Gliomas are heterogeneous tumors. They can show a wide range of mitotic activity, cellular and nuclear pleomorphism, vascular proliferation, and necrotic content. These differences might be apparent even in different parts of the same tumor [7].
In literature, the success rates of conventional MRI in glioma grading range between 55% and 83.3%. Classically, with the use of conventional MRI, tumor grade is predicted considering the presence of heterogeneity, necrosis, contour characteristics, and the presence of hemorrhage and diffusion restriction. However, it has been stated in the literature that these properties are not always reliable for the prediction of tumor grade [8]. Contrast enhancement is another parameter that correlates with tumor grade in conventional MRI techniques. However, it has been reported that approximately 40% of high-grade glioma cases might not enhance with gadolinium-based contrast medium [9, 10]. In addition, low-grade gliomas might show avid contrast enhancement [11]. Reliable and correct grading on MRI is crucial for the treatment plan, especially for patients for whom biopsy is risky [12].
Neovascularization and micro vascular permeability are important parameters for glioma grading, and advanced MRI methods have been trying to provide information about these changes. Perfusion and permeability MRI techniques are the most commonly used for this purpose [9, 10].
Perfusion MRI provides information about tumoral neovascularization and capillary permeability, so that it can be effectively used as a tool for glioma grading. In literature, it has been stated that CBV values are correlated with tumor grade in both primary and metastatic brain tumors [13]. Prediction values suggested for rCBV to predict high-grade tumors differ between 1.50 and1.98, and the most widely used value is 1.75 [14,15,16]. The current study results confirmed the literature data, as all of the high-grade gliomas included in the study had rCBV values > 1.75.
When 1.75 is used as the predictive value for rCBV to differentiate high- and low-grade gliomas, high-grade gliomas can be detected with sensitivity of 83% and specificity of 81%. In contrast to the literature, according to the current study data, a predictive value of 3.25 can differentiate high-grade gliomas with a sensitivity and specificity of 100%.
The mean rCBV value of the low-grade group was higher than the previous findings in literature (2.41 ± 0.55). This difference could have been caused by the relatively small number of patients and the inclusion in the current study of oligodengroglioma cases. Although oligodendrogliomas are low-grade tumors, they generally have high rCBV values, because of their avid neovascularization [13, 17]. It was seen to be consistent with the literature where oligodendroglioma cases have been included that high rCBV values (4.42, 5.01, and 4.44) were reported similar to high-grade gliomas (Fig. 3).
In the literature, the diagnostic success of rCBV has generally been examined for the differentiation of low- and high-grade gliomas. Unlike the literature, the predictive values indicating grade 3 and grade 4 subgroups were found to be different in the current study (a rCBV value of > 3.25 predicts grade 3 with sensitivity and specificity of 100%, and a rCBV value of > 5.67 predicts grade 4 with sensitivity of 100%, and specificity of 92.8%). The current study can be considered to make a valuable contribution to the literature with these predictive values.
rCBF provides information about tissue perfusion. In the literature, it has been stated that rCBF values can differentiate low- and high-grade gliomas, but they are less reliable than rCBV values [16, 18, 19]. This is explained by the wide variability of rCBF values between different studies. This variability can be attributed to the heterogeneous nature of gliomas, such as neovascularisation and blood flow rates which might vary even in different parts of the same tumor [18]. In the current study, rCBF values seemed to be as successful as rCBV values. This difference could be attributed to the relatively homogeneous inner characteristics of the included glioma cases. Moreover, in other studies examining rCBF values, generally one ROI has been used, whereas three ROI placements were used in the current study, which might have minimized the heterogeneity of tumor vascularization and increased rCBF success. The use of at least 3 ROIs can be recommended when predicting tumor grade with rCBF values.
In the literature, the diagnostic success of rCBF has generally been examined for the differentiation of low- and high-grade gliomas. In the current study, unlike the literature, rCBF values were also found to be useful for the differentiation of grade 1–2, grade 3, and grade 4 subgroups from one another.
Permeability MRI is relatively a new method, and there is less knowledge about its success. It has been stated that Ktrans values increase together with the tumor grade [5]. The current study results are consistent with the literature, as the Ktrans values were found to be successful in differentiating high- and low-grade tumors. In the literature, there are few studies defining a predictive Ktrans value for the differentiation of low- and high-grade gliomas. Jain et al. suggested 0.045 as a predictive value [5]. In the current study, a Ktrans value of > 0.043 was found to differentiate low- and high-grade gliomas (sensitivity 81.82%, specificity 100%).
Ve is another permeability MRI parameter. There is limited number of studies examining the diagnostic success of Ve in the differentiation of low- and high-grade gliomas [14, 19, 20]. However, no widely used predictive Ve value could be found in those studies. In the current study, consistent with the literature, Ve was determined to be useful in the differentiation of low- and high-grade gliomas. Furthermore, as a contribution to the literature, it was decided that the predictive Ve value of > 0.255 could predict grade 3 glioma diagnosis with sensitivity and specificity of 100%. A Ve value of > 0.49 indicated grade 4 glioma with sensitivity of 87.5% and specificity of 78.57%.
In the literature, studies have generally examined the correlation between perfusion MRI parameters (rCBV, rCBF, MTT, etc.). rCBV and rCBF values have been shown to have a positive correlation [16]. The current study results are consistent with the literature. Both in whole population and in all of the subgroups, rCBV and rCBF values had a positive correlation. No study could be found which gave information about the correlation between perfusion and permeability MRI parameters. According to the current study data, a positive correlation was present between all parameters in the whole study population. However, this correlation was not present in all the subgroups. Especially in high-grade gliomas, no correlation could be detected between perfusion and permeability parameters. It was concluded that in high-grade gliomas, the changes of blood flow (represented with perfusion parameters) and micro vascular permeability (represented with permeability parameters) do not happen in a balanced manner. Further studies on the molecular/tissue basis will be able to clarify the pathogenesis. It can be concluded that for more precise grading, especially in high-grade cases, combining permeability and perfusion techniques can increase accuracy.
The study has some limitations. As the study focused on the differentiation of glioma grades, the performance of perfusion and permeability MRI could not be evaluated in the differentiation of tumoral and non-tumoral cases. The grade 1 and grade 2 subgroups had to be combined because of the small number of grade 1 glioma cases. Therefore, results cannot be defined independently for grade 1 and 2 tumors. The data of only one perfusion and permeability MRI examination were available for each case. Evaluation of follow-up results could have an effect on the performance of the methods.
