Contemporary mechanical ventilation strategies in ARDS rely on lung-protective ventilation approaches that typically utilize separate static variables/settings (e.g., tidal volumes, plateau pressure) and cut-off values. This approach fails to capture complex patient dynamics. Increasing efforts have focused on the interactions between different parameters (e.g. mechanical power, driving pressure); however, these only accommodate a limited number of interactions and do not integrate the complexity of patient-specific, severity-dependent and time-varying thresholds for “safe” mechanical ventilation. In aviation, the “flight envelope” concept revolutionized flight safety by defining flexible, context-dependent boundaries as a function of multiple dimensions (e.g. flight speed, altitude, (dynamic) loads on the aircraft) within which an aircraft can operate. When a new aircraft is developed, its operational safety envelope is determined analytically. Calculations are quickly followed by flight simulations and flight testing, beginning from a known safe point within the envelope and gradually carefully exploring its boundaries to characterize its limits. Inspired by this aviation approach, we propose the “respiratory envelope” framework for mechanical ventilation: a conceptual framework that allows for the incorporation of multiple (time-dependent) dimensions and integrates interactions between ventilator variables/settings and patient characteristics. Just as flight envelopes informed the development of automated envelope protection algorithms and autopilot systems, a similar framework could be applied in clinical settings to simulate real-time “safety zones” based on continuously monitored, yet underutilized, physiological data, such as in digital twins.

Background: Prolonged weaning from mechanical ventilation is associated with poor clinical outcome. Therefore, choosing the right moment for weaning and extubation is essential. Electrical Impedance Tomography (EIT) is a promising innovative lung monitoring technique, but its role in supporting weaning decisions is yet uncertain. We aimed to evaluate physiological trends during a T-piece spontaneous breathing trail (SBT) as measured with EIT and the relation between EIT parameters and SBT success or failure. Methods: This is an observational study in which twenty-four adult patients receiving mechanical ventilation performed an SBT. EIT monitoring was performed around the SBT. Multiple EIT parameters including the end-expiratory lung impedance (EELI), delta Tidal Impedance (ΔZ), Global Inhomogeneity index (GI), Rapid Shallow Breathing Index (RSBI_EIT), Respiratory Rate (RR_EIT) and Minute Ventilation (MV_EIT) were computed on a breath-by-breath basis from stable tidal breathing periods. Results: EELI values dropped after the start of the SBT (p < 0.001) and did not recover to baseline after restarting mechanical ventilation. The ΔZ dropped (p < 0.001) but restored to baseline within seconds after restarting mechanical ventilation. Five patients failed the SBT, the GI (p = 0.01) and transcutaneous CO₂ (p < 0.001) values significantly increased during the SBT in patients who failed the SBT compared to patients with a successful SBT. Conclusion: EIT has the potential to assess changes in ventilation distribution and quantify the inhomogeneity of the lungs during the SBT. High lung inhomogeneity was found during SBT failure. Insight into physiological trends for the individual patient can be obtained with EIT during weaning from mechanical ventilation, but its role in predicting weaning failure requires further study.

Objective. Geometrical region of interest (ROI) selection in electrical impedance tomography (EIT) monitoring may lack sensitivity to subtle changes in ventilation distribution. Therefore, we demonstrate a new physiological method for ROI definition. This is relevant when using ROIs to compute subsequent EIT-parameters, such as the ventral-to-dorsal ratio during a positive end-expiratory pressure (PEEP) trial.Approach.Our physiological approach divides an EIT image to ensure exactly 50% tidal impedance variation in the ventral and dorsal region. To demonstrate the effects of our new method, EIT measurements during a decremental PEEP trial in 49 mechanically ventilated ICU-patients were used. We compared the center of ventilation (CoV), a robust parameter for changes in ventro-dorsal ventilation distribution, to our physiological ROI selection method and different commonly used ROI selection methods. Moreover, we determined the impact of different ROI selection methods on the PEEP level corresponding to a ventral-to-dorsal ratio closest to 1.Main results.The division line separating the ventral and dorsal ROI was closer to the CoV for our new physiological method for ROI selection compared to geometrical ROI definition. Moreover, the PEEP level corresponding to a ventral-to-dorsal ratio of 1 is strongly influenced by the chosen ROI selection method, which could have a profound clinical impact; the within-subject range of PEEP level was 6.2 cmH2O depending on the chosen ROI selection method.Significance.Our novel physiological method for ROI definition is sensitive to subtle ventilation-induced changes in regional impedance (i.e. due to (de)recruitment) during mechanical ventilation, similar to the CoV.