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Adding radiomics to the 2021 WHO updates may improve prognostic prediction for current IDH-wildtype histological lower-grade gliomas with known EGFR amplification and TERT promoter mutation status

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Abstract

Objectives

To assess whether radiomic features could improve the accuracy of survival predictions of IDH-wildtype (IDHwt) histological lower-grade gliomas (LGGs) over clinicopathological features.

Methods

Preoperative MRI data of 61 patients with IDHwt histological LGGs were included as the institutional training set. The test set consisted of 32 patients from The Cancer Genome Atlas. Radiomic features (n = 186) were extracted using conventional MRIs. The radiomics risk score (RRS) for overall survival (OS) was derived from the elastic net. Multivariable Cox regression analyses with clinicopathological features (including epidermal growth factor receptor [EGFR] amplification and telomerase reverse transcriptase promoter [TERTp] mutation status) and the RRS were performed. The integrated area under the receiver operating curves (iAUCs) from the models with and without the RRS were compared. The net reclassification index (NRI) for 1-year OS was also calculated. The prognostic value of the RRS was evaluated using the external validation set.

Results

The RRS independently predicted OS (hazard ratio = 48.08; p = 0.001). Compared with the clinicopathological model alone, adding the RRS had a better OS prediction performance (iAUCs 0.775 vs. 0.910), which was internally validated (iAUCs 0.726 vs. 0.884, 1-year OS NRI = 0.497), and a similar trend was found on external validation (iAUCs 0.683 vs. 0.705, 1-year OS NRI = 0.733). The prognostic significance of the RRS was confirmed in the external validation set (p = 0.001).

Conclusions

Integrating radiomics with clinicopathological features (including EGFR amplification and TERTp mutation status) can improve survival prediction in patients with IDHwt LGGs.

Key Points

• Radiomics risk score has the potential to improve survival prediction when added to clinicopathological features (iAUCs increased from 0.775 to 0.910).

• NRIs for 1-year OS showed that the radiomics risk score had incremental value over the clinicopathological model.

• The prognostic significance of the radiomics risk score was confirmed in the external validation set (p = 0.001).

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Abbreviations

AIC:

Akaike information criterion

cIMPACT-NOW:

Consortium to Inform Molecular and Practical Approaches to CNS Tumour Taxonomy

EGFR:

Epidermal growth factor receptor

GLSZM:

Grey-level size zone matrix

iAUC:

Integrated area under the time-dependent receiver operating characteristic curve

IDH:

Isocitrate dehydrogenase

IDHwt:

IDH-wild type

LGG:

Lower-grade glioma

LL:

Log likelihood

NRI:

Net reclassification index

OS:

Overall survival

ROC:

Receiver operating characteristic

RRS:

Radiomics risk score

TCGA:

The Cancer Genome Atlas

TERTp:

Telomerase reverse transcriptase promoter

WHO:

World Health Organization

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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 (2020R1A2C1003886). This research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1I1A1A01071648). This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI21C1161).

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Authors and Affiliations

  1. Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea

    Yae Won Park, Sung Soo Ahn, Kyunghwa Han & Seung-Koo Lee

  2. Department of Statistics and Data Science, Yonsei University, Seoul, Korea

    Sooyon Kim

  3. Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Gyeonggi-do, Korea

    Chae Jung Park

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

    Seok-Gu Kang & Jong Hee Chang

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

    Se Hoon Kim

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  1. Yae Won Park
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Correspondence to Sung Soo Ahn.

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The scientific guarantor of this publication is Professor Seung-Koo Lee, MD, PhD, from Yonsei University College of Medicine (slee@yuhs.ac).

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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.

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One of the authors has significant statistical expertise (K.H., a biostatistics professor with 11 years of experience in biostatistics).

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Park, Y., Kim, S., Park, C. et al. Adding radiomics to the 2021 WHO updates may improve prognostic prediction for current IDH-wildtype histological lower-grade gliomas with known EGFR amplification and TERT promoter mutation status. Eur Radiol 32, 8089–8098 (2022). https://doi.org/10.1007/s00330-022-08941-x

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