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A MRI-based radiomics model predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma

  • Head and Neck
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Abstract

Objectives

To develop and validate a radiomics-based model for predicting radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) by pretreatment MRI of the temporal lobe.

Methods

A total of 216 patients with diagnosed NPC were retrospectively reviewed. Patients were randomly allocated to the training (n = 136) and the validation cohort (n = 80). Radiomics features were extracted from pretreatment contrast-enhanced T1- or fat-suppressed T2 weighted MRI. A radiomics signature was generated by the least absolute shrinkage and selection operator (LASSO) regression algorithm, Pearson correlation analysis, and univariable logistic analysis. Clinical features were selected with logistic regression analysis. Multivariable logistic regression analysis was conducted to develop three models for RTLI prediction in the training cohort: namely radiomics signature, clinical variables, and clinical-radiomics parameters. A radiomics nomogram was used and assessed with respect to calibration, discrimination, reclassification, and clinical application.

Results

The radiomics signature, composed of two radiomics features, was significantly associated with RTLI. The proposed radiomics model demonstrated favorable discrimination in both the training (AUC, 0.89) and the validation cohort (AUC, 0.92), outperforming the clinical prediction model (p < 0.05). Combining radiomics and clinical features, higher AUCs were achieved (AUC, 0.93 and 0.95), as well as a better calibration and improved accuracy of the prediction of RTLI. The clinical-radiomics model showed also excellent performance in predicting RTLI in different clinical-pathologic subgroups.

Conclusion

A radiomics model derived from pretreatment MRI of the temporal lobe showed persuasive performance for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

Key Points

• Radiomics features from pretreatment MRI are associated with radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

• The radiomics model shows better predictive performance than a clinical model and was similar to a clinical-radiomics model.

• A clinical-radiomics model shows excellent performance in the prediction of radiation-induced temporal lobe injury in different clinical-pathologic subgroups.

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Abbreviations

AUC:

Area under the curve

IMRT:

Intensity-modulated radiotherapy

NPC:

Nasopharyngeal carcinoma

ROI:

Region of interest

RTLI:

Radiotherapy-induced temporal lobe injury

TL:

Temporal lobe

VOI:

Volume of interests

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Funding

This study has received funding from the Non-profit Central Research Institute Fund of the Chinese Academy of Medical Sciences (2019XK320073).

Author information

Author notes

  1. Yanfeng Zhao and Dehong Luo contributed equally to this work as corresponding authors.

Authors and Affiliations

  1. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China

    Dan Bao, Yanfeng Zhao, Lin Li, Meng Lin, Zheng Zhu, Hongxia Zhong, Haijun Xu, Xinming Zhao & Dehong Luo

  2. Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China

    Meng Yuan

  3. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China

    Dehong Luo

Authors
  1. Dan Bao
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  2. Yanfeng Zhao
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  3. Lin Li
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  4. Meng Lin
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  8. Haijun Xu
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  9. Xinming Zhao
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  10. Dehong Luo
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Corresponding authors

Correspondence to Yanfeng Zhao or Dehong Luo.

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Guarantor

The scientific guarantor of this publication is Dehong Luo.

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

One of the authors has significant statistical expertise.

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Written informed consent was waived by the Institutional Review Board.

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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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Bao, D., Zhao, Y., Li, L. et al. A MRI-based radiomics model predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma. Eur Radiol 32, 6910–6921 (2022). https://doi.org/10.1007/s00330-022-08853-w

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  • DOI: https://doi.org/10.1007/s00330-022-08853-w

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