BACKGROUND AND PURPOSE: Glioblastoma and primary CNS lymphoma dictate different neurosurgical strategies; it is critical to distinguish them preoperatively. However, current imaging modalities do not effectively differentiate them. We aimed to examine the use of DWI and T1-weighted dynamic contrast-enhanced–MR imaging as potential discriminative tools. MATERIALS AND METHODS: We retrospectively reviewed 18 patients with primary CNS lymphoma and 36 matched patients with glioblastoma with pretreatment DWI and dynamic contrast-enhanced–MR imaging. VOIs were drawn around the tumor on contrast-enhanced T1WI and FLAIR images; these images were transferred onto coregistered ADC maps to obtain the ADC and onto dynamic contrast-enhanced perfusion maps to obtain the plasma volume and permeability transfer constant. Histogram analysis was performed to determine the mean and relative ADC_mean and relative 90th percentile values for plasma volume and the permeability transfer constant. Nonparametric tests were used to assess differences, and receiver operating characteristic analysis was performed for optimal threshold calculations. RESULTS: The enhancing component of primary CNS lymphoma was found to have significantly lower ADC_mean (1.1 × 10⁻³ versus 1.4 × 10⁻³; P < .001) and relative ADC_mean (1.5 versus 1.9; P < .001) and relative 90th percentile values for plasma volume (3.7 versus 5.0; P < .05) than the enhancing component of glioblastoma, but not significantly different relative 90th percentile values for the permeability transfer constant (5.4 versus 4.4; P = .83). The nonenhancing portions of glioblastoma and primary CNS lymphoma did not differ in these parameters. On the basis of receiver operating characteristic analysis, mean ADC provided the best threshold (area under the curve = 0.83) to distinguish primary CNS lymphoma from glioblastoma, which was not improved with normalized ADC or the addition of perfusion parameters. CONCLUSIONS: ADC was superior to dynamic contrast-enhanced–MR imaging perfusion, alone or in combination, in differentiating primary CNS lymphoma from glioblastoma.

BACKGROUND AND PURPOSE: Vertebral hemangiomas are benign vascular lesions that are almost always incidentally found in the spine. Their classic typical hyperintense appearance on T1- and T2-weighted MR images is diagnostic. Unfortunately, not all hemangiomas have the typical appearance, and they can mimic metastases on routine MR imaging. These are generally referred to as atypical hemangiomas and can result in misdiagnosis and ultimately additional imaging, biopsy, and unnecessary costs. Our objective was to assess the utility of dynamic contrast-enhanced MR imaging perfusion in distinguishing vertebral atypical hemangiomas and malignant vertebral metastases. We hypothesized that permeability and vascular density will be increased in metastases compared with atypical hemangiomas. MATERIALS AND METHODS: Consecutive patients from 2011 to 2015 with confirmed diagnoses of atypical hemangiomas and spinal metastases from breast and lung carcinomas with available dynamic contrast-enhanced MR imaging were analyzed. Time-intensity curves were qualitatively compared among the groups. Perfusion parameters, plasma volume, and permeability constant were quantified using an extended Tofts 2-compartment pharmacokinetic model. Statistical significance was tested using the Mann-Whitney U test. RESULTS: Qualitative inspection of dynamic contrast-enhanced MR imaging time-intensity curves demonstrated differences in signal intensity and morphology between metastases and atypical hemangiomas. Quantitative analysis of plasma volume and permeability constant perfusion parameters showed significantly higher values in metastatic lesions compared with atypical hemangiomas (P < .001). CONCLUSIONS: Our data demonstrate that plasma volume and permeability constant perfusion parameters and qualitative inspection of contrast-enhancement curves can be used to differentiate atypical hemangiomas from vertebral metastatic lesions. This work highlights the benefits of adding perfusion maps to conventional sequences to improve diagnostic accuracy.

