Knowledge of the topological and structural heterogeneity of tumor microvasculature is important for monitoring of disease progression and treatment response [1]. A vessel caliber and type dependent temporal shift between the signal of gradient-echo (GE) and spin-echo (SE) dynamic susceptibility-weighted (DSC) MRI has been described recently [1]. This phenomenon forms the basis for the vascular architecture mapping (VAM) technique. In this study we introduce new MR imaging biomarkers for the assessment of vascular pathologies in gliomas using VAM.Forty-six patients with known or suspected brain tumors (7 low-grade glioma, 12 glioma WHO° III, 25 glioblastoma, and 2 meningioma) were examined at 3 Tesla (Trio, Siemens) using the VAM technique. We used a dual contrast agent injection approach to obtain GE- and SE-EPI DSC perfusion MRI data [2]. To minimize patient motions and differences in the time to first-pass peak between the two DSC examinations we employed the following strategies: i) proper fixation of the patient’s head and clear, repeated patient instructions before and during the MRI examinations, and ii) a peripheral pulse unit (PPU) fitted to a finger of the patient 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 (at PPU’s peak systole signal). Geometric parameters and measurement parameters were identical for the GE- and SE-EPI DSC perfusion MRI sequences (TR: 1740 ms; in-plane resolution: 1.8 x 1.8 mm, slice thickness: 4 mm; 29 slices; GRAPPA: 2; and 60 dynamic measurements) except for TE (33 ms for SE-EPI and 22 ms for GE-EPI). Both DSC perfusion MRI examinations were performed with administration of 0.1 mmol/kg-bodyweight gadoterate meglumine (Dotarem, Guerbet) at a rate of 4 ml/s with utmost attention to the injection time (see above). Custom-made in-house MatLab software was used for calculation of ΔR_2,GE versus (ΔR_2,SE)^3/2 diagrams, which we termed vascular hysteresis loops (VHLs, Fig. 1B and C), for each brain voxel. The index Q=ΔR_2,GE/(ΔR_2,SE)^3/2 was calculated. VHLs were evaluated with new versions of the known parameters microvessel radius (R_U) and density (N_U) [3] which were adapted to the temporal shift phenomenon (Fig. 2A) as well as with three new imaging biomarkers: i) microvessel type indicator (MTI) as the signed hysteresis area calculated from the difference between the areas under the ascending and the descending brunch of the VHL (Fig. 2B), ii) vascular induced peak shift (VIPS) as the time shift between the peak signals of SE- and GE-EPI perfusion (Fig. 2C), and iii) the curvature (Curv) of the long-axis of the VHL fitted with a quadratic polynomial (Fig. 2D).Maps of R_U and N_U showed increased levels of heterogeneous structures ranging from mild to severe in glioblastoma and meningioma. Areas with severely increased microvessel density NU were associated mildly increased to normal microvessel radius RU and vice versa, i.e. maps of RU and NU provided complementary and inversely correlated information. Changes in RU and NU were found to be more moderately increased in glioma WHO° III compared to glioblastoma, and were undetectable in low-grade glioma. In accordance with Emblem et al. [1] and Xu et al. [4], VHLs transverse in the counterclockwise direction if the vascular system contains venule- and capillary-like vessel components [1], i.e. in case of more relative venous blood volume [4]. Whereas, VHLs transverse in clockwise direction if vascular system consist of arterioles and capillaries [1], i.e. in case of more relative arterial blood volume [4]. A counterclockwise VHL-direction was associated with negative MTI and VIPS values and a clockwise VHL-direction with positive MTI and VIPS values, respectively. Maps of MTI allowed differentiation between supplying arterial (areas with warm colors in Figs. 2B, 3C, 4C, 5C) and draining venous microvasculature (areas with cool colors in Figs. 2B, 3C, 4C, 5C) within high-grade glioma and meningioma. VIPS provided additional information about microvessel type at the tumor periphery which is partly complementary to MTI. Presumably, VIPS is more sensitive to early angiogenic activity. The changes in MTI and VIPS in combination extended the contrast-enhancing tumor areas. Interestingly, Curv was decreased in tumor but increased in peritumoral vasogenic edema, which might be related to changes in the microvascular architecture due to a breakdown of the tight endothelial junctions that make up the blood-brain barrier.These new MR imaging biomarkers provide insights into the complexity and heterogeneity of vascular changes in brain tumors. However, investigations in more well-defined patient populations and histological validations are required.