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      Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T

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          Abstract

          Purpose: To assess the contribution of 1H-magnetic resonance spectroscopy ( 1H-MRS), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic susceptibility contrast-enhanced (DSCE) imaging metrics in the differentiation of glioblastomas from solitary metastasis, and particularly to clarify the controversial reports regarding the hypothesis that there should be a significant differentiation between the intratumoral and peritumoral areas. Methods: Conventional MR imaging, 1H-MRS, DWI, DTI and DSCE MRI was performed on 49 patients (35 glioblastomas multiforme, 14 metastases) using a 3.0-T MR unit. Metabolite ratios, apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) were measured in the intratumoral and peritumoral regions of the lesions. Receiver-operating characteristic analysis was used to obtain the cut-off values for the parameters presenting a statistical difference between the two tumor groups. Furthermore, we investigated the potential effect of the region of interest (ROI) size on the quantification of diffusion properties in the intratumoral region of the lesions, by applying two different ROI methods. Results: Peritumoral N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, Cho/NAA and rCBV significantly differentiated glioblastomas from intracranial metastases. ADC and FA presented no significant difference between the two tumor groups. Conclusions: 1H-MRS and dynamic susceptibility measurements in the peritumoral regions may definitely aid in the differentiation of glioblastomas and solitary metastases. The quantification of the diffusion properties in the intratumoral region is independent of the ROI size placed.

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          High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging.

          To determine whether perfusion-weighted and proton spectroscopic MR imaging can be used to differentiate high-grade primary gliomas and solitary metastases on the basis of differences in vascularity and metabolite levels in the peritumoral region. Fifty-one patients with a solitary brain tumor (33 gliomas, 18 metastases) underwent conventional, contrast material--enhanced perfusion-weighted, and proton spectroscopic MR imaging before surgical resection or stereotactic biopsy. Of the 33 patients with gliomas, 22 underwent perfusion-weighted MR imaging; nine, spectroscopic MR imaging; and two underwent both. Of the 18 patients with metastases, 12 underwent perfusion-weighted MR imaging, and six, spectroscopic MR imaging. The peritumoral region was defined as the area in the white matter immediately adjacent to the enhancing (hyperintense on T2-weighted images, but not enhancing on postcontrast T1-weighted images) portion of the tumor. Relative cerebral blood volumes in these regions were calculated from perfusion-weighted MR data. Spectra from the enhancing tumor, the peritumoral region, and normal brain were obtained from the two-dimensional spectroscopic MR acquisition. The Student t test was used to determine if there was a statistically significant difference in relative cerebral blood volume and metabolic ratios between high-grade gliomas and metastases. The measured relative cerebral blood volumes in the peritumoral region in high-grade gliomas and metastases were 1.31 +/- 0.97 (mean +/- SD) and 0.39 +/- 0.19, respectively. The difference was statistically significant (P <.001). Spectroscopic imaging demonstrated elevated choline levels (choline-to-creatine ratio was 2.28 +/- 1.24) in the peritumoral region of gliomas but not in metastases (choline-to-creatine ratio was 0.76 +/- 0.23). The difference was statistically significant (P =.001). Although conventional MR imaging characteristics of solitary metastases and primary high-grade gliomas may sometimes be similar, perfusion-weighted and spectroscopic MR imaging enable distinction between the two.
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            Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy.

