Research Papers

Determinant Factors for Arterial Hemodynamics in Hypertension: Theoretical Insights From a Computational Model-Based Study

[+] Author and Article Information
Fuyou Liang

School of Naval Architecture, Ocean
and Civil Engineering,
Shanghai Jiao Tong University,
800 Dongchuan Road,
Shanghai 200240, China;
Collaborative Innovation Center for Advanced
Ship and Deep-Sea Exploration (CISSE),
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: fuyouliang@sjtu.edu.cn

Debao Guan

School of Naval Architecture, Ocean and Civil
Shanghai Jiao Tong University,
Shanghai 200240, China

Jordi Alastruey

School of Biomedical Engineering
and Imaging Sciences,
King's College London, St Thomas' Hospital,
London SE1 7EH, UK

1Corresponding author.

Manuscript received May 9, 2017; final manuscript received November 1, 2017; published online January 17, 2018. Assoc. Editor: C. Alberto Figueroa.

J Biomech Eng 140(3), 031006 (Jan 17, 2018) (14 pages) Paper No: BIO-17-1202; doi: 10.1115/1.4038430 History: Received May 09, 2017; Revised November 01, 2017

Hypertension is a well-documented predictive factor for cardiovascular events. Clinical studies have extensively demonstrated the differential hemodynamic consequences of various antihypertensive drugs, but failed to clearly elucidate the underlying mechanisms due to the difficulty in performing a quantitative deterministic analysis based on clinical data that carry confounding information stemming from interpatient differences and the nonlinearity of cardiovascular hemodynamics. In the present study, a multiscale model of the cardiovascular system was developed to quantitatively investigate the relationships between hemodynamic variables and cardiovascular properties under hypertensive conditions, aiming to establish a theoretical basis for assisting in the interpretation of clinical observations or optimization of therapy. Results demonstrated that heart period, central arterial stiffness, and arteriolar radius were the major determinant factors for blood pressures and flow pulsatility indices both in large arteries and in the microcirculation. These factors differed in the degree and the way in which they affect hemodynamic variables due to their differential effects on wave reflections in the vascular system. In particular, it was found that the hemodynamic effects of varying arteriolar radius were considerably influenced by the state of central arterial stiffness, and vice versa, which implied the potential of optimizing antihypertensive treatment by selecting proper drugs based on patient-specific cardiovascular conditions. When analyzed in relation to clinical observations, the simulated results provided mechanistic explanations for the beneficial pressure-lowering effects of vasodilators as compared to β-blockers, and highlighted the significance of monitoring and normalizing arterial stiffness in the treatment of hypertension.

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Fig. 1

Schematic description of multiscale modeling of the cardiovascular system. The fifty-five largest arteries are represented by a 1D model and distal arteries/arterioles are mimicked by ST models. The 1D model is coupled with the ST models at the distal ends of peripheral arteries and further integrated into a lumped-parameter (0D) model of the remaining cardiovascular portions. It is noted that blood flows through the ST models are assumed to converge respectively to the upper-body and lower-body capillary beds to simplify the model configuration. More details of the 1D and 0D models have been given in Ref. [28].

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Fig. 2

Flowchart of the numerical scheme employed to couple the 0D, 1D and ST models. Notations: nΔt, current time-step; (n + 1)Δt, next time-step; k, iteration step; w1,j, forward-traveling Riemann invariant at the distal end of the jth peripheral artery; w2, backward-traveling Riemann invariant at the root of the ascending aorta. See the text for further details of notations.

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Fig. 3

Model-simulated pressure wave variations from the heart toward the capillary bed along the vascular system of the left arm (normotensive versus hypertensive). Locations: A—left ventricle; B—middle of the ascending aorta; C—middle of the brachial artery; D—distal end of the radial artery (i.e., inlet of the ST model); E—distal end of arterioles (i.e., outlet of the ST model or inlet of the capillary bed); F—distal end of the capillary bed.

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Fig. 4

Changes of hemodynamic variables with variations in cardiac parameters ((a), heart period; (b), peak systolic elastance of the left ventricle). Abbreviations: MP, aortic MP; SP, aortic SP; PP, aortic PP, AR, PP amplification ratio from the aorta to the branchial artery; CI, cardiac index. The reference values of MP, SP, PP, AR and CI are 123.38 mmHg, 152.33 mmHg, 58.20 mmHg, 1.23 and 2.77 l/min/m2, respectively. The abbreviations and reference values will be used throughout the paper unless stated elsewhere.

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Fig. 5

Changes of hemodynamic variables with variations in macrovascular parameters ((a), stiffness of central arteries and (b), stiffness of peripheral arteries)

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Fig. 6

Changes of hemodynamic variables with variations in microvascular parameters ((a), radius of distal arteries/arterioles and (b), media-to-lumen ratio of distal arteries/arterioles)

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Fig. 7

Hemodynamic changes induced by ±20% variations in model parameters relative to the reference values ((a), parameter value +20% and (b), parameter value −20%)

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Fig. 8

±20% parameter variations-induced changes in the forward-traveling (Pf) and backward-traveling (Pb) components of PP, the modulus of input impedance (Zin) and the modulus of wave reflection coefficient (Γ) in the ascending aorta (from left to right). See the caption of Table 2 for the notations of model parameters. Herein, the subscript “0” denotes the reference state of each parameter. Note that Pf and Pb have been calculated based solely on the pulsatile component of the pressure wave to highlight the characteristics of wave propagation and reflection.

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Fig. 9

Changes in flow pulsatility indices along the vascular system induced by ±20% variations in model parameters relative to the reference values ((a), parameter value +20%; (b), parameter value −20%). The distal arterial flow pulsatility index (PI) is monitored in the distal segment of the left radial artery, and the capillary flow PI is calculated based on the simulated flow wave through the upper-body capillary bed. The flow pulsatility indices computed under the reference conditions are 6.11, 3.74, 2.28 and 0.13 in the aorta, brachial artery, distal artery and capillary bed, respectively.

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Fig. 10

Surface plots of hemodynamic changes induced by combined variations in central arterial stiffness and arteriolar radius: (a) aortic mean pressure (MP), (b) aortic systolic pressure (SP), (c) aortic pulse pressure (PP), and (d) aortic-to-brachial pulse pressure amplification ratio (AR). The numbers in the white boxes denote the amounts of hemodynamic changes when arteriolar radius is changed from the −10% state to the +20% state (relative to the reference value).

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Fig. 11

Changes of pre-capillary pressure with variations in model parameters ((a) PP and (b) MP)



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