Electrical impedance tomography to guide personalized ventilator settings in intensive care patients

In the intensive care unit, critically ill patients are often mechanically ventilated. While ventilation can be life-saving, it may also cause additional lung injury. Careful monitoring of ventilation is therefore crucial. This dissertation investigated the role of electrical impedance tomography (EIT), an innovative, non-invasive technique that provides real-time images of lung ventilation. This enables the care givers to better respond to changes in lung function and to adjust ventilator settings more precisely to the individual patient. This thesis shows that EIT can support setting the optimal positive end-expiratory pressure, thereby reducing both alveolar collapse and overdistension. This thesis also developed a new algorithm allowing EIT to be used in patients who are partially breathing spontaneously. In addition, it was demonstrated that EIT can track changes in lung function over time, for example in COVID-19 patients. EIT thus contributes to more personalized and safer ventilation, with a reduced risk of additional lung injury.