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Meta-Analysis
. 2019 Sep;8(12):5564-5573.
doi: 10.1002/cam4.2369. Epub 2019 Aug 7.

Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis

Sachi Okuchi  1 , Antonio Rojas-Garcia  2 , Agne Ulyte  3 , Ingeborg Lopez  4 , Jurgita Ušinskienė  5 , Martin Lewis  1 , Sara M Hassanein  1   6 , Eser Sanverdi  1 , Xavier Golay  1 , Stefanie Thust  1   7 , Jasmina Panovska-Griffiths  2 , Sotirios Bisdas  1   7
Affiliations
Meta-Analysis

Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis

Sachi Okuchi et al. Cancer Med. 2019 Sep.

Abstract

Background: T1-weighted dynamic contrast-enhanced (DCE) perfusion magnetic resonance imaging (MRI) has been broadly utilized in the evaluation of brain tumors. We aimed at assessing the diagnostic accuracy of DCE-MRI in discriminating between low-grade gliomas (LGGs) and high-grade gliomas (HGGs), between tumor recurrence and treatment-related changes, and between primary central nervous system lymphomas (PCNSLs) and HGGs.

Methods: We performed this study based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis of Diagnostic Test Accuracy Studies criteria. We systematically surveyed studies evaluating the diagnostic accuracy of DCE-MRI for the aforementioned entities. Meta-analysis was conducted with the use of a random effects model.

Results: Twenty-seven studies were included after screening of 2945 possible entries. We categorized the eligible studies into three groups: those utilizing DCE-MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment-related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients). The pooled sensitivity, specificity, and area under the curve for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment-related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively.

Conclusions: Dynamic contrast-enhanced-Magnetic resonance imaging is a promising noninvasive imaging method that has moderate or high accuracy in stratifying gliomas. DCE-MRI shows high diagnostic accuracy in discriminating between HGGs and their low-grade counterparts, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment-related changes as well as PCNSLs and HGGs.

Keywords: dynamic contrast-enhanced MRI; gliomas; lymphoma; meta-analysis; perfusion.

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Conflict of interest statement

None declared.

Figures

Figure 1
Figure 1
Flowchart describing the study selection process. One study was categorized in two categories (HGGs vs LGGs, PCNSLs vs HGGs). DCE, dynamic contrast‐enhanced; HGG, high‐grade glioma; LGG, low‐grade glioma; PCNSL, primary CNS lymphoma
Figure 2
Figure 2
Results of the QUADAS2 quality assessment of the included studies. The risk of bias in four different domains and concerns regarding applicability in three domains are shown
Figure 3
Figure 3
SROC plot of differentiating (A) HGGs from LGGs, (B) recurrence from treatment‐related changes, and (C) PCNSLs from HGGs. AUC, area under the curve; HGG, high‐grade glioma; LGG, low‐grade glioma; PCNSL, primary CNS lymphoma; SENS, sensitivity; SPEC, specificity; SROC, Summary receiver operating characteristic curve
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