Addo Daniel A, Kang Wendy, Prisk Gordon Kim, Tawhai Merryn H, Burrowes Kelly Suzzane
Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
Departments of Medicine and Radiology, University of California, San Diego, La Jolla, California.
Physiol Rep. 2019 Jun;7(11):e14077. doi: 10.14814/phy2.14077.
Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is an imaging methodology that uses blood as an endogenous contrast agent to quantify flow. One limitation of this method of capillary blood quantification when applied in the lung is the contribution of signals from non-capillary blood. Intensity thresholding is one approach that has been proposed for minimizing the non-capillary blood signal. This method has been tested in previous in silico modeling studies; however, it has only been tested under a restricted set of physiological conditions (supine posture and a cardiac output of 5 L/min). This study presents an in silico approach that extends previous intensity thresholding analysis to estimate the optimal "per-slice" intensity threshold value using the individual components of the simulated ASL signal (signal arising independently from capillary blood as well as pulmonary arterial and pulmonary venous blood). The aim of this study was to assess whether the threshold value should vary with slice location, posture, or cardiac output. We applied an in silico modeling approach to predict the blood flow distribution and the corresponding ASL quantification of pulmonary perfusion in multiple sagittal imaging slices. There was a significant increase in ASL signal and heterogeneity (COV = 0.90 to COV = 1.65) of ASL signals when slice location changed from lateral to medial. Heterogeneity of the ASL signal within a slice was significantly lower (P = 0.03) in prone (COV = 1.08) compared to in the supine posture (COV = 1.17). Increasing stroke volume resulted in an increase in ASL signal and conversely an increase in heart rate resulted in a decrease in ASL signal. However, when cardiac output was increased via an increase in both stroke volume and heart rate, ASL signal remained relatively constant. Despite these differences, we conclude that a threshold value of 35% provides optimal removal of large vessel signal independent of slice location, posture, and cardiac output.
动脉自旋标记（ASL）磁共振成像（MRI）是一种利用血液作为内源性对比剂来量化血流的成像方法。当这种毛细血管血量化方法应用于肺部时，一个局限性是来自非毛细血管血的信号贡献。强度阈值化是一种被提出用于最小化非毛细血管血信号的方法。该方法已在先前的计算机模拟研究中进行了测试；然而，它仅在一组受限的生理条件（仰卧姿势和心输出量为5升/分钟）下进行了测试。本研究提出了一种计算机模拟方法，该方法扩展了先前的强度阈值化分析，以使用模拟的ASL信号的各个成分（独立于毛细血管血以及肺动脉血和肺静脉血产生的信号）来估计最佳的“每层”强度阈值。本研究的目的是评估阈值是否应随切片位置、姿势或心输出量而变化。我们应用计算机模拟方法来预测多个矢状位成像切片中的血流分布以及相应的肺灌注ASL量化。当切片位置从外侧变为内侧时，ASL信号和ASL信号的异质性（COV = 0.90至COV = 1.65）显著增加。与仰卧姿势（COV = 1.17）相比，俯卧位时切片内ASL信号的异质性显著更低（P = 0.03）（COV = 1.08）。增加 stroke volume 会导致ASL信号增加，相反，增加心率会导致ASL信号降低。然而，当通过同时增加 stroke volume 和心率来增加心输出量时，ASL信号保持相对恒定。尽管存在这些差异，我们得出结论，35%的阈值可提供与切片位置、姿势和心输出量无关的大血管信号的最佳去除效果。
