## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Region** & **Feature** & **Accuracy** & **Sensitivity** & **Specificity** & **AUC (Range)** \\ \hline \multirow{3}{*}{CET} & OEF & 81\% & 87\% & 75\% & 0.79 (0.76–0.84) \\  & CBF & 71\% & 70\% & 71\% & 0.67 (0.55–0.73) \\  & CMRO\({}_{2}\) & 63\% & 27\% & 95\% & 0.52 (0.41–0.68) \\ \hline \multirow{3}{*}{NET2} & OEF & 68\% & 70\% & 66\% & 0.65 (0.46–0.82) \\  & CBF & 73\% & 54\% & 89\% & 0.69 (0.64–0.75) \\  & CMRO\({}_{2}\) & 73\% & 44\% & 99\% & 0.66 (0.61–0.71) \\ \hline \multirow{3}{*}{CET/NET2} & OEF & 69\% & 60\% & 78\% & 0.66 (0.55–0.77) \\  & CBF & 75\% & 63\% & 86\% & 0.80 (0.77–0.82) \\  & CMRO\({}_{2}\) & 83\% & 85\% & 82\% & 0.85 (0.73–0.93) \\ \hline \multirow{3}{*}{Best} & OEF\({}_{\text{CET}}\) + & \multirow{3}{*}{93\%} & \multirow{3}{*}{99\%} & \multirow{3}{*}{88\%} & \multirow{3}{*}{0.94 (0.88–0.96)} \\  & CMRO\({}_{\text{2}}\) & CET/NET2 & & & \\ \hline \hline \end{tabular} Values are shown for contrast-enhancing tumor (CET), peritumoral non-enhancing T2 FLAIR hyperintensity (NET2) and their ratio (CET/NET2). AUC range indicates the lowest and highest values over 10 iterations. OEF-oxygen extraction fraction; CBF: cerebral blood flow; CMRO\({}_{2}\): cerebral metabolic rate of oxygen; AUC: area under the receiver operating characteristic curve.  
\end{table} 
Table 1: Receiver operating characteristic analysis results of a linear kernel support-vector machine trained on oxygenation and perfusion parameters. edema and does not show extensive tumor cell infiltration [42]. This may explain why OEF, CBF and CMRO2 were significantly higher in CET than in NET2 for cMET patients only. We observed OEF in CET of GBM patients to be in line with the results of previous studies [26; 27; 43], reproducing the findings of low OEF, which is possibly a marker of less efficient oxygen extraction due to a physiologically inferior capillary configuration [27], coupled with high CBF. This gives plausibility to the parameter maps calculated with the QSM + qBOLD model that have in the past shown higher, more uniform OEF across the whole brain and more robust CMRO2 estimates than QSM or qBOLD alone [27]. It was surprising, however, to find discrepancies between the OEF values computed in NET2 of GBM patients: While we found lower OEF in NET2 than in CET, reproducing the results of a previous study [43], two other studies found higher OEF in the edema surrounding the tumor [5; 6]. This might either be a cause of incongruent definitions of the ROIs \"edema\" and \"NET2\" or another underlying phenomenon. A PET/MR study with a sufficiently large number of patients might be useful to shed light on true OEF in the peritumoral region of GBM. In addition to the good classification accuracy, the CMRO2 yielded by QSM + qBOLD serves as an important physiological parameter that has been shown to predict tumor response to antiangiogenic therapy as well as progression-free survival and overall survival in GBM patients [44] through association with intratumoral angiogenesis and oxygenation status [45]. Other possible applications of CMRO2 that warrant further investigation consist of monitoring tumor response after initial radiation or chemotherapy and early detection of recurrence. With regard to preoperative imaging, CMRO2 may also serve as a parameter to improve assessment of the surgical margins necessary for a more complete resection of glioblastomas, possibly adding complementary information to conventional MRI sequences for a \"supratotal resection\" [46]. This work is subject to a number of limitations. The QSM + qBOLD model requires a set of assumptions about physiologic parameters that were not measured for each patient individually. Among these assumptions are a constant tissue hematocrit and arterial oxygen saturation.