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Investigation of MRI-based radiomics model in differentiation between sinonasal primary lymphomas and squamous cell carcinomas

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Abstract

Purpose

To develop and validate an MRI-based radiomics model in differentiation between sinonasal primary lymphomas and squamous cell carcinomas (SCCs).

Materials and methods

One-hundred-and-fifty-four patients were enrolled (74 individuals with SCCs and 80 with lymphomas). After feature analysis and feature selection with variance threshold and least absolute shrinkage and selection operator (LASSO) methods, an MRI-based radiomics model with the support vector machine (SVM) classifier was constructed in differentiation between lymphomas and SCCs. Areas under the receiver operating characteristic curves (AUCs) of the MRI-based radiomics model were compared with those of radiologists using Delong test.

Results

Five features (T1 original shape Compactness2, T1 wavelet-HHH first-order Total Energy, T2 wavelet-HLH GLCM Informational Measure of Correlation1, T1 wavelet-LHL GLCM Inverse Variance and T1 square GLRLM Long Run Low Gray Level Emphasis) were finally selected in the radiomics model. The AUC values in differentiation between lymphomas and SCCs were 0.94 for the training dataset and 0.85 for the validation dataset, respectively. For all the patient datasets, the AUC values of radiomics model, readers 1, 2 and 3 were 0.92, 0.76, 0.77 and 0.80, respectively. For the validation datasets, no significant difference was found between the AUCs of the radiomics model and those of the three radiologist (P = 0.459, 0.469, 0.738 for radiologist 1, 2 and 3, respectively).

Conclusion

An MRI-based radiomics model can help to differentiate sinonasal lymphomas from SCCs with high accuracy.

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Acknowledgements

The authors thank Feng Li (Department of Radiology, University of Chicago) for revising the manuscript.

Funding

Beijing Municipal Administration of Hospitals’ Ascent Plan (DFL20190203); Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (ZYLX201704); National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2015BAll6H00); High Level Health Technical Personnel of Bureau of Health in Beijing(2014-2-005).

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Authors and Affiliations

  1. Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China

    Xinyan Wang, Qian Wang & Junfang Xian

  2. Huiying Medical Technology Co., Ltd., Beijing, China

    Shuangfeng Dai & Xiangfei Chai

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  1. Xinyan Wang
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  2. Shuangfeng Dai
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Correspondence to Junfang Xian.

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Wang, X., Dai, S., Wang, Q. et al. Investigation of MRI-based radiomics model in differentiation between sinonasal primary lymphomas and squamous cell carcinomas. Jpn J Radiol 39, 755–762 (2021). https://doi.org/10.1007/s11604-021-01116-6

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  • DOI: https://doi.org/10.1007/s11604-021-01116-6

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