BACKGROUND Comprehensive quantification of intracranial vascular characteristics by vascular tracing provides an objective clinical assessment of vascular structure. However, weak signal or low contrast in small distal arteries, artifacts due to volitional motion, and vascular pulsation are challenges for accurate vessel tracing from 3D time-of-flight (3D-TOF) magnetic resonance angiography (MRA) images. NEW METHOD A vascular measurement refinement algorithm is developed and validated for robust quantification of intracranial vasculature from 3D-TOF MRA. After automated vascular tracing, centerline positions, lumen radii and centerline deviations are jointly optimized to restrict traces to within vascular regions in the straightened curved planar reformation (CPR) views. The algorithm is validated on simulated vascular images and on repeat 3D-TOF MRA acquired from infants and adults. RESULTS The refinement algorithm can reliably estimate vascular radius and correct deviated centerlines. For the simulated vascular image with noise level of 1 and deviation of centerline of 3, the mean radius difference is below 15.3 % for scan-rescan reliability. Vascular features from repeated clinical scans show significantly improved measurement agreement, with intra-class correlation coefficient (ICC) improvement from 0.55 to 0.7 for infants and from 0.59 to 0.92 for adults. COMPARISON WITH EXISTING METHODS The refinement algorithm is novel because it utilizes straightened CPR views that incorporate information from the entire artery. In addition, the optimization corrects centerline positions, lumen radii and centerline deviations simultaneously. CONCLUSIONS Intracranial vasculature quantification using a novel refinement algorithm for vascular tracing improves the reliability of vascular feature measurements in both infants and adults.

中文翻译：

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一种改进婴儿和成人脑血管测量的新算法。

背景技术通过血管追踪对颅内血管特征的综合量化提供了血管结构的客观临床评估。然而，小远端动脉的弱信号或低对比度、由意志运动引起的伪影和血管脉动​​是从 3D 飞行时间 (3D-TOF) 磁共振血管造影 (MRA) 图像准确追踪血管的挑战。新方法 开发并验证了血管测量细化算法，用于从 3D-TOF MRA 对颅内血管系统进行稳健量化。在自动血管追踪之后，中心线位置、管腔半径和中心线偏差被联合优化，以将追踪限制在拉直弯曲平面重建 (CPR) 视图中的血管区域内。该算法在模拟血管图像和从婴儿和成人获得的重复 3D-TOF MRA 上得到验证。结果 细化算法可以可靠地估计血管半径并纠正偏离的中心线。对于噪声水平为 1 且中心线偏差为 3 的模拟血管图像，平均半径差异低于 15.3 % 以确保扫描重新扫描的可靠性。重复临床扫描的血管特征显示测量一致性显着提高，婴儿的类内相关系数 (ICC) 从 0.55 提高到 0.7，成人从 0.59 提高到 0.92。与现有方法的比较 细化算法是新颖的，因为它利用整合了来自整个动脉的信息的拉直 CPR 视图。此外，优化校正中心线位置，腔半径和中心线偏差同时进行。结论 颅内脉管系统量化使用新的细化算法进行血管追踪提高了婴儿和成人血管特征测量的可靠性。