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Published in: European Radiology 10/2022

31-05-2022 | Head and Neck

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

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

Published in: European Radiology | Issue 10/2022

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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.
Appendix
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Metadata
Title
A MRI-based radiomics model predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma
Authors
Dan Bao
Yanfeng Zhao
Lin Li
Meng Lin
Zheng Zhu
Meng Yuan
Hongxia Zhong
Haijun Xu
Xinming Zhao
Dehong Luo
Publication date
31-05-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 10/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08853-w

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