Comparing the Results of a Computer Analysis Algorithm With Clinical Decisions in a Patient With Electrical Impedance Tomography Guided Ventilator Settings Regarding Optimal Positive End Expiratory Pressure and Inspiratory Pressure

The study will be performed at the Intensive Care Unit, Maastricht University Medical Centre. The investigators routinely apply EIT (Pulmovista, Dräger, Lübeck. Germany) in mechanically ventilated patients to optimize the ventilator settings .

An algorithm will be developed by the Institute of Technical Medicine, Furtwangen University, Germany. The algorithm will automatically detect changes in both PEEP and inspiratory pressures. For each PEEP step and/or changes in inspiratory pressure the difference in regional alveolar overdistension and alveolar collapse will be calculated. This makes it possible to select the optimal ventilator setting depending on the best compromise between alveolar overdistension and alveolar collapse.

The algorithm will be tested in 40 EIT guided mechanically ventilated patients. EIT measurements will be performed during an incremental and decremental PEEP trial. The EIT measurement will be performed in the same way as during standard clinical care. EIT data will be analysed offline by a ventilation practitioner with experience in EIT and with the newly developed algorithm. The resulting advice on optimal ventilator settings will be compared for inter-observer variability.