Shields A, Setlur Nagesh S V, Ionita C, Bednarek D R, Rudin S
Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY.
Proc SPIE Int Soc Opt Eng. 2021 Feb;11600. doi: 10.1117/12.2580888. Epub 2021 Feb 15.
In order to accurately quantify rapidly changing blood flow velocities, as typically seen in the neurovasculature, high temporal resolution is necessary. Current methods to extract velocity data from angiographic image sequences are generally limited to 30 fps or less. High-speed angiography (HSA) with a maximal frame rate of 1000 fps can be used to evaluate time-dependent flow details normally averaged out with lower frame rates. For new HSA image sequences, two different quantitative methods were utilized to extract high-temporal resolution velocity changes: X-Ray Particle Image Velocimetry (X-PIV) and optical flow (OF). A variety of flow conditions were examined in a range of patient-specific 3D-printed phantoms. Both pulsatile and constant flow settings were investigated. X-PIV was performed using radiopaque sub-millimeter microspheres, which were tracked throughout the image sequence to provide accurate, but limited sampling of the velocity field within the 3D-printed models. Also, an open source optical flow algorithm, OpenOpticalFlow, was used to perform velocity estimation based on the spatio-temporal intensity changes of iodinated contrast wavefronts. Periodic changes in velocity within each phantom ROI can be illustrated throughout the pulsatile cycle capture by the high-speed detector. In the constant flow sequences, changes in velocity across the phantom geometry can be seen. The ability to accurately measure detailed velocity distributions and velocity changes throughout various flow conditions at high temporal resolution enables further insight into the evaluation and treatment of neurovascular disease states.
为了准确量化快速变化的血流速度,如在神经血管系统中常见的那样,高时间分辨率是必要的。目前从血管造影图像序列中提取速度数据的方法通常限于30帧每秒或更低。最大帧率为1000帧每秒的高速血管造影(HSA)可用于评估通常会被较低帧率平均掉的随时间变化的血流细节。对于新的HSA图像序列,采用了两种不同的定量方法来提取高时间分辨率的速度变化:X射线粒子图像测速法(X-PIV)和光流法(OF)。在一系列患者特异性的3D打印模型中检查了各种血流情况。研究了脉动流和恒定流设置。X-PIV使用不透射线的亚毫米微球进行,这些微球在整个图像序列中被跟踪,以在3D打印模型内提供速度场的准确但有限的采样。此外,还使用了一种开源光流算法OpenOpticalFlow,根据碘化造影剂波前的时空强度变化来进行速度估计。在高速探测器捕获的脉动周期内,可以显示每个模型感兴趣区域内速度的周期性变化。在恒定流序列中,可以看到模型几何形状上速度的变化。在高时间分辨率下准确测量各种血流情况下详细的速度分布和速度变化的能力,有助于进一步深入了解神经血管疾病状态的评估和治疗。