Authors:
J Furtner, V Schöpf, M Preusser, U Asenbaum, R Woitek, A Wöhrer, JA Hainfellner, S Wolfsberger, D Prayer
Journal name: 
Eur J Radiol
Citation info: 
83(5):806-810
Abstract: 
Using conventional MRI methods, the differentiation of primary cerebral lymphomas (PCNSL) and other primary brain tumors, such as glioblastomas, is difficult due to overlapping imaging characteristics. This study was designed to discriminate tumor entities using normalized vascular intratumoral signal intensity values (nVITS) obtained from pulsed arterial spin labeling (PASL), combined with intratumoral susceptibility signals (ITSS) from susceptibility-weighted imaging (SWI). Thirty consecutive patients with glioblastoma (n=22) and PCNSL (n=8), histologically classified according to the WHO brain tumor classification, were included. MRIs were acquired on a 3T scanner, and included PASL and SWI sequences. nVITS was defined by the signal intensity ratio between the tumor and the contralateral normal brain tissue, as obtained by PASL images. ITSS was determined as intratumoral low signal intensity structures detected on SWI sequences and were divided into four different grades. Potential differences in the nVITS and ITSS between glioblastomas and PCNSLs were revealed using statistical testing. To determine sensitivity, specificity, and diagnostic accuracy, as well as an optimum cut-off value for the differentiation of PCNSL and glioblastoma, a receiver operating characteristic analysis was used. We found that nVITS (p=0.011) and ITSS (p=0.001) values were significantly higher in glioblastoma than in PCNSL. The optimal cut-off value for nVITS was 1.41 and 1.5 for ITSS, with a sensitivity, specificity, and accuracy of more than 95%. These findings indicate that nVITS values have a comparable diagnostic accuracy to ITSS values in differentiating glioblastoma and PCNSL, offering a completely non-invasive and fast assessment of tumoral vascularity in a clinical setting.
DOI: 
http://doi.org/10.1016/j.ejrad.2014.01.017
E-pub date: 
01 May 2014
Users with this publication listed: 
Ramona Woitek