Multiparametric imaging-based differentiation of lymphoma and glioblastoma: using T1-perfusion, diffusion, and susceptibility-weighted MRI

Saini, Jitender; Gupta, Pradeep Kumar; Awasthi, Ashish; Pandey, Chandra Kant; Singh, Anup; Patir, Rana; Ahlawat, Sunita; Sadashiva, Nishanth; Mahadevan, Anita; Gupta, Rakesh K.

doi:10.1016/j.crad.2018.07.107

Cited by 26 publications

(35 citation statements)

References 39 publications

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“…Detailed information of excluded studies is described in the Supplementary Materials. One further relevant study was also identified, resulting in a final total of 22 studies investigating the diagnostic performance of MRI for differentiating PCNSL from glioblastoma, with these studies covering 1182 patients.…”

Section: Resultsmentioning

confidence: 99%

“…Seven studies enrolled patients in a consecutive manner, while the enrollment was not explicit in the others. Nineteen studies used only histopathology as the reference standard, while two studies used histopathology and clinicoradiologic diagnosis for patients with PCNSL …”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…A variety of MRI sequences were used in various combinations (Table ), with the most commonly used sequences being DWI in 14 studies, DSC in nine studies, and DCE in four studies . The other less‐commonly used sequences were ASL in four studies, SWI in four studies, MRS in three studies, and IVIM in two studies . In terms of the ROI placement, the entire enhancing tumor was selected in 14 studies, and both the entire enhancing tumor and peritumoral area were selected in seven studies .…”

Section: Resultsmentioning

confidence: 99%

“…During the last decade, multiple MRI sequences have been introduced for differentiating PCNSL from glioblastoma . These sequences, which include 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), have demonstrated variable diagnostic performance.…”

mentioning

confidence: 99%

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

Suh

Kim

Jung

et al. 2019

Magnetic Resonance Imaging

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%