Time-based pulmonary features from electrical impedance tomography demonstrate ventilation heterogeneity in chronic obstructive pulmonary disease

摘要

Pulmonary electrical impedance tomography (EIT) is a functional imaging technique that allows real-time monitoring of ventilation distribution. Ventilation heterogeneity (VH) is a characteristic feature of chronic obstructive pulmonary disease (COPD) and has previously been quantified using features derived from tidal variations in the amplitude of the EIT signal. however, VH may be better described by time-based metrics, the measurement of which is made possible by the high temporal resolution of EIT. We aimed 1) to quantify VH using novel time-based Eli metrics and 2) to determine the physiological relevance of these metrics by exploring their relationships with complex lung mechanics measured by the forced oscillation technique (FOT). We performed FOT, spirometry, and tidal-breathing EIT measurements in 11 healthy controls and 9 volunteers with COPD. Through offline signal processing, we derived 3 features from the impedance-time (Z-t) curve for each image pixel: 1) t(E) mean expiratory time; 2) PHASE, mean time difference between pixel and global Z-t curves; and 3) AMP, mean amplitude of Z-t curve tidal variation. Distribution was quantified by the coefficient of variation (CV) and the heterogeneity index (HI). Both CV and HI of the t(E) and PHASE features were significantly increased in COPD compared with controls, and both related to spirometry and FOT resistance and reactance measurements. In contrast, distribution of the AMP feature showed no relationships with lung mechanics. These novel time-based EIT metrics of VH reflect complex lung mechanics in COPD and have the potential to allow real-time visualization of pulmonary physiology in spontaneously breathing subjects.