Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan.
Master's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan.
Sci Rep. 2021 Feb 3;11(1):2920. doi: 10.1038/s41598-021-82300-6.
The purpose of this study was to investigate the influence of arterial input function (AIF) selection on the quantification of vertebral perfusion using axial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, axial DCE-MRI was performed on 2 vertebrae in each of eight healthy volunteers (mean age, 36.9 years; 5 men) using a 1.5-T scanner. The pharmacokinetic parameters K, v, and v, derived using a Tofts model on axial DCE-MRI of the lumbar vertebrae, were evaluated using various AIFs: the population-based aortic AIF (AIF_PA), a patient-specific aortic AIF (AIF_A) and a patient-specific segmental arterial AIF (AIF_SA). Additionally, peaks and delay times were changed to simulate the effects of various AIFs on the calculation of perfusion parameters. Nonparametric analyses including the Wilcoxon signed rank test and the Kruskal-Wallis test with a Dunn-Bonferroni post hoc analysis were performed. In simulation, K and v increased as the peak in the AIF decreased, but v increased when delay time in the AIF increased. In humans, the estimated K and v were significantly smaller using AIF_A compared to AIF_SA no matter the computation style (pixel-wise or region-of-interest based). Both these perfusion parameters were significantly greater using AIF_SA compared to AIF_A.
本研究旨在探讨在使用轴向动态对比增强磁共振成像(DCE-MRI)定量椎体灌注时,动脉输入函数(AIF)选择对其的影响。在这项研究中,使用 1.5T 扫描仪对 8 名健康志愿者(平均年龄 36.9 岁,5 名男性)的每 2 个椎体进行了轴向 DCE-MRI。使用 Tofts 模型评估了来自腰椎轴向 DCE-MRI 的药代动力学参数 K、v 和 v,采用了多种 AIF:基于人群的主动脉 AIF(AIF_PA)、患者特异性主动脉 AIF(AIF_A)和患者特异性节段性动脉 AIF(AIF_SA)。此外,还改变了峰值和延迟时间,以模拟各种 AIF 对灌注参数计算的影响。进行了非参数分析,包括 Wilcoxon 符号秩检验和 Kruskal-Wallis 检验,以及 Dunn-Bonferroni 事后分析。在模拟中,随着 AIF 峰值的降低,K 和 v 增加,但当 AIF 中的延迟时间增加时,v 增加。在人体中,无论计算方式(像素级或基于感兴趣区域的方式)如何,使用 AIF_A 估计的 K 和 v 明显小于 AIF_SA。与 AIF_A 相比,使用 AIF_SA 时这两个灌注参数均明显更高。