Estimating central blood pressure from aortic flow: development and assessment of algorithms

Abstract

Central blood pressure (cBP) is a highly prognostic cardiovascular (CV) risk factor whose accurate, invasive assessment is costly and carries risks to patients. We developed and assessed novel algorithms for estimating cBP from non-invasive aortic haemodynamic data and a peripheral BP measurement. These algorithms were created using three blood flow models: the 2-and-3-element Windkessel (0-D) models and a one-dimensional (1-D) model of the thoracic aorta. We tested new and existing methods for estimating CV parameters (ejection time, outflow BP, arterial resistance, compliance, pulse wave velocity, characteristic impedance) required for the cBP algorithms, using 'virtual' subjects (n=19,646) for which reference CV parameters were known exactly. We then tested the cBP algorithms using 'virtual' subjects (n=4,064), for which reference cBP were available free-of-measurement error, and clinical datasets containing invasive (n=10) and non-invasive (n=171) reference cBP waves across a wide-range of CV conditions. The 1-D algorithm outperformed the 0-D algorithms when the aortic vascular geometry was available, achieving central systolic blood pressure (cSBP) errors ≤2.1±9.7mmHg and root-mean-square-errors (RMSEs) ≤6.4±2.8mmHg against invasive reference cBP waves (n=10). When the aortic geometry was unavailable, the 3-element 0-D algorithm achieved cSBP errors ≤6.0±4.7mmHg and RMSEs ≤5.9±2.4mmHg against non-invasive reference cBP waves (n=171), outperforming the 2-element 0-D algorithm. All CV parameters were estimated with mean percentage errors ≤8.2%, except for the aortic characteristic impedance (≤13.4%), which affected the 3-element 0-D algorithm's performance. The freely-available algorithms developed in this work enable fast and accurate calculation of the cBP wave and CV parameters from ultrasound or magnetic resonance imaging data.

Arterial pulse wave propagation across stenoses and aneurysms: assessment of one-dimensional simulations against three-dimensional simulations andin vitromeasurements

“…The ensemble-averaged pressure measured by the first sensor fixed at the inlet of the aortic phantom was taken as a reference to calibrate the pressure measured by the second sensor at different positions along the phantom. Finally, the 1-D model parameters of the three-element Windkessel outflow boundary condition were calculated using the inflow boundary condition and the pressure waveform at the inlet using the algorithm described in [55].…”

Hemodynamic profiles of arterial hypertension with ambulatory blood pressure monitoring

“…In particular, central BP and central PP evaluation with our model are not reliable. Other researchers have demonstrated that a three-element Windkessel model outperforms the 2-WK model for central BP assessment [ 55 ]. In addition, an arterial model used to estimate central BP usually requires flow waves [ 56 ], which we did not use in our study.…”

Human Hypertension Blood Flow Model Using Fractional Calculus

“…Their cardiac cycle is T = 0.92 s . The second clinical dataset was obtained from data supplement publicly available at in (Mariscal-Harana et al, 2021 ). The dataset was originally used in a study about forward and backward pressure waveform morphology analysis in hypertension, (Li et al, 2017 ).…”

“…48% of the subject were on treatment and hence their blood pressure were settled to the normal values (normotensive). More details about the collection of this data such as the consent approval and the measurement tools can be fount in (Mariscal-Harana et al, 2021 ). In addition to the aortic waveforms the dataset contains extra chracteristic of the subjects such as the height, weight, measurements of systolic (SBP) and diastolic (DBP) blood pressure, cardiac output, stroke volume and heart rate.…”