Our population consisted of 50 patients aged 3 to 70 years. As in the clinical setting, the incidence of HGG (58%) was higher than that of LGG (42%) and it was higher for men (52%) than for women (48%). Glioblastoma was the commonest type of all gliomas and accounted for 34%. These results are consistent with the estimated international incidence of gliomas [18,19,20]
At an intermediate TE, we found significant differences (P = 0.0001 value) in all reports related to the Cho metabolite (Cho/NAA and Cho/Cr), between low-grade and high-grade tumors (Table 2). In agreement with our results, Faten et al. [21] reported that Cho/NAA and Cho/Cr ratios showed a statistically significant increase in high-grade astrocytoma than low-grade glioma. So MRS has superior diagnostic performance in predicting glioma grade. These findings have also been reported by Fatima et al. [22] and Naser et al. [23].
The present study revealed that for high-grade glioma, we observed Cho/Cr ratios ranging from 1.9 to 8.75 with an average of 3.5 and Cho/NAA ratios ranging from 2 to 7. 5 with an average of 5.1. With regard to the low-grade glioma, Cho/Cr ranging from 1.6 to 1.8 with an average of 1.6. Cho/NAA ratios ranging from 1.2 to 1.8 with an average ratio of 1.6.
Our results are in agreement with those obtained by Naser, Faten, and Fatima, who confirm that ratios related to the Cho metabolite (Cho/NAA and Cho/Cr) are higher for high-grade tumors than for low-grade tumors.
In our study, using ROC analysis, the cut-off values useful for intermediate TE Cho metabolite ratios were used to differentiate high-grade tumors from low-grade tumors; the Cho/NAA ratio to a cut-off value more than 1.8 and the Cho/Cr ratio at a cut-off value of 1.7 with a higher value was considered a high-grade glioma.
Other previous studies have also identified cut-off values [24,25,26,27,28]. However, cut-off values for tumor classification vary from study to study. A possible explanation for these variations could be the differences between MRS imaging methods, including MRI field strength, acquisition parameters, voxel size, and location. Another explanation behind these varieties could be the distinction made in the subject of the study, including the number of patients and the heterogeneity of the tumors.
At an intermediate TE, our results revealed that the sensitivity of Cho/NAA was 100%, indicating that the HGG is correctly classified. This metabolic ratio may, therefore, be useful for determining tumor grades. The corresponding specificity of this ratio was 76.2%, indicating that the less severe tumors were correctly classified. The sensitivity of the Cho/Cr ratios was 96.9%, indicating true positive high rates and false negative low rates; therefore, it is very useful for determining high-grade tumors. However, its high specificity (76.2%) indicates that only a few low-grade tumors have been falsely identified as high grade. These results are consistent with those of Faten, Fatima, and Naser.
In this study, rCBVt was able to differentiate significantly LGG and HGG, with a P value of 0.0001. The present study showed that rCBV ratios ranged from 1.8 to 6.13 with an average of 3.5 for HGG, but for low-grade gliomas, we found lower rCBV ratios of 0.5 at 1.7 with an average of 1.16. This finding is in line with many previous studies [7, 9, 29, 30], highlighting the importance of rCBVt as an indicator of tumor neovascularization in glioma grading.
Another important finding is that rCBVt value with a threshold more than 1.7 can differentiate between LGG and HGG and gives 96.8% sensitivity, 95.2% specificity, and 96% diagnostic accuracy. The 96% specificity reflects a high real negative rate which means that most LGGs have been correctly diagnosed. The relatively high sensitivity means that even though few have been misclassified, most HGGs have been correctly diagnosed. These results reflect those of Fatima et al. [22] who also found that LG and HG could be differentiated from rCBV at the cut-off of 1.33 were 100%, 67%, and 90% respectively.
This study corroborates evidence from previous observations, e.g., Eman et al. [31], Soliman et al. [30], Sparacia et al. [32] who found almost comparable rCBV values with relatively high sensitivity and specificity in the distinction between low- and high-grade gliomas, indicating the reliability of rCBV in this concern.
Interestingly, within the peritumor region, our results revealed that rCBVp had the ability to differentiate between LGG and HGG, with a P value of 0.0001. rCBVp ratios ranging from 0.5 to 3 with a mean of 2.4 for HGG; however, for a low-grade glioma, we observed lower rCBVp ratios ranging from 0.3 to 1 with an average of 0.8.
These results are consistent with different reports [15,16,17], and further argue that malignant infiltration, with neo-angiogenesis, is expanding to the peritumoral HGG tissues but to a lesser extent in LGG. Therefore, rCBVp can be a useful diagnostic tool in glioma grading.
An rCBVp at cut-off value 1, differentiating low-grade glioma from high-grade glioma with a sensitivity of 87.5% and a specificity of 100%, further confirms the importance of the application of rCBVp in this case. The corresponding specificity (100%) reflecting a high real negative rate which means that all LGGs were correctly diagnosed. These results are also reported by Soliman et al. [30], which revealed a threshold value more than 0.7 with a sensitivity of 100%, a specificity of 66.7%, a VPP of 88.2%, a NPV of 100%, and an accuracy 90.5% best distinguish high- and low-grade gliomas. On the other hand, Server et al. [16] also reported this.
The most obvious conclusion emerging from the analysis is that the combination of MRS and MR perfusion with conventional MRI improves the accuracy of the distinction between low- and high-grade gliomas up to 100%. This result was also reported by Zonari P et al. and Di Costanzo et al. [8, 28].
It should be noted that despite the agreement that rCBV is an incredible tool for determining the grading, there is a slight variation in threshold values between literatures. The heterogeneous nature of the tumors, the MRI scanner, the contrast injection protocol, and the method of analysis are partly responsible for these variations.
It is, therefore, necessary to standardize the technique, the method of analysis, the post-treatment, and, subsequently, the rCBV values, so that the DSC-MRI can be applied realistically in the routine protocol of the MRI of brain tumors. In this regard, the American Society for Functional Neuroradiology (ASFNR) has introduced guidelines and recommendations for optimizing the protocol [33].