Evaluation of methods to derive blood flow velocity from 1000 fps high-speed angiographic sequences (HSA) using optical flow (OF) and computational fluid dynamics (CFD).

Digital Subtraction Angiography (DSA) is considered the gold standard for imaging and guiding treatment of neurovascular lesions, such as cerebral aneurysms and carotid stenoses. Though DSA can show high-resolution morphology, it remains difficult to extract temporal physiological information, because higher frame-rates are necessary to accurately quantify neurovascular flow details. Recent advances in photon-counting detector technology have led us to develop High-Speed Angiography (HSA), where X-ray images are acquired at 1000 fps for more accurate visualization and quantification of blood flow. Blood flow was imaged using HSA under constant flow conditions within various 3D printed patient-specific phantoms. Blood velocity was quantified using an open source Optical Flow algorithm, OpenOpticalFlow, to perform velocity estimation based on the spatio-temporal intensity changes of iodinated contrast wavefronts. The results of these algorithms are then compared with Computational Fluid Dynamics (CFD) simulations, using the same inlet boundary conditions and model geometries. The performance of these algorithms at lower temporal resolution was then also assessed by simulating lower frame rates from the acquired 1000 fps data. It is important to ascertain the hemodynamic effect of abnormal neurovascular conditions, as well as their effect on treatment of such conditions during the actual clinical interventional procedure. While theoretical CFD results requiring considerable computer capability are delayed for hours or more, it is expected that clinical results from multiple HSA sequences will be available almost immediately while the patient is still under treatment, and even right after flow conditions are changed beneficially by the intervention.