Reprogramming energy metabolism and inducing angiogenesis are part of the hallmarks of cancer [1]. The WHO classification distinguishes low grade from high grade gliomas by the presence of microvascular proliferation as a diagnostic criterion and an independent prognostic parameter [2]. A biological link between hypoxia and angiogenesis is generally accepted [3]. However, to date the non-invasive in-vivo assessment of angiogenic activity and oxygen metabolism is still challenging and thus not part of clinical diagnostics of brain tumors. In this study, we introduce a multiparametric magnetic resonance imaging (MRI) approach that enables the combined exanimation of oxygen metabolism and angiogenesis in gliomas.Thirty-five patients with untreated or recurrent glioma (6 WHO°II, 10 WHO°III, 19 glioblastoma) were examined at 3 Tesla (Trio, Siemens) using vascular architecture mapping (VAM) [4,5] and multiparametric quantitative BOLD (mp-qBOLD) [6] as part of the routine MRI protocol. For VAM a dual contrast agent injections approach was used to obtain GE- and SE-EPI DSC perfusion MRI data [7]. To minimize patient motions the head of the patients were fixated as well as clear and repeated patient instructions before and during the MRI examination were provided. To prevent differences in the time to first-pass peak between the two DSC examinations, a peripheral pulse unit (PPU) which was fitted to a patient’s finger to monitor heart rate and cardiac cycle was used. Special attention was paid to perform the two injections at the same heart rate and exactly at the same phase of the cardiac cycle, i.e. at PPU’s peak systole signal. For mp-qBOLD, additional T2*- and T2-mapping sequences were performed. Geometric parameters (in-plane resolution: 1.8 x 1.8 mm, slice thickness: 4 mm; 29 slices) were identical for VAM and mp-qBOLD sequences. Custom-made in-house MatLab software was used for VAM and mp-qBOLD data postprocessing and comprising the following 5 main steps: 1) calculation of CBV and CBF maps from GE-EPI DSC data; 2) calculation of T2* and T2 maps; 3) calculation of maps of the oxygen metabolism MRI biomarkers oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO₂); 4) calculation of ΔR_2,GE versus (ΔR_2,SE)^3/2 diagrams (vascular hysteresis loops, VHLs) from GE- and SE-EPI DSC data; and 5) calculation of maps of the vascular architecture MRI biomarkers microvessel radius (R_U), density (N_U) [8], and type indicator (MTI).Low-grade glioma (LGGs, WHO°II) showed increased OEF compared to contralateral normal-appearing brain (CNB; p=0.027), peritumoral (predom. edematous) regions (p=0.028; Fig. 1C, Tab. 1), and high-grade gliomas (HGGs, WHO°III and IV, p<0.001) (Figs. 2C and 3C). No microvascular changes due to tumor-induced angiogenic activity within LGGs and their peritumoral regions (Figs. 1F and 1H), but in fact a lower microvessel density N_U (Fig. 1G) compared to cNB/peritumoral (p=0.046) and HGGs (p=0.011 and p<0.001) were detected. The increased OEF values in LGGs might be associated with an only slightly increased tumor oxygen demand as well as with a lower N_U. This higher OEF is sufficient to cover the oxygen demand of LGGs. Further increase in oxygen metabolism due to dedifferentiation of the lesion will initiate angiogenic processes. HGGs (WHO°III and IV) demonstrated significantly decreased OEF (Figs. 2C and 3C) and increased NU values (Figs. 2G and 3G) compared to cNB (p=0.005 and p<0.001) (Tab. 1). Glioblastomas showed large areas with significantly increased CMRO₂ (p<0.001) (Fig 3D, Tab. 1). Areas with highest CMRO₂ values were positively correlated with high NU (Fig 3G). These tumor areas with severely increased microvessel density N_U showed, in turn, only mildly increased to normal microvessel radius RU and vice versa, i.e. maps of R_U and N_U provided complementary and inversely correlated information. Maps of MTI allowed differentiation between supplying arterial (small areas with warm colors) and draining venous microvasculature (widespread areas, especially in glioblastoma with cool colors) (Figs. 2H and 3H). These findings can be interpreted that the excessive oxygen demand in HGGs (especially in glioblastoma) is covered and even oversupplied by microvascular changes induced by angiogenesis. The OEF in HGGs is of only the half of that in cNB sufficient to ensure the increased oxygen demand (detected by an increased CMRO₂) of the lesions.Combined assessment of tumor oxygen metabolism and angiogenesis provide insight into tumor biology and thus may be beneficial for grading and therapy monitoring of gliomas. However, investigations in more well-defined patient populations and histological validations are necessary.