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European Radiology

, Volume 28, Issue 6, pp 2628–2638 | Cite as

Multiparametric MRI as a potential surrogate endpoint for decision-making in early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma: a systematic review and meta-analysis

  • Chong Hyun Suh
  • Ho Sung KimEmail author
  • Seung Chai Jung
  • Choong Gon Choi
  • Sang Joon Kim
Neuro

Abstract

Objective

To evaluate the value of multiparametric MRI for determination of early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma.

Methods

A computerized search of Ovid-MEDLINE and EMBASE up to 1 October 2017 was performed to find studies on the diagnostic performance of multiparametric MRI for differentiating true progression from pseudoprogression. The beginning search date was not specified. Pooled estimates of sensitivity and specificity were obtained using hierarchical logistic regression modeling. We performed meta-regression and sensitivity analyses to explain the effects of the study heterogeneity.

Results

Nine studies including 456 patients were included. Pooled sensitivity and specificity were 84 % (95 % CI 74–91) and 95 % (95 % CI 83–99), respectively. Area under the hierarchical summary receiver operating characteristic curve was 0.95 (95 % CI 0.92–0.96). Meta-regression showed true progression in the study population, the mean age and the reference standard were significant factors affecting heterogeneity.

Conclusion

Multiparametric MRI may be used as a potential surrogate endpoint for assessment of early treatment response, especially in the differentiation of true progression from pseudoprogression. However, based on the current evidence, monoparametric and multiparametric MRI perform equally in the clinical context. Further evaluation will be needed.

Key Points

Multiparametric MRI shows high diagnostic performance for early treatment response in glioblastoma.

Multiparametric MRI could differentiate true progression from pseudoprogression in newly diagnosed glioblastoma.

The normalized rCBV derived from DSC was the most commonly used parameter.

Keywords

Glioblastoma Magnetic resonance imaging Perfusion Diagnosis Standardization 

Abbreviations

ADC

Apparent diffusion coefficient

ASL

Arterial spin labeling

AUROC

Area under the receiver operating characteristic curve

CBF

Cerebral blood flow

DCE

Dynamic contrast-enhanced imaging

DSC

Dynamic susceptibility-weighted contrast-enhanced imaging

DTI

Diffusion tensor imaging

DWI

Diffusion-weighted imaging

HSROC

Hierarchical summary receiver operating characteristic

IAUC

Initial area under the curve

MRI

Magnetic resonance imaging

MRS

MR spectroscopy

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

QUADAS-2

Quality Assessment of Diagnostic Accuracy Studies-2

RANO

Response assessment in neuro-oncology

rCBV

Relative cerebral blood volume

Notes

Funding

This study was supported by a grant from the National R&D Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea (1720030)

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Ho Sung Kim.

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.

Statistics and biometry

One of the authors (Chong Hyun Suh) has significant statistical expertise (4 years of experience in a systematic review and meta-analysis).

Informed consent

Written informed consent was not required for this study because of the nature of our study, which was a systemic review and meta-analysis.

Ethical approval

Institutional Review Board approval was not required because of the nature of our study, which was a systemic review and meta-analysis.

Methodology

• systematic review

• meta-analysis

• performed at one institution

Supplementary material

330_2017_5262_MOESM1_ESM.docx (5.4 mb)
Supplementary Fig. 1 (DOCX 5501 kb)

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of Radiology and Research Institute of RadiologyUniversity of Ulsan College of Medicine, Asan Medical CenterSeoulRepublic of Korea

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