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Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication

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An Editorial Comment to this article was published on 13 September 2022

Abstract

Objectives

To determine whether imaging-based risk stratification enables prognostication in diffuse glioma, NOS (not otherwise specified).

Methods

Data from 220 patients classified as diffuse glioma, NOS, between January 2011 and December 2020 were retrospectively included. Two neuroradiologists analyzed pre-surgical CT and MRI to assign gliomas to the three imaging-based risk types considering well-known imaging phenotypes (e.g., T2/FLAIR mismatch). According to the 2021 World Health Organization classification, the three risk types included (1) low-risk, expecting oligodendroglioma, isocitrate dehydrogenase (IDH)-mutant, and 1p/19q-codeleted; (2) intermediate-risk, expecting astrocytoma, IDH-mutant; and (3) high-risk, expecting glioblastoma, IDH-wildtype. Progression-free survival (PFS) and overall survival (OS) were estimated for each risk type. Time-dependent receiver operating characteristic analysis using 10-fold cross-validation with 100-fold bootstrapping was used to compare the performance of an imaging-based survival model with that of a historical molecular-based survival model published in 2015, created using The Cancer Genome Archive data.

Results

Prognostication according to the three imaging-based risk types was achieved for both PFS and OS (log-rank test, p < 0.001). The imaging-based survival model showed high prognostic value, with areas under the curves (AUCs) of 0.772 and 0.650 for 1-year PFS and OS, respectively, similar to the historical molecular-based survival model (AUC = 0.74 for PFS and 0.87 for OS). The imaging-based survival model achieved high long-term performance in both 3-year PFS (AUC = 0.806) and 5-year OS (AUC = 0.812).

Conclusion

Imaging-based risk stratification achieved histomolecular-level prognostication in diffuse glioma, NOS, and could aid in guiding patient referral for insufficient or unsuccessful molecular diagnosis.

Key Points

• Three imaging-based risk types enable distinct prognostication in diffuse glioma, NOS (not otherwise specified).

• The imaging-based survival model achieved similar prognostic performance as a historical molecular-based survival model.

• For long-term prognostication of 3 and 5 years, the imaging-based survival model showed high performance.

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Abbreviations

AUC:

Area under the curve

CI:

Confidence intervals

FLAIR:

Fluid-attenuated inversion recovery

HR:

Hazard ratio

IDH:

Isocitrate dehydrogenase

NOS:

Not Otherwise Specified

OS:

Overall survival

PFS:

Progression-free survival

RANO:

Response Assessment in Neuro-Oncology

ROC:

Receiver operating characteristic

WHO:

World Health Organization

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Funding

This research was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (grant number: NRF-2020R1A2B5B01001707) and by the Ministry of Health and Welfare, South Korea (HI21C1161).

Author information

Authors and Affiliations

  1. Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea

    Eun Bee Jang, Ho Sung Kim & Ji Eun Park

  2. Department of Statistics and Data Science, Korea National Open University, Seoul, Republic of Korea

    Seo Young Park

  3. Department of Radiology, Shinchon Yonsei Hospital, Seoul, Republic of Korea

    Yeo Kyung Nam

  4. Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea

    Soo Jung Nam

  5. Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea

    Young-Hoon Kim & Jeong Hoon Kim

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  1. Eun Bee Jang
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Correspondence to Ho Sung Kim.

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Guarantor

The scientific guarantor of this publication is Ji Eun Park.

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The authors declare no competing interests.

Statistics and biometry

One of the authors has significant statistical expertise (Seo Young Park, 10-year experienced statistician).

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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

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• performed at one institution

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Jang, E.B., Kim, H.S., Park, J.E. et al. Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication. Eur Radiol 32, 7780–7788 (2022). https://doi.org/10.1007/s00330-022-08850-z

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  • DOI: https://doi.org/10.1007/s00330-022-08850-z

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