Arterial Spin Labeling (ASL) can be used for morphological imaging of the arterial architecture. To perform artery-selective imaging, the label process has to be modified so that only a single artery of interest is tagged, e.g. using super-selective ASL [1]. The feasibility of super-selective ASL for static and time-resolved angiographic acquisitions was already presented [2, 3]. However, the measurement of blood flow velocity and direction with ASL-based methods is limited with respect to spatial and time resolutions. Phase-contrast angiography measurements provide higher precision regarding the quantification of hemodynamic blood flow parameters and can add important information for a differential diagnosis [4]. In this study, we present an approach based on ASL that allows selectively visualizing individual arteries of the brain in conjunction with phase-encoded information in order to derive detailed information about blood flow direction and velocity, which may be important for the evaluation of e.g. aneurysms, arterio-venous malformations and stenotic arteries [4].Four healthy volunteers and a patient suffering from an aneurysm in the bifurcation of the right arteria cerebri media underwent MR scanning under the general protocol for sequence development, approved by the local ethical committee. Imaging was performed on a Philips 3T Achieva (Philips, Best, The Netherlands) scanner using a standard 32 channel SENSE Head coil. For tagging, a labeling duration of 1000ms was used in order to ensure sufficient filling of all intracranial arteries [5]. Image acquisition started immediately after labeling using a 3D T1-TFE readout with 0.7mm³ isotropic voxel size and 120 slices. Phase-encoding was performed in right-left, anterior-posterior and feet-head direction. The gradient strengths were chosen to resolve flow velocities of up to 100 cm/s. The acquisition time for a scan of a single artery was 5 min. 49sec. After acquisition of the images, further processing has to be performed. A flow-chart how to perform processing is shown in Fig. 1. First, the magnitude images (label and control) are subtracted to obtain the selective angiograms of the arteries (Fig. 1, left column). From these images, a binary mask is created by means of signal treshholding. Subsequently, the mask is applied to the phase-encoded images representing flow velocities in different directions (Fig. 1, right column). Merging and color-encoding of the masked images results in selective phase-contrast angiograms (Fig. 1, 2a). Additionally, the individual arteries are merged into a single frame, each presenting a single color (Fig. 2b). The signal intensity is used to represent different flow velocities. All calculations were performed using Matlab R2013a (The Mathworks, Natick, MA).Image acquisition was successfully performed in all volunteers and in the patient. Multiple image contrasts were obtained. For instance, the unsubtracted ASL magnitude images might be useful for the evaluation of brain structure due to the high isotropic spatial resolution (Fig. 1). By processing the data, selective phase-encoded angiograms could be obtained (Fig. 2). The high SNR of the subtracted ASL magnitude images allowed creating a binary mask by simple treshholding of the signal intensity. The final post-processed images show high resolution static angiograms of an individual selected artery in conjunction with directional and velocity blood flow information. In the case of the patient scan, the aneurysm could be visualized as projection angiogram without unwanted superposition of contralateral arteries similar to images generated with digital subtraction angiography (Fig. 3). In addition, hemodynamic parameters were quantified which may be important for an advanced diagnosis. Usually, such information cannot be obtained from a single MRI measurement. At least two acquisitions are required, a selective ASL acquisition and a phase-contrast angiography have to be performed individually, which can prolong scan times significantly and make the measurements prone to subject motion in between the acquisitions. Furthermore, it is also possible to obtain a venous-only image from the phase-encoded images (not shown here). For this purpose, a mask of the arterial vessels can be applied to the phase-encoded images, leaving only the signal from the veins in the final images.The presented method makes it possible to gather artery-selective information in conjunction with important hemodynamic parameters like blood flow direction and velocity in the cerebrovascular system within a single acquisition. Further studies in patients suffering from vascular diseases are required to prove the applicability of this method in a clinical setting.