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Abstract Background Glioma grading is a critical procedure for selecting the most effective treatment policy. Biopsy result is the gold standard method for glioma grading, but inherent sampling errors in the biopsy procedure could lead to tumor misclassification. Aim This study evaluated grading performances of a more comprehensive collection of the physiological indices quantified using an optimized dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) paradigm for glioma grading. Methods Thirty-five patients with glioma underwent DCE-MR imaging to evaluate the grading performances of DCE-MRI-derived physiological indices. The statistical differences in the physiological indices between the different grades of gliomas were studied, and the grading performances of these parameters were evaluated using the leave-one-out cross-validation method. Results There were significant statistical differences in DCE-MRI-derived physiological indices between the different grades of gliomas. The mean rCBVs for grade II (low-grade glioma, LGG), grade III, grade IV, and high-grade (HGG) gliomas were 2.03 ± 0.78, 3.61 ± 1.64, 7.14 ± 3.19, and 5.28 ± 3.02, respectively. The mean rCBFs of 1.94 ± 0.97, 2.67 ± 0.96, 4.57 ± 1.77, and 3.57 ± 1.68 were, respectively, quantified for grade II (LGG), grade III, grade IV, and high-grade gliomas. The leave-one-out cross-validation method indicates that the grades of glioma tumors could be determined based on a specific threshold for each physiological index; for example, the optimal cutoff values for rCBF, rCBV, Ktrans, Kep, and Vp indices to distinguish between HGGs and LGGs were 2.11, 2.80, 0.025 mL/g min, 0.29 min−1, and 0.065 mL/g, respectively. Conclusions From the results, it could be concluded that glioma grades could be determined using DCE-MRI-derived physiological indices with an acceptable agreement with histopathological results.

Abstract Background Brain tumors are an important health problem. The preoperative classification of gliomas by non-invasive techniques is a significant problem. Relative cerebral blood volume and spectroscopy have the ability to sample the entire lesion non-invasively. The present study aims to evaluate the combined role of dynamic susceptibility perfusion and spectroscopy in the classification of primary brain tumors. The combination of both provides overall diagnostic accuracy (100%). Relative cerebral blood volume in peritumoral region plays an important additional role in this regard. Results On the basis of histopathology, among 50 patients with brain tumors, high-grade gliomas accounted for 58%, while low-grade gliomas accounted for 42%. The relative cerebral blood volume in the tumor had the best sensitivity, specificity, and accuracy of 96.8%, 95.3%, and 96, respectively. The use of relative cerebral blood volume and choline/N-acetyl Aspartate increased diagnostic accuracy by 100%. Conclusion The combination of magnetic resonance spectroscopy and perfusion can increase sensitivity and positive predictive value to define the degree of glioma.

Objectives: To assess the diagnostic accuracy of DW-MRI, ADC value, and MRS in preoperative glioma grading because of its importance in treatment planning. Patients and methods: A prospective study included 30 patients with gliomas, based on CT and cMRI findings, referred from Neurosurgery Department for DWI and MRS. Results were correlated with histopathological diagnosis after surgical resection. Results: ADC values were significantly higher in low grade gliomas relative to high grade ones. The lowest value was for GBM, 100% sensitivity, specificity, PPV and NPP in glioma grading. MRS revealed higher Cho/NAA and Cho/Cr ratios in high grade neoplasms and characteristic elevated lipid peak with statistical significant difference between low grade and high grade gliomas. MRS was more accurate than ADC value in detecting peritumoral infiltration of high grade gliomas, but there were no statistically significant differences between anaplastic and GBM in tumoral and peritumoral regions. Conclusion: DW-MRI had higher sensitivity, specificity and accuracy than cMRI and MRS in glioma grading while MRS is more accurate than ADC value in assessing peri-tumoral infiltration based on high metabolite ratios in peri-tumoral tissue for anaplastic glioma and GBM, but there were no statistically significant differences between high grade groups.

Background and purpose: Gliomas are very heterogeneous tumors, glioma grading is currently based on the histologic assessment. With noninvasive measurement of vascular permeability by CT Perfusion (CTP) multiple perfusion parameters which can be obtained with a single acquisition the aim of this study was to find the most sensitive and specific CTP parameters and their cutoffs that can be used to differentiate between low and high grade brain gliomas. Material and methods: Twenty-five patients were included in this study divided into two groups: group A includes 15 patients with high grade glioma, group B includes 10 patients with low grade glioma; CTP was done for all patients, perfusion values of tumors were then calculated, and statistical analysis was done using IBM SPSS. Results: A statistically highly significant difference was found between the two groups regarding the BF, BV and PS with P values of 0.0003, 0.00026 and 0.0009 respectively. The two groups were found to be self-discriminated by BV and PS with sensitivity of 95% and 86% respectively. Conclusion: CTP shows high sensitivity in terms of differentiation between high and low grade adult gliomas.