
  • , Dongsheng Gu
  • , Yuhao Dong
  • , Lu Zhang
  • , Zhouyang Lian
  • , Jing Liu
  • , Xiaoning Luo
  • , Shufang Pei
  • , Xiaokai Mo
  • , Wenhui Huang
  • , Fusheng Ouyang
  • , Baoliang Guo
  • , Long Liang
  • , Wenbo Chen
  • , Changhong Liang
  • , Shuixing Zhang*
  • *Corresponding author for this work
  • Guangdong Academy of Medical Sciences
  • Southern Medical University
  • Chinese Academy of Sciences
  • Shantou University
  • South China University of Technology
  • Huizhou Municipal Central Hospital

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC). Experimental Design: One-hundred and eighteen patients (training cohort: n ¼ 88; validation cohort: n ¼ 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms. Nomogram discrimination and calibration were evaluated. Associations between radiomics features and clinical data were investigated using heatmaps. Results: The radiomics signatures were significantly associated with PFS. A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone. One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system. This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.761 vs. 0.514; P < 2.68 × 10-9). Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.776 vs. 0.649; P < 1.60 × 10-7). Calibration curves showed good agreement. Findings were confirmed in the validation cohort. Heatmaps revealed associations between radiomics features and tumor stages. Conclusions: Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC. These results provide an illustrative example of precision medicine and may affect treatment strategies.

Original languageEnglish
Pages (from-to)4259-4269
Number of pages11
JournalClinical Cancer Research
Volume23
Issue number15
DOIs
StatePublished - 1 Aug 2017
Externally publishedYes

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