The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: A systematic review and meta-analysis
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Magnetic resonance spectroscopy (MRS) is a powerful tool for preoperative grading of gliomas. We performed a meta-analysis to evaluate the diagnostic performance of MRS in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs).
PubMed and Embase databases were systematically searched for relevant studies of glioma grading assessed by MRS through 27 March 2015. Based on the data from eligible studies, pooled sensitivity, specificity, diagnostic odds ratio and areas under summary receiver operating characteristic curve (SROC) of different metabolite ratios were obtained.
Thirty articles comprising a total sample size of 1228 patients were included in our meta-analysis. Quantitative synthesis of studies showed that the pooled sensitivity/specificity of Cho/Cr, Cho/NAA and NAA/Cr ratios was 0.75/0.60, 0.80/0.76 and 0.71/0.70, respectively. The area under the curve (AUC) of the SROC was 0.83, 0.87 and 0.78, respectively.
MRS demonstrated moderate diagnostic performance in distinguishing HGGs from LGGs using tumoural metabolite ratios including Cho/Cr, Cho/NAA and NAA/Cr. Although there was no significant difference in AUC between Cho/Cr and Cho/NAA groups, Cho/NAA ratio showed higher sensitivity and specificity than Cho/Cr ratio and NAA/Cr ratio. We suggest that MRS should combine other advanced imaging techniques to improve diagnostic accuracy in differentiating HGGs from LGGs.
• MRS has moderate diagnostic performance in distinguishing HGGs from LGGs.
• There is no significant difference in AUC between Cho/Cr and Cho/NAA ratios.
• Cho/NAA ratio is superior to NAA/Cr ratio.
• Cho/NAA ratio shows higher sensitivity and specificity than Cho/Cr and NAA/Cr ratios.
• MRS should combine other advanced imaging techniques to improve diagnostic accuracy.
KeywordsMagnetic resonance spectroscopy Glioma Differentiation Systematic review Meta-analysis
Area under the curve
Diagnostic odds ratio
Diffusion tensor imaging
Lipids and lactate
Positive likelihood ratio
Negative likelihood ratio
Long echo time
Magnetic resonance imaging
Magnetic resonance spectroscopy
Quality Assessment Tool for Diagnostic Accuracy Studies version 2
Single photon mission computed tomography
Summary receiver-operating characteristic curve
Short echo time
The scientific guarantor of this publication is Hui Zhang, PHD. 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. The authors state that this work has not received any funding. One of the authors (Hui Zhang) has significant statistical expertise. Neither institutional review board approval nor written informed consent were required, because of the nature of our study, which was a systemic review and meta-analysis. Methodology: Meta-analysis, performed at one institution.
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