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MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma

  • Imaging Informatics and Artificial Intelligence
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To establish and validate a radiomics nomogram for prediction of induction chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients.

Methods

One hundred twenty-three NPC patients (100 in training and 23 in validation cohort) with multi-MR images were enrolled. A radiomics nomogram was established by integrating the clinical data and radiomics signature generated by support vector machine.

Results

The radiomics signature consisting of 19 selected features from the joint T1-weighted (T1-WI), T2-weighted (T2-WI), and contrast-enhanced T1-weighted MRI images (T1-C) showed good prognostic performance in terms of evaluating IC response in two cohorts. The radiomics nomogram established by integrating the radiomics signature with clinical data outperformed clinical nomogram alone (C-index in validation cohort, 0.863 vs 0.549; p < 0.01). Decision curve analysis demonstrated the clinical utility of the radiomics nomogram. Survival analysis showed that IC responders had significant better PFS (progression-free survival) than non-responders (3-year PFS 84.81% vs 39.75%, p < 0.001). Low-risk groups defined by radiomics signature had significant better PFS than high-risk groups (3-year PFS 76.24% vs 48.04%, p < 0.05).

Conclusions

Multiparametric MRI-based radiomics could be helpful for personalized risk stratification and treatment in NPC patients receiving IC.

Key Points

• MRI Radiomics can predict IC response and survival in non-endemic NPC.

• Radiomics signature in combination with clinical data showed excellent predictive performance.

• Radiomics signature could separate patients into two groups with different prognosis.

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Abbreviations

CCRT:

Concurrent chemoradiation

IC:

Induction chemotherapy

IMRT:

Intensity-modulated radiotherapy

LASSO:

Least absolute shrinkage and selection operator

NPC:

Nasopharyngeal carcinoma

PFS:

Progression-free survival

RF:

Random forest

SVM:

Support vector machine

T1-C:

T1 contrast

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Funding

This study has received funding by the National Natural Science Foundation of China Grants 81872699 and Key project of Shanxi Province 2017ZDXM-SF-043.

Author information

Author notes

  1. Lina Zhao and Jie Gong contributed equally to this work.

Authors and Affiliations

  1. Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi’an, China

    Lina Zhao, Man Xu, Yutian Yin & Mei Shi

  2. Life Sciences Research Center, School of Life Sciences and Technology, Xidian University, Xi’an, 710126, China

    Jie Gong & Wei Qin

  3. Department of Radiology, Xijing Hospital, Air Force Medical University, Xi’an, China

    Yibin Xi, Chen Li, Xiaowei Kang & Hong Yin

Authors
  1. Lina Zhao
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  2. Jie Gong
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  3. Yibin Xi
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  4. Man Xu
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  5. Chen Li
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  6. Xiaowei Kang
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  7. Yutian Yin
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  8. Wei Qin
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  9. Hong Yin
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  10. Mei Shi
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Corresponding authors

Correspondence to Wei Qin or Mei Shi.

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Guarantor

The scientific guarantor of this publication is Lina Zhao.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

Yutian Yin, one of the authors, has significant statistical expertise.

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Written informed consent was not required for this study because the retrospective nature of the study.

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Institutional Review Board approval was obtained.

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• retrospective

• diagnostic or prognostic study

• performed at one institution

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Zhao, L., Gong, J., Xi, Y. et al. MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma. Eur Radiol 30, 537–546 (2020). https://doi.org/10.1007/s00330-019-06211-x

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  • DOI: https://doi.org/10.1007/s00330-019-06211-x

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