## 4 Discussion
There were no statistically significant results obtained except for the minimum value. However, this single metric might be skewed due to the small range and large outlier datapoints. Thus, ASL seems to be not an appropriate predictor of MGMT status, which is not surprising, as these kinds of changes likely do not reflect in perfusion changes. Similarly, the type of mutation was analyzed, i.e., IDH-1, NOS, or wildtype (the dataset only had two patients with IDH-2 mutations, which were subsequently discarded), which did not show statistically significant results. Only the minimum shows a \(p\)-value below 0.05, which again has to be interpreted with care as in the MGMT status analysis. As explained in the MGMT status, mutations will not likely cause (strong) changes in perfusion and thus will not be reflected in the ASL analysis. While MRI has been shown to be predictive of MGMT and mutation status, such analyses likely were performed using multiple sequences and contrasts rather than perfusion imaging alone, and therefore, the value of (ASL) perfusion imaging remains questionable [26; 27]. Finally, the differentiation between tumor and edema shows highly statistically significant results (\(p<0.0001\)) for all analyzed metrics. This is obvious, as there is a large signal difference between the tumor volume and the surrounding edema, which is then also reflected in the histograms. Somewhat surprising is that there is no statistically significant difference between perfusion in the surrounding edema of the tumor and the contralateral side. Visually, the box plots show a higher standard deviation compared to the contralateral side, which could hint at a difference in perfusion, i.e., the tumor surrounding the edema area experiences changes in perfusion. As there is cell swelling within the area of the tumor, it is self-evident that perfusion in this area is being reduced. However, the results in this study suggest that there is an overall reduction of perfusion within the entire brain, as the measured values of the contralateral side do not differ much from the ones in the edema area. As a further consequence, this could mean that the cell swelling itself does not influence local perfusion, but the secondary increase in ICP downregulates cerebral perfusion globally. This specific topic, however, seems to have received only low attention in the past [4; 28]. Even there, perfusion mechanisms were only assessed indirectly using DWI [4] to differentiate between tumor or metastasis [28]. A specific edema perfusion-characterizing study has not yet been performed to our knowledge. Observing isolated edema perfusion has several potential advantages, including finding biomarkers that predict drug delivery when administered and prediction of cell death inside the edema. These questions could not be answered in this study; thus, further analysis alongside different methods should be performed. Comparing the findings to the current literature as well as clinical practice shows that ASL holds the potential to add to the current clinical routine use and to be seen as an add-on for glioma evaluation. Current standard methods such as T1, T2 (FLAIR), and DWI still remain the gold standard that should be performed as a minimum [29]. Other methods such as DSC already show the potential of grading gliomas, which, however, happens at the expense of having to use contrast agents [30]. Thus, ASL might be attractive to be used in patients who cannot obtain external contrast agents. Other methods such as SWI can be used as well and show promising results yet are also limited compared to perfusion imaging, such as investigating the vascularity of tumors [31]. More advanced DWI methods such as diffusion kurtosis imaging are being currently investigated yet have not found their way into routine applications yet [32]. The strength of this study is the large number of patients and MRI datasets alongside quality-controlled segmentations of the areas of interest and a multitude of clinical parameters that were assessed.