Event-triggered averaging of electrical impedance tomography (EIT) respiratory waveforms as compared to low-pass filtering for removal of cardiac related impedance changes.

Abstract

Electrical impedance tomography (EIT) is used for bedside ventilation monitoring; cardiac related impedance changes represent a source of noise superimposed on the ventilation signal, commonly removed by low-pass filtering (LPF). We investigated if an alternative approach, based on an event-triggered averaging (ETA) process, is more effective at preserving the actual ventilation waveform. Ten paralyzed patients undergoing volume-controlled ventilation were studied; 30 breaths for each patient were identified to compare LPF and ETA. For ETA the identified breaths were temporally aligned on the beginning of inspiration; the values of the thirty curves at each time point were averaged. The analysis was conducted on the global EIT signal and on four ventral-to-dorsal regions of interest. Global tidal variations by ETA resulted higher than LPF (average difference 139 ± 88 arbitrary units, p = 0.004). Both for global and regional waveforms, minimum and maximum EIT slopes were steeper by ETA as compared to LPF (average difference respectively − 57 ± 60 mL/s and 144 ± 96 mL/s for global signal, p < 0.05); ventilator inspiratory peak airflow correlated with maximum slope measured by ETA (r = 0.902, p < 0.001), but not LPF (p = 0.319). Beginning of inspiration identified on the ventilator waveform and on the global EIT signal by ETA occurred simultaneously, (+ 0.04 ± 0.07 s, p = 0.081), while occurred earlier by LPF (− 0.26 ± 0.1 s, p < 0.001). Removal of cardiac related impedance changes by ETA results in a ventilation signal more similar to the waveforms recorded by the ventilator, particularly regarding the slope of impedance changes and time at the minimum values as compared to LPF.Electronic supplementary materialThe online version of this article (10.1007/s10877-019-00348-2) contains supplementary material, which is available to authorized users.