Early detection of recurrence is crucial in patient care. According to the RANO criteria, increase in contrast material enhancement with worsening vasogenic edema and mass effect are the hallmarks of recurrent disease [1]. However, differentiation of treatment related necrosis from recurrent neoplasm is often difficult with conventional MRI (cMRI) because both entities can share the above mentioned features [2]. In this study, we evaluated the usefulness for glioma recurrence grade increase detection of a multiparametric MRI for combined exanimation of oxygen metabolism and microvessel architecture.Forty-one consecutive patients with suspected recurrent glioma (7 WHO°II, 9 WHO°III, 25 glioblastoma) and one patient (glioblastoma WHO°IV) during the first three cycles of antiangiogenic therapy (Avastin) were included in this study. The patient under antiangiogenic therapy received one baseline (one day before Avastin onset) and two follow-up (after the 1st and 3rd cycle) MRI examinations. Vascular architecture mapping (VAM) [3,4] and multiparametric quantitative BOLD (mp-qBOLD) [5] were performed as part of the routine MRI protocol at 3 Tesla (Trio, Siemens). For VAM a dual contrast agent injections approach was used to obtain GE- and SE-EPI DSC perfusion MRI data [6]. To prevent timing differences between the two DSC examinations, a peripheral pulse unit (PPU) which was used to monitor heart rate and cardiac cycle. Special attention was paid to perform the two injections at the same heart rate and exactly at the same phase of the cardiac cycle. For mp-qBOLD additional performed T2*- and T2-mapping sequences were performed. Custom-made in-house MatLab software was used for VAM and mp-qBOLD data postprocessing and compromised 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) [7], and type indicator (MTI). cMRI was diagnosed by two experienced radiologists in consensus.Form the seven patients with a suspected recurrent low-grade glioma (LGG, WHO°II), two patients were diagnosed as recurrent LGG with dedifferentiation based on cMRI (Figs. 1A, B, and E), which was in agreement with the findings from oxygen metabolism: the areas with suspected recurrent LGG showed increased OEF values, whereas in areas with suspected dedifferentiation OEF values were decreased and CMRO₂ values were decreased (Figs. 1C and D). For the remaining five LGG patients no indication for recurrence of the lesion were found on cMRI (Figs. 2A, B, and E), but four patients (57 % of the initial LGG patients) showed significant increased OEF values in the vicinity of the previous location of the lesions (Fig. 1C). Form the seven patients with a suspected recurrent glioma WHO°III, three patients were diagnosed as recurrent glioma based on cMRI, which was in agreement with the findings from oxygen metabolism and microvessel architecture: increased values for CMRO₂, N_U, and MTI within the suspicious regions. For the remaining six patients no indication for recurrence of the lesion were found on cMRI (Figs. 3A, B, and E), but two patients (22 %) showed significant increased CMRO₂, N_U, and MTI values in the vicinity of the previous lesion locations (Figs. 3D, G and H). Form the 25 patients with a suspected recurrent glioblastoma, 12 patients were diagnosed as recurrent glioblastoma based on cMRI, which was in agreement with the findings from oxygen metabolism and microvessel architecture: increased values for CMRO₂, R_U, N_U, and MTI within the suspicious regions. For the remaining 13 patients no indication for recurrence of the lesion were found on cMRI (Figs. 4A, B, and E), but eight patients (32 %) showed significant increased CMRO₂, NU, and MTI values in the vicinity of the previous lesion locations (Figs. 4D, F, G and H). Finally, the follow-up examinations of the patient with a recurrent glioblastoma under anti-angiogenic therapy showed no reliable signs for therapy-induced changes CE T1w and CBV, but a moderate decrease in edema on FLAIR. However, MR imaging biomarkers for oxygen metabolism and microvascular architecture demonstrated changes in tumor physiology during anti-angiogenic therapy. (Fig. 5)Combined assessment of tumor oxygen metabolism and angiogenesis provide insight into tumor biology and thus may be beneficial for follow-up and therapy monitoring in glioma patients. However, investigations in more well-defined patient populations and histological validations are necessary.