Regional expiratory time constants in severe respiratory failure estimated by electrical impedance tomography: a feasibility study

Abstract

Background: Electrical impedance tomography (EIT) has been used to guide mechanical ventilation in ICU patients with lung collapse. Its use in patients with obstructive pulmonary diseases has been rare since obstructions could not be monitored on a regional level at the bedside. The current study therefore determines breath-by-breath regional expiratory time constants in intubated patients with chronic obstructive pulmonary disease (COPD) and acute respiratory distress syndrome (ARDS).

Methods: Expiratory time constants calculated from the global impedance EIT signal were compared to the pneumatic volume signals measured with an electronic pneumotachograph. EIT-derived expiratory time constants were additionally determined on a regional and pixelwise level. However, regional EIT signals on a single pixel level could in principle not be compared with similar pneumatic changes since these measurements cannot be obtained in patients. For this study, EIT measurements were conducted in 14 intubated patients (mean Simplified Acute Physiology Score II (SAPS II) 35 ± 10, mean time on invasive mechanical ventilation 36 ± 26 days) under four different positive end-expiratory pressure (PEEP) levels ranging from 10 to 17 cmH2O. Only patients with moderate-severe ARDS or COPD exacerbation were included into the study, preferentally within the first days following intubation.

Results: Spearman's correlation coefficient for comparison between EIT-derived time constants and those from flow/volume curves was between 0.78 for tau (τ) calculated from the global impedance signal up to 0.83 for the mean of all pixelwise calculated regional impedance changes over the entire PEEP range. Furthermore, Bland-Altman analysis revealed a corresponding bias of 0.02 and 0.14 s within the limits of agreement ranging from - 0.50 to 0.65 s for the aforementioned calculation methods. In addition, exemplarily in patients with moderate-severe ARDS or COPD exacerbation, different PEEP levels were shown to have an influence on the distribution pattern of regional time constants.

Conclusions: EIT-based determination of breath-by-breath regional expiratory time constants is technically feasible, reliable and valid in invasively ventilated patients with severe respiratory failure and provides a promising tool to individually adjust mechanical ventilation in response to the patterns of regional airflow obstruction.

Trial registration: German Trial Register DRKS 00011650 , registered 01/31/17.

Keywords: ARDS; Electrical impedance tomography; Exacerbation; Expiratory time constant; Flow limitation; Severe COPD.

Conflict of interest statement

Ethics approval and consent to participate

The present study was approved by the Institutional Review Board (Ethical committee of the University Witten/Herdecke) and registered at the German Clinical Trial Register and the WHO trial register (DRKS00011650/ U1111–1192-0396).

Consent for publication

The manuscript has been read and its submission approved by all co-authors. Patients were prospectively included after informed consent was obtained from the legal caregiver.

Competing interests

CK and SS received travel grants and lecture fees from Maquet Cardiopulmonary, Rastatt, Germany. WW received fees for advisory board meetings and lectures from Maquet Cardiopulmonary, Rastatt, Germany. Andreas Waldmann is an employee of Swisstom AG. PR and TS have no competing interests. SHB was co-founder and chief medical director of Swisstom until October 2016.

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Figures

Fig. 1

Algorithm for calculating regional time constant τreg. Of note, curve fitting starts at the time when 75% of peak signal is reached (see “Methods”). V(t): volume at time point t, V0 volume at start of expiration, t the time from the start at end-inspiration to the end of expiration, τ the expiratory time constant and C the end expiratory volume

Fig. 2

Tau calculation from global (a) vs. mean or median (b) of regional tau. ΔZ, impedance change. EIT, electrical impedance tomography

Fig. 3

Spearman correlation r between global tau calculation and volume signal (a), mean regional electrical impedance tomography (EIT)-derived tau (c) and median regional EIT-derived tau (e). The corresponding Bland-Altman analysis is displayed in b, d and f

Fig. 4

Typical examples of frequency distribution of regional τ values calculated in a stiff lung (a), in acute respiratory distress syndrome with pneumonia (b) and in chronic obstructive pulmonary disease (c). From left to right: computed tomography scan, histogram of τ regional values and flow curve

Fig. 5

Typical examples of τ determined at different positive end-expiratory pressure (PEEP) levels in pneumonia/acute respiratory distress syndrome (ARDS) (a), in stiff lungs (b) and in chronic obstructive pulmonary disease (COPD) (c and d) with its regional distribution. NA = not applicable

Fig. 6

Typical examples of τ determined at different positive end-expiratory pressure (PEEP) levels in pneumonia/acute respiratory distress syndrome (ARDS) (a), in stiff lungs (b) and in chronic obstructive pulmonary disease (COPD) (c and d) displayed as pixel-wise histograms