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Abstract SUMMARY The grading of brain tumor is essential in clinical management. Unfortunately, numerous tumors may be inaccessible for biopsy. Regardless the excellent soft tissue contrast provided by MRI, the sensitivity and specificity with which this methodology characterizes tumor type and grade are restricted. MRS and DWIs are a non invasive diagnostic study has been proposed as an alternative strategy for grading of brain tumors as well as for targeting and evaluating response to therapy (Al-Okaili 2007). MRS is a method for analyzing the metabolism of organs and cells, biochemical changes, and quantitative analysis of compounds in humans. Various metabolites in brain tissue, such as NAA, Cho, Cr, lactate, and lipid, can be measured using 1H-MRS (Oshiro etal .,2007) The MRS characteristic of glioma includes a significant reduction in NAA and in Cr and an elevation of Cho. Reduction of NAA reflects loss of neuronal elements, as they are destroyed and/or replaced by malignant cells. Reduced Cr is probably related to an altered metabolism. Elevation of Cho reflects increased membrane synthesis and cellularity. This results in an absolute increase in Cho/Cr and Cho/NAA and a decrease in NAA/Cr ratios (Elshafey et al., 2013). In our study, we have provided cutoff values for Cho/Cr, Cho/NAA, and lactate/Cr ratios to differentiate low- from high-grade gliomas. Tumor cellularity is one of the important parameters for WHO grading of gliomas, with higher grades associated with higher cellularity. ADC is inversely proportional to cellular density. Diffusion of free water molecules in high grade tumors is reduced because of reduction in extra cellular space due to increased cellularity. Therefore, ADC values have a negative correlation with tumor grade. Minimal ADCT value and normalized ADC ratio showed a decreasing trend with increasing tumor grade. Moreover, there was significant difference for ADCT values and normalized ADC ratio between high and low grade gliomas. So combination of sequences increases the accuracy of image assisted grading of gliomas, when compared with individual sequence alone. |