            Proton spectroscopy can noninvasively provide useful information on brain tumor type and grade. Short- (30 ms) and long- (136 ms) echo time (TE) (1)H spectra were acquired from normal white matter (NWM), meningiomas, grade II astrocytomas, anaplastic astrocytomas, glioblastomas, and metastases. Very low myo-Inositol ([mI]) and creatine ([Cr]) were characteristic of meningiomas, and high [mI] characteristic of grade II astrocytomas. Tumor choline ([Cho]) was greater than NWM and increased with grade for grade II and anaplastic astrocytomas, but was highly variable for glioblastomas. Higher [Cho] and [Cr] correlated with low lipid and lactate (P < 0.05), indicating a dilution of metabolite concentrations due to necrosis in high-grade tumors. Metabolite peak area ratios showed no correlation with lipids and mI/Cho (at TE = 30 ms), and Cr/Cho (at TE = 136 ms) best correlated with tumor grade. The quantified lipid, macromolecule, and lactate levels increased with grade of tumor, consistent with progression from hypoxia to necrosis. Quantification of lipids and macromolecules at short TE provided a good marker for tumor grade, and a scatter plot of the sum of alanine, lactate, and delta 1.3 lipid signals vs. mI/Cho provided a simple way to separate most tumors by type and grade. Copyright 2003 Wiley-Liss, Inc.
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              Primary cerebral lymphoma and glioblastoma multiforme: differences in diffusion characteristics evaluated with diffusion tensor imaging.

              Differentiating between primary cerebral lymphoma and glioblastoma multiforme (GBM) based on conventional MR imaging sequences may be impossible. Our hypothesis was that there are significant differences in fractional anisotropy (FA) and apparent diffusion coefficient (ADC) between lymphoma and GBM, which will allow for differentiation between them. Preoperative diffusion tensor imaging (DTI) was performed in 10 patients with lymphoma and 10 patients with GBM. Regions of interest were placed in only solid-enhancing tumor areas and the contralateral normal-appearing white matter (NAWM) to measure the FA and ADC values. The differences in FA and ADC between lymphoma and GBM, as well as between solid-enhancing areas of each tumor type and contralateral NAWM, were analyzed statistically. Cutoff values of FA, FA ratio, ADC, and ADC ratio for distinguishing lymphomas from GBMs were determined by receiver operating characteristic curve analysis. FA and ADC values of lymphoma were significantly decreased compared with NAWM. Mean FA, FA ratio, ADC (x10(-3) mm(2)/s), and ADC ratios were 0.140 +/- 0.024, 0.25 +/- 0.04, 0.630 +/- 0.155, and 0.83 +/- 0.14 for lymphoma, respectively, and 0.229 +/- 0.069, 0.40 +/- 0.12, 0.963 +/- 0.119, and 1.26 +/- 0.13 for GBM, respectively. All of the values were significantly different between lymphomas and GBM. Cutoff values to differentiate lymphomas from GBM were 0.192 for FA, 0.33 for FA ratio, 0.818 for ADC, and 1.06 for ADC ratio. The FA and ADC of primary cerebral lymphoma were significantly lower than those of GBM. DTI is able to differentiate lymphomas from GBM.
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                Author and article information

                Journal
                Cancer Imaging
                Cancer Imaging
                CI
                Cancer Imaging
                Cancer Imaging
                e-Med
                1740-5025
                1470-7330
                2012
                26 October 2012
                : 12
                : 3
                : 423-436
                Affiliations
                aMedical Physics Department, University of Thessaly, Biopolis, 41110 Larissa, Greece; bDepartment of Neurosurgery, University Hospital of Larissa, Biopolis, 41110 Larissa, Greece and cDepartment of Radiology, University Hospital of Larissa, Biopolis 41110, Larissa, Greece
                Author notes
                Corresponding address: Dr Ioannis Tsougos, Medical Physics Department, University Hospital of Larissa, Biopolis, 41110 Larissa, Greece. Email: tsougos@ 123456med.uth.gr

                *These authors contributed equally.

                Article
                ci120038
                10.1102/1470-7330.2012.0038
                3494384
                23108208
                57edf168-b0b0-4b3b-9450-9825240813f2
                © 2012 International Cancer Imaging Society
                History
                : 31 July 2012
                Categories
                Original Article

                spectroscopy,diffusion-weighted imaging,dynamic susceptibility contrast-enhanced imaging,glioblastoma,metastasis

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