Artery Research

Volume 24, Issue C, December 2018, Pages 76 - 76

4.5 CARDIAC OUTPUT ESTIMATION FROM BEAT-TO-BEAT RADIAL PRESSURE AND PULSE WAVE VELOCITY: A MODEL-BASED STUDY

Authors
Vasiliki Bikia1, Stamatia Pagoulatou1, Theodore G. Papaioannou2, Nikolaos Stergiopulos1
1Laboratory of Hemodynamics and Cardiovascular Technology, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
2Biomedical Engineering Unit, 1st Department of Cardiology, “Hippokration” Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
Available Online 4 December 2018.
DOI
10.1016/j.artres.2018.10.044How to use a DOI?
Abstract

Background: Cardiac output (CO) monitoring remains a salient challenge. The state-of-the-art is based on generalized transfer functions and parameter estimations from pooled clinical data, which do not necessarily reflect the state of the cardiovascular system in a patient-specific way. Here, we introduce a patient-specific approach to estimate CO from sequential radial pressure measurements and carotid-to-femoral pulse wave velocity (cf-PWV). We do so by effectively tuning a generalized mathematical model of the cardiovascular system (1).

Methods: Initially, the method uses the measured cf-PWV to estimate arterial compliance. We consequently determine aortic flow from beat-to-beat radial pressure measurements based on the assumption of a fairly constant total peripheral resistance (TPR) over several heartbeats (2). Concretely, we developed an algorithm which, starting from an initial flow, employs a gradient-based optimization process (3) to calculate TPR at each beat. This TPR value is subsequently used as input for a new flow approximation. The process is repeated until convergence is reached. To assess the accuracy of the method, we implemented the algorithm on in vivo anonymized data from n=15 subjects (4) and compared the method-derived CO to the measured ones.

Results: Our results demonstrated that precise estimates of CO were yielded, with a RMSE of 0.38 L/min (Fig. 1). Small variance in arterial compliance tuning did not show to significantly undermine the accuracy of the CO predictions.

Conclusions: The in vivo validation allows us to conclude that our novel method accurately estimates CO in a patient-specific way. Therefore, the technique may potentially be employed for noninvasive CO monitoring in the clinical setting.

Open Access
This is an open access article distributed under the CC BY-NC license.

References

1.P Reymond, F Merenda, F Perren, D Rüfenacht, and N Stergiopulos, Validation of a one-dimensional model of the systemic arterial tree, Am J Physiol Heart Circ Physiol., Vol. 297, No. 1, Jul 2009, pp. H208-222.
2.KH Wesseling, JR Jansen, JJ Settels, and JJ Schreuder, Computation of aortic flow from pressure in humans using a nonlinear, three-element model, Journal of Applied Physiology, Vol. 74, No. 5, May 1993, pp. 2566-73.
3.S Pagoulatou and N Stergiopulos, Estimating Left Ventricular Elastance from Aortic Flow Waveform, Ventricular Ejection Fraction, and Brachial Pressure: An In Silico Study. ABME-D-17-006793. (Pending for publication)
4.TG Papaioannou, D Soulis, O Vardoulis, A Protogerou, PP Sfikakis, N Stergiopulos, et al., First in vivo application and evaluation of a novel method for non-invasive estimation of cardiac output, Med Eng Phys., Vol. 36, No. 10, Oct 2014, pp. 1352-7.
Journal
Artery Research
Volume-Issue
24 - C
Pages
76 - 76
Publication Date
2018/12/04
ISSN (Online)
1876-4401
ISSN (Print)
1872-9312
DOI
10.1016/j.artres.2018.10.044How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Vasiliki Bikia
AU  - Stamatia Pagoulatou
AU  - Theodore G. Papaioannou
AU  - Nikolaos Stergiopulos
PY  - 2018
DA  - 2018/12/04
TI  - 4.5 CARDIAC OUTPUT ESTIMATION FROM BEAT-TO-BEAT RADIAL PRESSURE AND PULSE WAVE VELOCITY: A MODEL-BASED STUDY
JO  - Artery Research
SP  - 76
EP  - 76
VL  - 24
IS  - C
SN  - 1876-4401
UR  - https://doi.org/10.1016/j.artres.2018.10.044
DO  - 10.1016/j.artres.2018.10.044
ID  - Bikia2018
ER  -