MRI as a diagnostic biomarker for differentiating primary central nervous system lymphoma from glioblastoma: A systematic review and meta‐analysis

• Published in: Journal of magnetic resonance imaging Vol. 50; no. 2; pp. 560 - 572
• Main Authors: Suh, Chong Hyun, Kim, Ho Sung, Jung, Seung Chai, Park, Ji Eun, Choi, Choong Gon, Kim, Sang Joon
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01-08-2019; Wiley Subscription Services, Inc
• Subjects: Biomarkers; Brain cancer; Central nervous system; Confidence intervals; Diagnostic software; Diagnostic systems; diffusion; Field strength; Glioblastoma; Heterogeneity; Lymphoma; Magnetic fields; Magnetic permeability; Magnetic resonance imaging; Magnetic resonance spectroscopy; Medical imaging; Meta-analysis; Nervous system; perfusion; Quality assessment; Quality control; Regression analysis; Sensitivity; Spin dynamics; Spin labeling; Statistical analysis; Statistical tests; Systematic review; diffusion; magnetic resonance imaging; glioblastoma; perfusion; lymphoma
• ISSN: 1053-1807; 1522-2586
• DOI: 10.1002/jmri.26602

Background
Accurate preoperative differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma is clinically crucial because the treatment strategies differ substantially.
Purpose
To evaluate the diagnostic performance of MRI for differentiating PCNSL from glioblastoma.
Study Type
Systematic review and meta‐analysis.
Subjects
Ovid‐MEDLINE and EMBASE databases were searched to find relevant original articles up to November 25, 2018. The search term combined synonyms for "lymphoma," "glioblastoma," and "MRI."
Field Strength/Sequence
Patients underwent at least one MRI sequence including diffusion‐weighted imaging (DWI), dynamic susceptibility‐weighted contrast‐enhanced imaging (DSC), dynamic contrast‐enhanced imaging (DCE), arterial spin labeling (ASL), susceptibility‐weighted imaging (SWI), intravoxel incoherent motion (IVIM), and magnetic resonance spectroscopy (MRS) using 1.5 or 3 T.
Assessment
Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies‐2 tool.
Statistical Tests
Hierarchical logistic regression modeling was used to obtain pooled sensitivity and specificity. Meta‐regression was performed.
Results
Twenty‐two studies with 1182 patients were included. MRI sequences demonstrated high overall diagnostic performance with pooled sensitivity of 91% (95% confidence interval [CI], 87–93%) and specificity of 89% (95% CI, 85–93%). The area under the hierarchical summary receiver operating characteristic curve was 0.92 (95% CI, 0.90–0.94). Studies using DSC or ASL showed high diagnostic performance (sensitivity of 93% [95% CI, 89–97%] and specificity of 91% [95% CI, 86–96%]). Heterogeneity was only detected in specificity (I2 = 66.84%) and magnetic field strength was revealed to be a significant factor affecting study heterogeneity.
Data Conclusion
MRI showed overall high diagnostic performance for differentiating PCNSL from glioblastoma, with studies using DSC or ASL showing high diagnostic performance. Therefore, MRI sequences including DSC or ASL is a potential diagnostic tool for differentiating PCNSL from glioblastoma.
Level of Evidence: 3
Technical Efficacy Stage: 2
J. Magn. Reson. Imaging 2019;50:560–572.