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不同的储层波模型舒张压拟合技术对波强分析的影响。

Impact of varying diastolic pressure fitting technique for the reservoir-wave model on wave intensity analysis.

机构信息

Biomedical Engineering Research Group, Brunel University London, UK.

Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, UK.

出版信息

Proc Inst Mech Eng H. 2020 Nov;234(11):1300-1311. doi: 10.1177/0954411920959957. Epub 2020 Sep 30.

DOI:10.1177/0954411920959957
PMID:32996433
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7675780/
Abstract

The reservoir-wave model assumes that the measured arterial pressure is made of two components: reservoir and excess. The effect of the reservoir volume should be excluded to quantify the effects of forward and backward traveling waves on blood pressure. Whilst the validity of the reservoir-wave concept is still debated, there is no consensus on the best fitting method for the calculation of the reservoir pressure waveform. Therefore, the aim of this parametric study is to examine the effects of varying the fitting technique on the calculation of reservoir and excess components of pressure and velocity waveforms. Common carotid pressure and flow velocity were measured using applanation tonometry and doppler ultrasound, respectively, in 1037 healthy humans collected randomly from the Asklepios population, aged 35 to 55 years old. Different fitting techniques to the diastolic decay of the measured arterial pressure were used to determine the asymptotic pressure decay, which in turn was used to determine the reservoir pressure waveform. The corresponding wave speed was determined using the PU-loop method, and wave intensity parameters were calculated and compared. Different fitting methods resulted in significant changes in the shape of the reservoir pressure waveform; however, its peak and time integral remained constant in this study. Although peak and integral of excess pressure, velocity components and wave intensity changed significantly with changing the diastolic decay fitting method, wave speed was not substantially modified. We conclude that wave speed, peak reservoir pressure and its time integral are independent of the diastolic pressure decay fitting techniques examined in this study. Therefore, these parameters are considered more reliable diagnostic indicators than excess pressure and velocity which are more sensitive to fitting techniques.

摘要

储层波模型假设测量的动脉压由两部分组成

储层和剩余部分。为了量化前向和后向传播波对血压的影响,应该排除储层体积的影响。虽然储层波概念的有效性仍存在争议,但对于计算储层压力波形的最佳拟合方法尚未达成共识。因此,本参数研究的目的是检查不同拟合技术对压力和速度波形的储层和剩余分量计算的影响。使用平板测压法和多普勒超声分别测量了 1037 名随机从 Asklepios 人群中收集的年龄在 35 至 55 岁的健康人颈总动脉的压力和流速。使用不同的拟合技术对测量动脉压的舒张期衰减进行拟合,以确定渐近压力衰减,进而确定储层压力波形。使用 PU 环法确定相应的波速,并计算和比较波强参数。不同的拟合方法导致储层压力波形的形状发生显著变化;然而,在本研究中,其峰值和时间积分保持不变。尽管过量压力、速度分量和波强的峰值和积分随舒张期衰减拟合方法的变化而显著变化,但波速并没有实质性的改变。我们得出结论,波速、峰值储层压力及其时间积分与本研究中检查的舒张期压力衰减拟合技术无关。因此,这些参数被认为比更敏感于拟合技术的过量压力和速度更可靠的诊断指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/e4b15ded4664/10.1177_0954411920959957-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/fc7912874b70/10.1177_0954411920959957-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/a82c536336b1/10.1177_0954411920959957-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/984c483e9d93/10.1177_0954411920959957-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/a79c871b24fc/10.1177_0954411920959957-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/a15d169a5a27/10.1177_0954411920959957-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/e1f15505c9b2/10.1177_0954411920959957-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/b0b0e8ccccc2/10.1177_0954411920959957-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/2d28f536b503/10.1177_0954411920959957-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/e4b15ded4664/10.1177_0954411920959957-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/fc7912874b70/10.1177_0954411920959957-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/a82c536336b1/10.1177_0954411920959957-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/984c483e9d93/10.1177_0954411920959957-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/a79c871b24fc/10.1177_0954411920959957-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/a15d169a5a27/10.1177_0954411920959957-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/e1f15505c9b2/10.1177_0954411920959957-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/b0b0e8ccccc2/10.1177_0954411920959957-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/2d28f536b503/10.1177_0954411920959957-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7ed/7675780/e4b15ded4664/10.1177_0954411920959957-fig9.jpg

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