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  • GLIOMA  (2)
  • 1
    Abstract: 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 kappa was excellent for glioblastoma (kappa = 0.938) and for PCNSL (kappa = 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.
    Type of Publication: Journal article published
    PubMed ID: 23238364
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  • 2
    Abstract: Purpose To compare multiparametric diagnostic performance with diffusion-weighted, dynamic susceptibility-weighted contrast material-enhanced perfusion-weighted, and susceptibility-weighted magnetic resonance (MR) imaging for differentiating primary central nervous system lymphoma (PCNSL) and atypical glioblastoma. Materials and Methods This retrospective study was institutional review board-approved and informed consent was waived. Pretreatment MR imaging was performed in 314 patients with glioblastoma, and a subset of 28 patients with glioblastoma of atypical appearance (solid enhancement with no visible necrosis) was selected. Parameters of diffusion-weighted (apparent diffusion coefficient [ADC]), susceptibility-weighted (intratumoral susceptibility signals [ITSS]), and dynamic susceptibility-weighted contrast-enhanced perfusion-weighted (relative cerebral blood volume [rCBV]) imaging were evaluated in these 28 patients with glioblastoma and 19 immunocompetent patients with PCNSL. A two-sample t test and chi(2) test were used to compare parameters.The diagnostic performance for differentiating PCNSL from glioblastoma was evaluated by using logistic regression analyses with leave-one-out cross validation. Results Minimum, maximum, and mean ADCs and maximum and mean rCBVs were significantly lower in patients with PCNSL than in those with glioblastoma (P 〈 .01, respectively), whereas mean ADCs and mean rCBVs allowed the best diagnostic performance. Presence of ITSS was significantly lower in patients with PCNSL (32% [six of 19]) than in those with glioblastoma (82% [23 of 28]) (P 〈 .01). Multiparametric assessment of mean ADC, mean rCBV, and presence of ITSS significantly increased the probability for differentiating PCNSL and atypical glioblastoma compared with the evaluation of one or two imaging parameters (P 〈 .01), thereby correctly predicting histologic results in 95% (18 of 19) of patients with PCNSL and 96% (27 of 28) of patients with atypical glioblastoma. Conclusion Combined evaluation of mean ADC, mean rCBV, and presence of ITSS allowed reliable differentiation of PCNSL and atypical glioblastoma in most patients, and these results support an integration of advanced MR imaging techniques for the routine diagnostic workup of patients with these tumors. (c) RSNA, 2014.
    Type of Publication: Journal article published
    PubMed ID: 24814181
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