Respiratory-gated electrical impedance tomography: a potential technique for quantifying stroke volume

Saaid H. Arshad; Ethan K. Murphy; Ryan J. Halter

doi:10.1117/12.2216595

29 March 2016 Respiratory-gated electrical impedance tomography: a potential technique for quantifying stroke volume

Saaid H. Arshad, Ethan K. Murphy, Ryan J. Halter

Proceedings Volume 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging; 97882D (2016) https://doi.org/10.1117/12.2216595
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Telemonitoring is becoming increasingly important as the proportion of the population living with cardiovascular disease (CVD) increases. Currently used health parameters in the suite of telemonitoring tools lack the sensitivity and specificity to accurately predict heart failure events, forcing physicians to play a reactive versus proactive role in patient care. A novel cardiac output (CO) monitoring device is proposed that leverages a custom smart phone application and a wearable electrical impedance tomography (EIT) system. The purpose of this work is to explore the potential of using respiratory-gated EIT to quantify stroke volume (SV) and assess its feasibility using real data. Simulations were carried out using the 4D XCAT model to create anatomically realistic meshes and electrical conductivity profiles representing the human thorax and the intrathoracic tissue. A single 5-second period respiration cycle with chest/lung expansion was modeled with end-diastole (ED) and end-systole (ES) heart volumes to evaluate how effective EIT-based conductivity changes represent clinically significant differences in SV. After establishing a correlation between conductivity changes and SV, the applicability of the respiratory-gated EIT was refined using data from the PhysioNet database to estimate the number of useful end-diastole (ED) and end-systole (ES) heart events attained over a 3.3 minute period. The area associated with conductivity changes was found to correlate to SV with a correlation coefficient of 0.92. A window of 12.5% around peak exhalation was found to be the optimal phase of the respiratory cycle from which to record EIT data. Within this window, ~47 useable ED and ES were found with a standard deviation of 28 using 3.3 minutes of data for 20 patients.

Citation Download Citation

Saaid H. Arshad, Ethan K. Murphy, and Ryan J. Halter "Respiratory-gated electrical impedance tomography: a potential technique for quantifying stroke volume", Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97882D (29 March 2016); https://doi.org/10.1117/12.2216595

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