Solution of an inverse problem to estimate airway resistance in mechanically ventilated patients from 3-D electrical impedance tomography data

This is the authors' abstract. We don't add key points for this paper.

We investigate the use of electrical impedance tomography, a non-invasive, non-ionizing imaging modality that provides real-time images of the ventilation distribution throughout the lung at the bedside, to image patients with acute hypoxic respiratory failure at the bedside and as data to inform an algorithm to determine the airway resistance throughout the bronchial tree. In this work, 3-D Electrical Impedance Tomography (EIT) difference image reconstructions and ventilator data are used in a multi-compartment lung model to solve an inverse problem to estimate the airway resistance along the bronchial tree. The method is demonstrated on five hospitalized patients who received mechanical ventilation as part of their hospital care. Comparisons of the EIT and airway resistance reconstructions are shown to be in good agreement with computed tomography (CT) scans and/or chest x-rays taken as part of the patients' care, and the results are consistent with their clinical condition. Patients with acute hypoxic respiratory failure often have heterogeneous distribution of ventilation, which makes the optimization of ventilator settings more difficult and increases the risk of ventilator-induced lung injury. Knowledge of the airway distribution along the bronchial tree could aid in determining personalized ventilator settings in such patients.