Diagnostic Accuracy of Differentiation between Primary Central Nervous System Lymphoma and High-Grade Glioma Using Dynamic Susceptibility Contrast Perfusion Curve Analysis

Abstract

Objective: To determine diagnostic accuracy of visualized dynamic susceptibility contrast (DSC) perfusion curve pattern in differentiation between primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG). Materials and Methods: Forty-one patients (nineteen cases of PCNSL and twenty-two cases of HGG) acquired between January 2010 and November 2017 were included in the present study. The DSC perfusion curve patterns were retrospectively reviewed by two neuroradiologists, divided into two patterns as 1) return of time-intensity curve above the baseline after initial drop, and 2) return of time-intensity curve below or equal to baseline. Sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy were analyzed. Results: Return of time-intensity curve above the baseline on DSC perfusion was found in 15 of 19 (78.9%) PCNSL cases, and only two of 22 (9.1%) HGG cases, p-value<0.001; whereas return of time-intensity curve below or equal to baseline was found in only four of 19 (21.1%) PCNSL cases and 20 of 22 (90.9%) HGG cases, p-value<0.001. Return of time-intensity signal curve above the baseline pattern had sensitivity of 78.9%, specificity of 90.9%, PPV of 88.2%, NPV of 88.3%, and accuracy of 85.4% for diagnosis of PCNSL, respectively. Conclusion: Visualized DSC curve pattern has a role in differentiation between PCNSL and HGG. Presence of return of time-signal intensity curve above the baseline could suggest the diagnosis of PCNSL. Keywords: PCNSL, HGG, DSC perfusion, Curve analysis, Return curve above baseline