A robust temporal metric of ventilation inhomogeneity in electrical impedance tomography

Abstract Objective. Quantification of ventilation inhomogeneity using electrical impedance tomography (EIT) typically relies on accurate identification of breathing cycles, which is often unreliable in spontaneously breathing patients. The objective of this study was to develop a robust, breath-independent metric for characterizing temporal ventilation heterogeneity. Approach. We propose a pixel asynchrony value (PAV), a window-based temporal correlation measure that quantifies the asynchrony between local pixel waveforms and a global ventilation reference without requiring breath segmentation. A global summary index, the global asynchronous index (GAI), is derived from spatial PAV distributions. The method was evaluated using EIT recordings from 21 high dependency unit patients acquired before and after airway clearance therapy. Main results. GAI demonstrated a consistent and significant reduction following treatment ( p = 0.0011), indicating improved temporal synchrony of regional ventilation. In contrast, conventional inhomogeneity indices, including the global inhomogeneity index and the standard deviation of regional ventilation delay, showed weaker or inconsistent changes. Robustness analysis further showed that GAI remains stable across a range of window lengths and is insensitive to the absence of explicit breath-cycle detection. Significance. The proposed PAV-based GAI provides a physiologically interpretable and robust measure of temporal ventilation heterogeneity that can be applied without breath segmentation, making it particularly suitable for spontaneously breathing patients and routine clinical monitoring.