BACKGROUND AND PURPOSE: Epidermal growth factor receptor variant III is a common mutation in glioblastoma, found in approximately 25% of tumors. Epidermal growth factor receptor variant III may accelerate angiogenesis in malignant gliomas. We correlated T1-weighted dynamic contrast-enhanced MR imaging perfusion parameters with epidermal growth factor receptor variant III status. MATERIALS AND METHODS: Eighty-two consecutive patients with glioblastoma and known epidermal growth factor receptor variant III status who had dynamic contrast-enhanced MR imaging before surgery were evaluated. Volumes of interest were drawn around the entire enhancing tumor on contrast T1-weighted images and then were transferred onto coregistered dynamic contrast-enhanced MR imaging perfusion maps. Histogram analysis with normalization was performed to determine the relative mean, 75th percentile, and 90th percentile values for plasma volume and contrast transfer coefficient. A Wilcoxon rank sum test was applied to assess the relationship between baseline perfusion parameters and positive epidermal growth factor receptor variant III status. The receiver operating characteristic method was used to select the cutoffs of the dynamic contrast-enhanced MR imaging perfusion parameters. RESULTS: Increased relative plasma volume and increased relative contrast transfer coefficient parameters were both significantly associated with positive epidermal growth factor receptor variant III status. For epidermal growth factor receptor variant III–positive tumors, relative plasma volume mean was 9.3 and relative contrast transfer coefficient mean was 6.5; for epidermal growth factor receptor variant III–negative tumors, relative plasma volume mean was 3.6 and relative contrast transfer coefficient mean was 3.7 (relative plasma volume mean, P < .001, and relative contrast transfer coefficient mean, P = .008). The predictive powers of relative plasma volume histogram metrics outperformed those of the relative contrast transfer coefficient histogram metrics (P < = .004). CONCLUSIONS: Dynamic contrast-enhanced MR imaging shows greater perfusion and leakiness in epidermal growth factor receptor variant III–positive glioblastomas than in epidermal growth factor receptor variant III–negative glioblastomas, consistent with the known effect of epidermal growth factor receptor variant III on angiogenesis. Quantitative evaluation of dynamic contrast-enhanced MR imaging may be useful as a noninvasive tool for correlating epidermal growth factor receptor variant III expression and related tumor neoangiogenesis. This potential may have implications for monitoring response to epidermal growth factor receptor variant III–targeted therapies.

Brain tumors lead to modifications of brain networks. Graph theory plays an important role in clarifying the principles of brain connectivity. Our objective was to investigate network modifications related to tumor grade and location using resting-state functional magnetic resonance imaging (fMRI) and graph theory. We retrospectively studied 30 low-grade (LGG), 30 high-grade (HGG) left-hemispheric glioma patients and 20 healthy controls (HC) with rs-fMRI. Tumor location was labeled as: frontal, temporal, parietal, insular or occipital. We collected patients’ clinical data from records. We analyzed whole-brain and hemispheric networks in all patients and HC. Subsequently, we studied lobar networks in subgroups of patients divided by tumor location. Seven graph-theoretical metrics were calculated (FDR p < 0.05). Connectograms were computed for significant nodes. The two-tailed Student t-test or Mann–Whitney U-test (p < 0.05) were used to compare graph metrics and clinical data. The hemispheric network analysis showed increased ipsilateral connectivity for LGG (global efficiency p = 0.03) and decreased contralateral connectivity for HGG (degree/cost p = 0.028). Frontal and temporal tumors showed bilateral modifications; parietal and insular tumors showed only local effects. Temporal tumors led to a bilateral decrease in all graph metrics. Tumor grade and location influence the pattern of network reorganization. LGG may show more favorable network changes than HGG, reflecting fewer clinical deficits.

To examine the functional connectivity of the primary and supplementary motor areas (SMA) in glioma patients using resting-state functional MRI (rfMRI). To correlate rfMRI data with tumor characteristics and clinical information to characterize functional reorganization of resting-state networks (RSN) and the limitations of this method. This study was IRB approved and in compliance with Health Insurance Portability and Accountability Act. Informed consent was waived in this retrospective study. We analyzed rfMRI in 24 glioma patients and 12 age- and sex-matched controls. We compared global activation, interhemispheric connectivity, and functional connectivity in the hand motor RSNs using hemispheric voxel counts, pairwise Pearson correlation, and pairwise total spectral coherence. We explored the relationship between tumor grade, volume, location, and the patient's clinical status to functional connectivity. Global network activation and interhemispheric connectivity were reduced in gliomas ( p < 0.05). Functional connectivity between the bilateral motor cortices and the SMA was reduced in gliomas ( p < 0.01). High-grade gliomas had lower functional connectivity than low-grade gliomas ( p < 0.05). Tumor volume and distance to ipsilateral motor cortex demonstrated no association with functional connectivity loss. Functional connectivity loss is associated with motor deficits in low-grade gliomas, but not in high-grade gliomas. Global reduction in resting-state connectivity in areas distal to tumor suggests that radiological tumor boundaries underestimate areas affected by glioma. Association between motor deficits and rfMRI suggests that rfMRI may accurately reflect functional changes in low-grade gliomas. Lack of association between rfMRI and clinical motor deficits implies decreased sensitivity of rfMRI in high-grade gliomas, possibly due to neurovascular uncoupling.