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European Radiology

, Volume 27, Issue 9, pp 3583–3592 | Cite as

Volume of high-risk intratumoral subregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma

  • Yi CuiEmail author
  • Shangjie Ren
  • Khin Khin Tha
  • Jia Wu
  • Hiroki Shirato
  • Ruijiang Li
Magnetic Resonance

Abstract

Objective

To develop and validate a volume-based, quantitative imaging marker by integrating multi-parametric MR images for predicting glioblastoma survival, and to investigate its relationship and synergy with molecular characteristics.

Methods

We retrospectively analysed 108 patients with primary glioblastoma. The discovery cohort consisted of 62 patients from the cancer genome atlas (TCGA). Another 46 patients comprising 30 from TCGA and 16 internally were used for independent validation. Based on integrated analyses of T1-weighted contrast-enhanced (T1-c) and diffusion-weighted MR images, we identified an intratumoral subregion with both high T1-c and low ADC, and accordingly defined a high-risk volume (HRV). We evaluated its prognostic value and biological significance with genomic data.

Results

On both discovery and validation cohorts, HRV predicted overall survival (OS) (concordance index: 0.642 and 0.653, P < 0.001 and P = 0.038, respectively). HRV stratified patients within the proneural molecular subtype (log-rank P = 0.040, hazard ratio = 2.787). We observed different OS among patients depending on their MGMT methylation status and HRV (log-rank P = 0.011). Patients with unmethylated MGMT and high HRV had significantly shorter survival (median survival: 9.3 vs. 18.4 months, log-rank P = 0.002).

Conclusion

Volume of the high-risk intratumoral subregion identified on multi-parametric MRI predicts glioblastoma survival, and may provide complementary value to genomic information.

Key points

High-risk volume (HRV) defined on multi-parametric MRI predicted GBM survival.

The proneural molecular subtype tended to harbour smaller HRV than other subtypes.

Patients with unmethylated MGMT and high HRV had significantly shorter survival.

HRV complements genomic information in predicting GBM survival

Keywords

Multi-parametric MRI Glioblastoma multiforme High-risk tumour volume Overall survival Radiogenomics 

Notes

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Dr. Ruijiang Li.

Conflict of interest

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.

Funding

This research was partially funded by the NIH (grant number: R01 CA193730), and partially supported by the Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, founded by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. Part of the data used in this research was obtained from The Cancer Imaging Archive (TCIA) sponsored by the Cancer Imaging Program, DCTD/NCI/NIH.

Statistics and biometry

One of the authors has significant statistical expertise.

Ethical approval

Institutional Review Board approval was obtained.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Methodology

• retrospective

• diagnostic or prognostic study

• multicentre study

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Copyright information

© European Society of Radiology 2017

Authors and Affiliations

  • Yi Cui
    • 1
    • 2
    Email author
  • Shangjie Ren
    • 3
  • Khin Khin Tha
    • 2
    • 4
  • Jia Wu
    • 1
  • Hiroki Shirato
    • 2
    • 4
  • Ruijiang Li
    • 1
    • 2
  1. 1.Department of Radiation OncologyStanford UniversityPalo AltoUSA
  2. 2.Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and EducationHokkaido UniversityHokkaidoJapan
  3. 3.School of Electrical Engineering and AutomationTianjin UniversityTianjin ShiChina
  4. 4.Department of Radiology and Nuclear MedicineHokkaido UniversityHokkaidoJapan

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