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Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas

European Radiology volume 30, pages 6464–6474 (2020)Cite this article

Abstract

Objectives

Isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas of histologic grades II and III follow heterogeneous clinical outcomes, which necessitates risk stratification. We aimed to evaluate whether radiomics from MRI would allow prediction of overall survival in patients with IDHwt lower-grade gliomas and to investigate the added prognostic value of radiomics over clinical features.

Methods

Preoperative MRIs of 117 patients with IDHwt lower-grade gliomas from January 2007 to February 2018 were retrospectively analyzed. The external validation cohort consisted of 33 patients from The Cancer Genome Atlas. A total of 182 radiomic features were extracted. Radiomics risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator (LASSO) and elastic net. Multivariable Cox regression analyses, including clinical features and RRSs, were performed. The integrated areas under the receiver operating characteristic curves (iAUCs) from models with and without RRSs were calculated for comparisons. The prognostic value of RRS was assessed in the validation cohort.

Results

The RRS derived from LASSO and elastic net independently predicted survival with hazard ratios of 9.479 (95% confidence interval [CI], 3.220–27.847) and 6.148 (95% CI, 3.009–12.563), respectively. Those RRSs enhanced model performance for predicting overall survival (iAUC increased to 0.780–0.797 from 0.726), which was externally validated. The RRSs stratified IDHwt lower-grade gliomas in the validation cohort with significantly different survival.

Conclusion

Radiomics has the potential for noninvasive risk stratification and can improve prediction of overall survival in patients with IDHwt lower-grade gliomas when integrated with clinical features.

Key Points

• Isocitrate dehydrogenase wild-type lower-grade gliomas with histologic grades II and III follow heterogeneous clinical outcomes, which necessitates further risk stratification.

• Radiomics risk scores derived from MRI independently predict survival even after incorporating strong clinical prognostic features (hazard ratios 6.148–9.479).

• Radiomics risk scores derived from MRI have the potential to improve survival prediction when added to clinical features (integrated areas under the receiver operating characteristic curves increased from 0.726 to 0.780–0.797).

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Abbreviations

iAUC:

Integrated area under the receiver operating characteristic curve

IDH:

Isocitrate dehydrogenase

IDHwt:

Isocitrate dehydrogenase wild-type

KPS:

Karnofsky Performance Status

OS:

Overall survival

ROC:

Receiver operating characteristic

RRS:

Radiomics risk score

TCGA:

The Cancer Genome Atlas

WHO:

World Health Organization

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Acknowledgments

The authors acknowledge M.S. Haesol Shin from the Department of Biostatistics and Computing, Yonsei University College of Graduate, for her support in statistical analysis. We also acknowledge Sang Wook Kim from the Department of Biomedical Engineering, Korea University, and Dongmin Choi from the Department of Computer Science, Yonsei University, for their support in radiomic feature extraction.

Funding

This research received funding from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies & Future Planning (2017R1D1A1B03030440).

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Authors and Affiliations

  1. Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea

    Chae Jung Park & Seung-Koo Lee

  2. Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea

    Kyunghwa Han, Sung Soo Ahn, Yoon Seong Choi & Yae Won Park

  3. Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Yonsei University College of Medicine, Seoul, South Korea

    Hwiyoung Kim & Sung Soo Ahn

  4. Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea

    Jong Hee Chang

  5. Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea

    Se Hoon Kim

  6. Department of Radiology, Langone Medical Center, New York University School of Medicine, New York, NY, USA

    Rajan Jain

  7. Department of Neurosurgery, Langone Medical Center, New York University School of Medicine, New York, NY, USA

    Rajan Jain

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  1. Chae Jung Park
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Correspondence to Sung Soo Ahn.

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The scientific guarantor of this publication is Sung Soo Ahn.

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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. Kyunghwa Han, Ph.D., from the Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, has significant statistical expertise and one of the authors.

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Park, C.J., Han, K., Kim, H. et al. Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas. Eur Radiol 30, 6464–6474 (2020). https://doi.org/10.1007/s00330-020-07089-w

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Keywords

  • Glioma
  • Isocitrate dehydrogenase
  • Magnetic resonance imaging
  • Radiomics
  • Survival