Williams Kyle A, Shields Allison, Setlur Nagesh Swetadri Vasan, Chudzik Mitchell, Bednarek Daniel R, Rudin Stephen, Ionita Ciprian
University at Buffalo, Department of Biomedical Engineering, Buffalo, New York, United States.
Canon Stroke and Vascular Research Center, Buffalo, New York, United States.
J Med Imaging (Bellingham). 2023 May;10(3):033502. doi: 10.1117/1.JMI.10.3.033502. Epub 2023 Jun 6.
Contrast dilution gradient (CDG) analysis is a quantitative method allowing blood velocity estimation using angiographic acquisitions. Currently, CDG is restricted to peripheral vasculature due to the suboptimal temporal resolution of current imaging systems. We investigate extension of CDG methods to the flow conditions of proximal vasculature using 1000 frames per second (fps) high-speed angiographic (HSA) imaging.
We performed HSA acquisitions using the XC-Actaeon detector and 3D-printed patient-specific phantoms. The CDG approach was used for blood velocity estimation expressed as the ratio of temporal and spatial contrast gradients. The gradients were extracted from 2D contrast intensity maps synthesized by plotting intensity profiles along the arterial centerline at each frame. results obtained at various frame rates via temporal binning of 1000 fps data were retrospectively compared to computational fluid dynamics (CFD) velocimetry. Full-vessel velocity distributions were estimated at 1000 fps via parallel line expansion of the arterial centerline analysis.
Using HSA, the CDG method displayed agreement with CFD at or above 250 fps [mean-absolute error (MAE): , ]. Relative velocity distributions correlated well with CFD at 1000 fps with universal underapproximation due to effects of pulsatile contrast injection (MAE: 4.3 cm/s).
Using 1000 fps HSA, CDG-based extraction of velocities across large arteries is possible. The method is sensitive to noise; however, image processing techniques and a contrast injection, which adequately fills the vessel assist algorithm accuracy. The CDG method provides high resolution quantitative information for rapidly transient flow patterns observed in arterial circulation.
对比剂稀释梯度（CDG）分析是一种利用血管造影采集来估计血流速度的定量方法。目前，由于当前成像系统的时间分辨率欠佳，CDG仅限于外周血管系统。我们使用每秒1000帧（fps）的高速血管造影（HSA）成像来研究将CDG方法扩展至近端血管系统的血流情况。
我们使用XC-Actaeon探测器和3D打印的患者特异性体模进行HSA采集。CDG方法用于估计血流速度，以时间和空间对比剂梯度的比值表示。梯度是从通过在每一帧沿动脉中心线绘制强度轮廓而合成的二维对比剂强度图中提取的。通过对1000 fps数据进行时间分箱在不同帧率下获得的结果，与计算流体动力学（CFD）测速法进行回顾性比较。通过动脉中心线分析的平行线扩展在1000 fps下估计全血管速度分布。
使用HSA时，CDG方法在250 fps及以上与CFD显示出一致性[平均绝对误差（MAE）： ， ]。在1000 fps时，相对速度分布与CFD相关性良好，但由于脉动性对比剂注射的影响存在普遍的低估（MAE：4.3 cm/s）。
使用1000 fps的HSA，可以基于CDG提取大动脉的速度。该方法对噪声敏感；然而，图像处理技术和能充分充盈血管的对比剂注射有助于提高算法准确性。CDG方法为动脉循环中快速瞬态血流模式提供了高分辨率的定量信息。
