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The added prognostic value of radiological phenotype combined with clinical features and molecular subtype in anaplastic gliomas

  • Clinical Study
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

Purpose

To determine whether radiological phenotype can improve the predictive performance of the risk model based on molecular subtype and clinical risk factors in anaplastic glioma patients.

Methods

This retrospective study was approved by our institutional review board with waiver of informed consent. MR images of 86 patients with pathologically diagnosed anaplastic glioma (WHO grade III) between January 2007 and February 2016 were analyzed according to the Visually Accessible Rembrandt Images (VASARI) features set. Significant imaging findings were selected to generate a radiological risk score (RRS) for overall survival (OS) and progression-free survival (PFS) using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The prognostic value of RRS was evaluated with multivariate Cox regression including molecular subtype and clinical risk factors. The C-indices of multivariate models with and without RRS were compared by bootstrapping.

Results

Eight VASARI features contributed to RRS for OS and six contributed to PFS. Multifocality or multicentricity was the most influential feature, followed by restricted diffusion. RRS was significantly associated with OS and PFS (P < .001), as well as age and molecular subtype. The multivariate model with RRS demonstrated a significantly higher predictive performance than the model without (C-index difference: 0.074, 95% confidence interval [CI]: 0.031, 0.148 for OS; C-index difference: 0.054, 95% CI: 0.014, 0.123 for PFS).

Conclusion

RRS derived from VASARI features was an independent predictor of survival in patients with anaplastic gliomas. The addition of RRS significantly improved the predictive performance of the molecular feature based model.

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Abbreviations

IDH:

Isocitrate dehydrogenase

WHO:

World health organization

VASARI:

Visually Accesable rembrandt images

RRS:

Radiologic risk score

OS:

Overall survival

PFS:

Progression-free survival

LASSO:

Least absolute shrinkage and selection operator

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Funding

This study was funded from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (Grant No. 2017R1D1A1B03030440) and the faculty research grants of the Yonsei University College of Medicine (Grant No. 6-2015-0079).

Author information

Authors and Affiliations

  1. Department of Radiology, Aerospace Medical Center, Republic of Korea Air Force, Chungcheongbuk-do, Cheongju-si, Republic of Korea

    Minsu Lee

  2. Departments of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea

    Kyunghwa Han, Sung Soo Ahn, Sohi Bae, Yoon Seong Choi & Seung-Koo Lee

  3. Neurosurgery, Yonsei University College of Medicine, Seoul, Republic of Korea

    Jong Hee Chang

  4. Pathology, Yonsei University College of Medicine, Seoul, Republic of Korea

    Se Hoon Kim

  5. Department of Neurosurgery, CHA Bundang Medical Center, School of Medicine, CHA University, Seongnam, Republic of Korea

    Je Beom Hong

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  1. Minsu Lee
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Correspondence to Sung Soo Ahn.

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Lee, M., Han, K., Ahn, S.S. et al. The added prognostic value of radiological phenotype combined with clinical features and molecular subtype in anaplastic gliomas. J Neurooncol 142, 129–138 (2019). https://doi.org/10.1007/s11060-018-03072-0

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  • DOI: https://doi.org/10.1007/s11060-018-03072-0

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