Project Summary Although Digital Subtraction Angiography (DSA) provides high resolution, dynamic imaging of blood flow through the brain during arterial filling and venous drainage, its acquisition framerate is currently limited to 1-3 frames-per-seconds to minimize patients' exposure to radiation. Our long-term goal is to contribute toward the development of DSA imaging techniques that are more easily interpretable. Our overall objectives in this application are to (i) develop a new technology capable of producing high framerate DSA acquisition without disrupting current clinical practice, (ii) evaluate the influence of framerate in the classification of entangled feeding and draining vessels for the understanding of cerebrovascular malformations. Our central hypothesis is that images from actual low framerate DSA sequences can be interpolated to generate new in-between images at an arbitrary high framerate. The rationale for this project is that such technology will likely provide a clear and interpretable imaging tool to clinicians that will facilitate diagnosis and planning of neurovascular proceedings. The central hypothesis will be tested by pursuing two specific aims: 1) Develop a technique for generating high framerate DSA sequences from low framerate ones and 2) Test high framerate DSA sequences on entangled feeding and draining vessels in the presence of cerebral malformation. Under the first aim, we will first decompose the sequence into arterial, capillary and venous phases. Next, we will generate a diffusion map to constrain image interpolation. Finally, we will generate intermediate images using a non-linear interpolation method based on contrast intensity and the pre-built diffusion map. For the second aim, we will test our approach on entangled arteries and veins and evaluate its accuracy using various similarity and corruptibility metrics. The proposed project is innovative, in our opinion, because it will be possible to automatically generate high frame rate DSA sequences from low frame rate acquisitions while maintaining low radiation exposure. Our solution does not alter the actual clinical routine, and is a software solution to a hardware problem. The proposed project is significant, because it is expected to provide a solution by which a high framerate DSA sequence can be generated using actual clinical acquisition protocols. The results are expected to have an important positive impact because they will ultimately provide new opportunities for the development of novel interpretation techniques to identify and treat cerebrovascular malformations.