Department of Aerospace & Mechanical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA; Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA; Advanced Imaging and Spectroscopy Center, Huntington Medical Research Institutes, Pasadena, CA 91105, USA.
Advanced Imaging and Spectroscopy Center, Huntington Medical Research Institutes, Pasadena, CA 91105, USA.
Magn Reson Imaging. 2020 Jun;69:8-15. doi: 10.1016/j.mri.2020.02.013. Epub 2020 Feb 24.
MRI assessment of aortic pulse wave velocity (PWV) helps predict the risk of vascular events, but the recommended phase contrast sampling rate is faster than what is utilized in most clinical sequences. There are many existing MRI databases obtained for assessment of cardiac output using lower temporal frequency sampling where information might be obtained about aortic stiffness (PWV). In this work, we sought to evaluate whether the Group Delay (GD) method can generate a reproducible measure of stiffness and describe expected age-related stiffening of the aortic arch using lower sampling rates in standard clinical sequences.
Phase contrast (PC) MRI was obtained on the ascending and descending aortic arch in a heterogeneous adult cohort (n = 23; 9 women) spanning over a wide range of ages (ages 24-89, mean 49.4 ± 18.4). Data was collected with standard cardiac MRI protocols for cardiac output evaluation (repetition time = 7.8 ms, views-per-segment = 4, encoding velocity = 200 cm/s). Pulse wave transit times (TT) were computed using the GD method, two other validated automated approaches (cross correlation TT Algorithm by Gaddum and Segment by Medviso), and the manual tangent method. Pressure waveforms from tonometry and flow waveforms from PC MRI were used to assess wave reflections.
Group Delay and TT-Algorithm showed significant and high retest reproducibility (r = 0.86 for both) as well as high PWV correlation with age (r = 0.93, P-value < 0.00005 and r = 0.96, P-value < 0.00005 respectively) and with each other (r = 0.94, P-value < 0.00001, RMSE = 0.94 m/s). Arbitrary altering of the image acquisition trigger in the GD method introduced error of 10%-13%, but the TT-algorithm error range was 11%-25%.
Group Delay enables reproducible assessment of transit time to derive PWV from low temporal resolution clinical cardiac MRI sequences that can also identify age-related stiffening.
MRI 评估主动脉脉搏波速度（PWV）有助于预测血管事件的风险，但推荐的相位对比采样率比大多数临床序列中使用的更快。有许多现有的 MRI 数据库是用于评估使用较低时间频率采样的心输出量，其中可能会获得关于主动脉僵硬度（PWV）的信息。在这项工作中，我们试图评估 Group Delay（GD）方法是否可以生成可重复的僵硬度测量值，并使用标准临床序列中的较低采样率来描述预期的主动脉弓随年龄增长而变硬的情况。
在一个涵盖广泛年龄范围（年龄 24-89 岁，平均 49.4±18.4 岁）的异质性成年队列中，对升主动脉和降主动脉弓进行了相位对比（PC）MRI 检查（n=23；9 名女性）。数据是使用标准的心脏 MRI 协议采集的，用于评估心输出量（重复时间=7.8ms，分段视图数=4，编码速度=200cm/s）。使用 GD 方法、另两种经过验证的自动方法（Gaddum 的交叉相关 TT 算法和 Medviso 的分段）和手动切线法计算脉搏波传递时间（TT）。使用血压计的压力波形和 PC MRI 的流量波形来评估波反射。
GD 方法和 TT-Algorithm 显示出显著的和高度可重复的复测相关性（两者的 r 值均为 0.86），并且与年龄（r 值分别为 0.93，P 值<0.00005 和 r 值为 0.96，P 值<0.00005）和彼此之间（r 值为 0.94，P 值<0.00001，RMSE=0.94m/s）的相关性都很高。GD 方法中图像采集触发的任意改变会引入 10%-13%的误差，但 TT-algorithm 的误差范围为 11%-25%。
GD 方法可以从低时间分辨率的临床心脏 MRI 序列中重复评估传输时间，从而得出 PWV，并且可以识别与年龄相关的僵硬度变化。
