Department of Engineering Mechanics, School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, China.
Department of Ultrasound, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Comput Methods Programs Biomed. 2024 Dec;257:108450. doi: 10.1016/j.cmpb.2024.108450. Epub 2024 Sep 30.
The higher clinical significance of central aortic blood pressure (CABP) compared to peripheral blood pressures has been extensively demonstrated. Accordingly, many methods for noninvasively estimating CABP have been proposed. However, there still lacks a systematic comparison of existing methods, especially in terms of how they differ in the ability to tolerate individual differences or measurement errors. The present study was designed to address this gap.
A large-scale 'virtual subject' dataset (n = 600) was created using a computational model of the cardiovascular system, and applied to examine several classical CABP estimation methods, including the direct method, generalized transfer function (GTF) method, n-point moving average (NPMA) method, second systolic pressure of periphery (SBP2) method, physical model-based wave analysis (MBWA) method, and suprasystolic cuff-based waveform reconstruction (SCWR) method. The errors of CABP estimation were analyzed and compared among methods with respect to the magnitude/distribution, correlations with physiological/hemodynamic factors, and sensitivities to noninvasive measurement errors.
The errors of CABP estimation exhibited evident inter-method differences in terms of the mean and standard deviation (SD). Relatively, the estimation errors of the methods adopting pre-trained algorithms (i.e., the GTF and SCWR methods) were overall smaller and less sensitive to variations in physiological/hemodynamic conditions and random errors in noninvasive measurement of brachial arterial blood pressure (used for calibrating peripheral pulse wave). The performances of all the methods worsened following the introduction of random errors to peripheral pulse wave (used for deriving CABP), as characterized by the enlarged SD and/or increased mean of the estimation errors. Notably, the GTF and SCWR methods did not exhibit a better capability of tolerating pulse wave errors in comparison with other methods.
Classical noninvasive methods for estimating CABP were found to differ considerably in both the accuracy and error source, which provided theoretical evidence for understanding the specific advantages and disadvantages of each method. Knowledge about the method-specific error source and sensitivities of errors to different physiological/hemodynamic factors may contribute as theoretical references for interpreting clinical observations and exploring factors underlying large estimation errors, or provide guidance for optimizing existing methods or developing new methods.
与外周血压相比，中心主动脉血压（CABP）具有更高的临床意义，这一点已得到广泛证明。因此，已经提出了许多非侵入性估计 CABP 的方法。然而，目前仍然缺乏对现有方法的系统比较，特别是在它们在耐受个体差异或测量误差方面的能力方面。本研究旨在解决这一差距。
使用心血管系统的计算模型创建了一个大规模的“虚拟主体”数据集（n=600），并应用于检查几种经典的 CABP 估计方法，包括直接法、广义传递函数（GTF）法、n 点移动平均（NPMA）法、外周第二收缩压（SBP2）法、基于物理模型的波分析（MBWA）法和基于超收缩袖带的波形重建（SCWR）法。分析并比较了方法之间 CABP 估计的误差，包括幅度/分布、与生理/血流动力学因素的相关性以及对非侵入性测量误差的敏感性。
CABP 估计的误差在均值和标准差（SD）方面表现出明显的方法间差异。相对而言，采用预训练算法的方法（即 GTF 和 SCWR 方法）的估计误差总体上较小，并且对生理/血流动力学条件的变化和肱动脉血压的非侵入性测量（用于校准外周脉搏波）的随机误差不敏感。在向外周脉搏波（用于推导 CABP）引入随机误差后，所有方法的性能都恶化了，表现为估计误差的 SD 增大和/或均值增加。值得注意的是，与其他方法相比，GTF 和 SCWR 方法并没有表现出更好的耐受脉搏波误差的能力。
用于估计 CABP 的经典非侵入性方法在准确性和误差源方面存在很大差异，这为理解每种方法的具体优缺点提供了理论依据。了解方法特有的误差源以及误差对不同生理/血流动力学因素的敏感性，可以为解释临床观察结果和探讨大估计误差的潜在因素提供理论参考，或者为优化现有方法或开发新方法提供指导。
