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基于个性化4D流磁共振成像的心血管模型中的观察者和序列变异性。

Observer- and sequence variability in personalized 4D flow MRI-based cardiovascular models.

作者信息

Casas Garcia Belén, Tunedal Kajsa, Viola Federica, Cedersund Gunnar, Carlhäll Carl-Johan, Karlsson Matts, Ebbers Tino

机构信息

Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.

Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.

出版信息

Sci Rep. 2025 Jan 8;15(1):1352. doi: 10.1038/s41598-024-84390-4.

Abstract

Subject-specific parameters in lumped hemodynamic models of the cardiovascular system can be estimated using data from experimental measurements, but the parameter estimation may be hampered by the variability in the input data. In this study, we investigate the influence of inter-sequence, intra-observer, and inter-observer variability in input parameters on estimation of subject-specific model parameters using a previously developed approach for model-based analysis of data from 4D Flow MRI acquisitions and cuff pressure measurements. The investigated parameters describe left ventricular time-varying elastance and aortic compliance. Parameter reproducibility with respect to variability in the MRI input measurements was assessed in a group of ten healthy subjects. The subject-specific parameters had coefficient of variations between 2.6 and 35% in the intra- and inter-observer analysis. In comparing parameters estimated using data from the two MRI sequences, the coefficients of variation ranged between 3.3 and 41%. The diastolic time constant of the left ventricle and the compliance of the ascending aorta were the parameters with the lowest and the highest variability, respectively. In conclusion, the modeling approach allows for estimating left ventricular elastance parameters and aortic compliance from non-invasive measurements with good to moderate reproducibility concerning intra-user, inter-user, and inter-sequence variability in healthy subjects.

摘要

心血管系统集总血流动力学模型中的个体特异性参数可通过实验测量数据进行估计,但参数估计可能会受到输入数据变异性的阻碍。在本研究中,我们使用先前开发的基于模型的方法对来自4D流MRI采集和袖带压力测量的数据进行分析,研究输入参数中的序列间、观察者内和观察者间变异性对个体特异性模型参数估计的影响。所研究的参数描述左心室时变弹性和主动脉顺应性。在一组十名健康受试者中评估了MRI输入测量变异性方面的参数可重复性。在观察者内和观察者间分析中,个体特异性参数的变异系数在2.6%至35%之间。在比较使用两个MRI序列数据估计的参数时,变异系数在3.3%至41%之间。左心室舒张时间常数和升主动脉顺应性分别是变异性最低和最高的参数。总之,该建模方法能够从非侵入性测量中估计左心室弹性参数和主动脉顺应性,在健康受试者中,对于用户内、用户间和序列间变异性具有良好到中等的可重复性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/48b6/11711780/cae540e52f99/41598_2024_84390_Fig1_HTML.jpg

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