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Updated: May 16, 2026
Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections
Published on: July 31, 2017
Differentiation of glioblastoma and primary CNS lymphomas using susceptibility weighted imaging
Alexander Radbruch1, Benedikt Wiestler, Linda Kramp
1Department of Neuroradiology, University of Heidelberg Medical Center, INF 400, 69120 Heidelberg, Germany. alexander.radbruch@med.uni-heidelberg.de
Introduction:
Reliable differentiation between glioblastoma and primary CNS lymphoma (PCNSL) using conventional MR imaging is challenging, since both entities may show similar appearance on structural MR imaging. Here we analyzed if the appearance of intratumoural susceptibility signals (ITSS) on susceptibility weighted imaging (SWI) may differentiate between both entities.
Methods And Materials:
SWI and contrast enhanced T1-weighted images were acquired from 15 patients with newly diagnosed PCNSL (14 B-cell PCNSL, 1 T-cell PCNSL) and 117 patients with newly diagnosed glioblastoma with a 3 Tesla MR. Additional phase images were available in 8 patients with PCNSL and 88 patients with glioblastoma. Appearance of ITSS was assessed by two readers on SWI and the size of the enhancing lesions on contrast enhanced T1-weighted images were measured. Furthermore it was assessed if ITSS displayed more clearly on SWI or on phase images.
Results:
ITSS were detected in 106 (reader 1) and 109 (reader 2) glioblastoma, respectively. Both readers identified ITSS within the T-cell PCNSL while both readers did not identify any ITSS within the 14 Bcell PCNSL. Interrarter variability as determined by Cohen κ was excellent for glioblastoma (κ=0.938) and for PCNSL (κ=1). The medium size of the enhancing lesion of the glioblastoma that did not harbour ITSS was significantly smaller than the size of the glioblastoma exhibiting ITSS (p<0.008). All identified ITSS displayed more clearly on SWI than on phase images.
Conclusion:
Presence of ITSS differentiates reliably between glioblastoma and B-cell PCNSL and provides a fast bases for the clinical decision without causing any postprocessing work.
