Spatial Ventilation Inhomogeneity Determined by Electrical Impedance Tomography in Patients With Chronic Obstructive Lung Disease

Abstract

The aim of this study was to examine whether electrical impedance tomography (EIT) could determine the presence of ventilation inhomogeneity in patients with chronic obstructive lung disease (COPD) from measurements carried out not only during conventional forced full expiration maneuvers but also from forced inspiration maneuvers and quiet tidal breathing and whether the inhomogeneity levels were comparable among the phases and higher than in healthy subjects. EIT data were acquired in 52 patients with exacerbated COPD (11 women, 41 men, 68 ± 11 years) and 14 healthy subjects (6 women, 8 men, 38 ± 8 years). Regional lung function parameters of forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), forced inspiratory vital capacity (FIVC), forced inspiratory volume in 1 s (FIV1), and tidal volume (V T ) were determined in 912 image pixels. The spatial inhomogeneity of the pixel parameters was characterized by the coefficients of variation (CV) and the global inhomogeneity (GI) index. CV and GI values of pixel FVC, FEV1, FIVC, FIV1, and VT were significantly higher in patients than in healthy subjects (p ≤ 0.0001). The ventilation distribution was affected by the analyzed lung function parameter in patients (CV: p = 0.0024, GI: p = 0.006) but not in healthy subjects. Receiver operating characteristic curves showed that CV and GI discriminated patients from healthy subjects with an area under the curve (AUC) of 0.835 and 0.852 (FVC), 0.845 and 0.867 (FEV1), 0.903 and 0.903 (FIVC), 0.891 and 0.882 (FIV1), and 0.821 and 0.843 (VT), respectively. These findings confirm the ability of EIT to identify increased ventilation inhomogeneity in patients with COPD.

Keywords: EIT; airway obstruction; electrical bioimpedance; forced ventilation maneuver; functional imaging; lung imaging; obstructive lung disease; pulmonary function testing.

Conflict of interest statement

IF has received funding from the European Commission (grant agreement numbers 611223, 668259, and 825572) and speaking/congress fees from Dräger AG & Co KGaA outside the submitted work. ZZ has received a consulting fee from Dräger AG & Co KGaA outside the submitted work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2021 Frerichs, Lasarow, Strodthoff, Vogt, Zhao and Weiler.

Figures

FIGURE 1

Schematic drawing of the electrical impedance tomography (EIT) waveform in one image pixel. The waveform reflects the regional lung volume changes over time during pulmonary function testing (A). Five lung function measures analyzed from the periods of quiet tidal breathing, forced full inspiration, and forced full expiration are highlighted: tidal volume (VT), forced inspiratory vital capacity (FIVC), forced inspiratory volume in 1 s (FIV1), forced expiratory volume in 1 s (FEV1), and forced vital capacity (FVC). These measures are calculated in all image pixels and can be visually presented in form of two-dimensional maps called functional EIT images. Example functional EIT images (B) showing the distribution of regional FEV1 acquired in a healthy subject and a patient with chronic obstructive lung disease (COPD) are provided.

FIGURE 2

Heterogeneity of regional lung ventilation in patients with COPD and healthy human subjects and the results of receiver-operating characteristics (ROC) analyses. Coefficients of variation (CV) of the pixel values of FVC (A), FEV1(B), FIVC (C), FIV1(D), and VT(E) are shown at the top. The ROC curves revealing the power of CV of the pixel values of FVC (F), FEV1(G), FIVC (H), FIV1(I), and VT(J) to discriminate between the patients suffering from COPD and the healthy subjects are displayed at the bottom. Box and whisker plots show the minimum, 25% percentile, median, 75% percentile, and maximum values. Significant differences between the two groups are indicated: ****p < 0.0001; ***p = 0.0001; ††p < 0.01 (vs. FEV1). AUC, confidence interval (CI), and p-values are given in the bottom part of each ROC curve diagram.

FIGURE 3

Heterogeneity of regional lung ventilation in patients with COPD and healthy human subjects and the results of ROC analyses. The values of GI indices calculated from the pixel values of FVC (A), FEV1(B), FIVC (C), FIV1(D), and VT(E) are shown at the top. The ROC curves revealing the power of the GI indices calculated from the pixel values of FVC (F), FEV1(G), FIVC (H), FIV1(I), and VT(J) to discriminate between the patients suffering from COPD and the healthy subjects are given at the bottom part of the figure. Box and whisker plots show the minimum, 25% percentile, median, 75% percentile, and maximum values. Significant differences between the two groups are indicated: ****p < 0.0001; ††p < 0.01 (vs. FEV1); † † †p < 0.001 (vs. FEV1). AUC, CI, and p-values are given in the bottom part of each ROC curve diagram.