Non-invasive assessment of stroke volume and cardiovascular parameters based on peripheral pressure waveform

• Published in: PLoS computational biology Vol. 20; no. 4; p. e1012013
• Main Authors: Wołos, Kamil, Pstras, Leszek, Debowska, Malgorzata, Dabrowski, Wojciech, Siwicka-Gieroba, Dorota, Poleszczuk, Jan
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.04.2024; Public Library of Science (PLoS)
• Subjects: Analysis; Biology and Life Sciences; Blood flow; Blood pressure; Calibration; Cardiovascular diseases; Cardiovascular system; Chronic illnesses; Coronary vessels; Customization; Diabetes; Elastic waves; Flow velocity; Heart failure; Heart function; Hemodialysis; Hemodynamics; Hypertension; Kidney diseases; Mathematical models; Measurement; Measuring instruments; Medicine and Health Sciences; Optimization; Parameters; Patients; Physical Sciences; Propagation; Pulse propagation; Stroke (Disease); Stroke volume; Systolic pressure; Veins & arteries; Ventricle; Wave propagation; Waveforms; Poland
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1012013

Cardiovascular diseases are the leading cause of death globally, making the development of non-invasive and simple-to-use tools that bring insights into the state of the cardiovascular system of utmost importance. We investigated the possibility of using peripheral pulse wave recordings to estimate stroke volume (SV) and subject-specific parameters describing the selected properties of the cardiovascular system. Peripheral pressure waveforms were recorded in the radial artery using applanation tonometry (SphygmoCor) in 35 hemodialysis (HD) patients and 14 healthy subjects. The pressure waveforms were then used to estimate subject-specific parameters of a mathematical model of pulse wave propagation coupled with the elastance-based model of the left ventricle. Bioimpedance cardiography measurements (PhysioFlow) were performed to validate the model-estimated SV. Mean absolute percentage error between the simulated and measured pressure waveforms was 4.0% and 2.8% for the HD and control group, respectively. We obtained a moderate correlation between the model-estimated and bioimpedance-based SV (r = 0.57, p<0.05, and r = 0.58, p<0.001, for the control group and HD patients, respectively). We also observed a correlation between the estimated end-systolic elastance of the left ventricle and the peripheral systolic pressure in both HD patients (r = 0.84, p<0.001) and the control group (r = 0.70, p<0.01). These preliminary results suggest that, after additional validation and possibly further refinement to increase accuracy, the proposed methodology could support non-invasive assessment of stroke volume and selected heart function parameters and vascular properties. Importantly, the proposed method could be potentially implemented in the existing devices measuring peripheral pressure waveforms.