Poleszczuk Jan, Debowska Malgorzata, Dabrowski Wojciech, Wojcik-Zaluska Alicja, Zaluska Wojciech, Waniewski Jacek
Department for Mathematical Modeling of Physiological Processes, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland.
Department of Anesthesiology and Intensive Therapy, Medical University of Lublin, Lublin, Poland.
PLoS One. 2018 Jan 11;13(1):e0190972. doi: 10.1371/journal.pone.0190972. eCollection 2018.
Cardiovascular diseases are the leading cause of death worldwide. Pulse wave analysis (PWA) technique, which reconstructs and analyses aortic pressure waveform based on non-invasive peripheral pressure recording, became an important bioassay for cardiovascular assessment in a general population. The aim of our study was to establish a pulse wave propagation modeling framework capable of matching clinical PWA data from healthy individuals on a per-subject basis. Radial pressure profiles from 20 healthy individuals (10 males, 10 females), with mean age of 42 ± 10 years, were recorded using applanation tonometry (SphygmoCor, AtCor Medical, Australia) and used to estimate subject-specific parameters of mathematical model of blood flow in the system of fifty-five arteries. The model was able to describe recorded pressure profiles with high accuracy (mean absolute percentage error of 1.87 ± 0.75%) when estimating only 6 parameters for each subject. Cardiac output (CO) and stroke volume (SV) have been correctly identified by the model as lower in females than males (CO of 3.57 ± 0.54 vs. 4.18 ± 0.72 L/min with p-value < 0.05; SV of 49.5 ± 10.1 vs. 64.2 ± 16.8 ml with p-value = 0.076). Moreover, the model identified age related changes in the heart function, i.e. that the cardiac output at rest is maintained with age (r = 0.23; p-value = 0.32) despite the decreasing heart rate (r = -0.49; p-value < 0.05), because of the increase in stroke volume (r = 0.46; p-value < 0.05). Central PWA indices derived from recorded waveforms strongly correlated with those obtained using corresponding model-predicted radial waves (r > 0.99 and r > 0.97 for systolic (SP) and diastolic (DP) pressures, respectively; r > 0.77 for augmentation index (AI); all p-values < 0.01). Model-predicted central waveforms, however, had higher SP than those reconstructed by PWA using recorded radial waves (5.6 ± 3.3 mmHg on average). From all estimated subject-specific parameters only the time to the peak of heart ejection profile correlated with clinically measured AI. Our study suggests that the proposed model may serve as a tool to computationally investigate virtual patient scenarios mimicking different cardiovascular abnormalities. Such a framework can augment our understanding and help with the interpretation of PWA results.
心血管疾病是全球主要的死亡原因。脉搏波分析（PWA）技术基于无创外周压力记录来重建和分析主动脉压力波形，已成为普通人群心血管评估的一项重要生物检测方法。我们研究的目的是建立一个脉搏波传播建模框架，能够在个体基础上匹配健康个体的临床PWA数据。使用压平式眼压计（SphygmoCor，AtCor Medical，澳大利亚）记录了20名健康个体（10名男性，10名女性）的桡动脉压力曲线，平均年龄为42±10岁，并用于估计五十五动脉系统中血流数学模型的个体特异性参数。该模型在为每个个体仅估计6个参数时，能够以高精度描述记录的压力曲线（平均绝对百分比误差为1.87±0.75%）。该模型正确识别出女性的心输出量（CO）和每搏输出量（SV）低于男性（CO分别为3.57±0.54与4.18±0.72L/min，p值<0.05；SV分别为49.5±10.1与64.2±16.8ml，p值=0.076）。此外，该模型识别出了与年龄相关的心脏功能变化，即尽管心率下降（r=-0.49；p值<0.05），但静息时的心输出量随年龄保持稳定（r=0.23；p值=0.32），这是由于每搏输出量增加（r=0.46；p值<0.05）。从记录波形得出的中心PWA指标与使用相应模型预测的桡动脉波形得出的指标高度相关（收缩压（SP）和舒张压（DP）分别为r>0.99和r>0.97；增强指数（AI）为r>0.77；所有p值<0.01）。然而，模型预测的中心波形的SP高于使用记录的桡动脉波形通过PWA重建的波形（平均高5.6±3.3mmHg）。在所有估计的个体特异性参数中，只有心脏射血曲线峰值时间与临床测量的AI相关。我们的研究表明，所提出的模型可作为一种工具，用于通过计算研究模拟不同心血管异常情况的虚拟患者场景。这样一个框架可以增进我们的理解，并有助于解释PWA结果。
