In Silico Validation of Non-Invasive Arterial Compliance Estimation and Potential Determinants of its Variability

Arterial compliance (AC) is an important cardiovascular parameter characterizing mechanical properties of arteries. AC is significantly influenced by arterial wall structure and vasomotion, and it markedly influences cardiac load. A new method, based on a two-element Windkessel model, has been recently proposed for estimating AC as the ratio of the time constant T of the diastolic blood pressure decay and peripheral vascular resistance derived from clinically available stroke volume measurements and selected peripheral blood pressure parameters which are less prone to peripheral distortions. The aim of this study was to validate AC estimation using a virtual population generated by in silico model of the systemic arterial tree. In the second part of study, we analysed causal coupling between AC oscillations and variability of its potential determinants - systolic blood pressure and heart rate in healthy young human subjects. The pool of virtual subjects (n=3818) represented an extensive AC distribution. AC was estimated from the peripheral blood pressure curve and by the standard method from the aortic blood pressure curve. The proposed method slightly overestimated AC set in the model but both ACs were strongly correlated (r=0.94, p<0.001). In real data, we observed that AC dynamics was coupled with basic cardiovascular parameters variability independently of the autonomic nervous system state. In silico analysis suggests that AC can be reliably estimated by noninvasive method. The analysis of short-term AC variability together with its determinants could improve our understanding of factors involved in AC dynamics potentially improving assessment of AC changes associated with atherosclerosis process. Key words Arterial compliance, Cardiovascular model, Arterial blood pressure, Causal analysis, Volume-clamp photoplethysmography.