Abstracts

Minimally invasive, patient specific, beat-by-beat estimation of left ventricular time varying elastance

by JG Chase




Institution: University of Canterbury
Department:
Year: 2017
Keywords: Humans; Electrocardiography; Feasibility Studies; Electric Capacitance; Heart Rate; Systole; Ventricular Function, Left; Time Factors; Signal Processing, Computer-Assisted; Male; Arterial Pressure; Patient-Specific Modeling; Time varying elastance; Cardiovascular system; Minimally invasive; Field of Research::11 - Medical and Health Sciences::1102 - Cardiovascular Medicine and Haematology::110201 - Cardiology (incl. Cardiovascular Diseases); Field of Research::09 - Engineering::0903 - Biomedical Engineering; Field of Research::09 - Engineering::0913 - Mechanical Engineering::091307 - Numerical Modelling and Mechanical Characterisation
Posted: 02/01/2018
Record ID: 2198201
Full text PDF: http://hdl.handle.net/10092/13467


Abstract

Background: The aim of this paper was to establish a minimally invasive method for deriving the left ventricular time varying elastance (TVE) curve beat-by-beat, the monitoring of which's inter-beat evolution could add significant new data and insight to improve diagnosis and treatment. The method developed uses the clinically available inputs of aortic pressure, heart rate and baseline end-systolic volume (via echocardiography) to determine the outputs of left ventricular pressure, volume and dead space volume, and thus the TVE curve. This approach avoids directly assuming the shape of the TVE curve, allowing more effective capture of intra- and inter-patient variability. Results: The resulting TVE curve was experimentally validated against the TVE curve as derived from experimentally measured left ventricular pressure and volume in animal models, a data set encompassing 46,318 heartbeats across 5 Pitrain pigs. This simulated TVE curve was able to effectively approximate the measured TVE curve, with an overall median absolute error of 11.4% and overall median signed error of -2.5%. Conclusions: The use of clinically available inputs means there is potential for real-time implementation of the method at the patient bedside. Thus the method could be used to provide additional, patient specific information on intra- and inter-beat variation in heart function.