Patinet-tailored mechanical ventilation through bedside respiratory monitoring: Clinical use and technical innovation

The aims of this thesis are to:
- improve our understanding of static and respiratory mechanics during mechanical
ventilation in critically ill patients;
- investigate different ways to set PEEP, how they relate, and how they might best be
used in different contexts;
- improve the methodology of EIT acquisition, analysis and interpretation, to maximize
its usefulness in the management of critically ill patients.

OUTLINE:

In part I, we discuss different approaches to monitoring patients with ARDS on mechanical
ventilation, especially in the context of setting PEEP. In chapter 2 we discuss how EIT, esophageal pressure and other techniques can be used to monitor patients with COVID-
19 related ARDS. In chapter 3 we discuss in more depth the use of esophageal pressure
for setting PEEP.
In part II, we discuss how we applied these different approaches during the COVID-19
crisis. In chapter 4 we discuss our early results of setting PEEP based on EIT measurements
in the early phases of the COVID-19 pandemic in 2020. In chapter 5 we expanded this
study to compare the EIT-based approach to traditional methods using predetermined
tables relating PEEP to FiO2 requirements. In chapter 6 we collaborated with the Maasstad
hospital in Rotterdam to investigate how setting PEEP based on respiratory mechanics,
EIT or esophageal pressure measurements compared in our combined cohorts.
In part III, we look towards the future with further development and implementation
of personalized respiratory mechanics in the ICU. In chapter 7, in collaboration with 26
authors we invited to a symposium the Netherlands, we discuss the current state of EIT,
resulting in recommendations to the scientific and medical community, and the related
industry, on how we can move towards a better implementation of this technology in the
ICU. In chapter 8 we present our efforts in improving filtering during the pre-processing
step EIT data analysis. In chapter 9 we present a project aiming to provide an open, accessible
and reproducible software workflow for scientific data analysis around EIT and
respiratory mechanics in general. In chapter 10 we developed an improved method for
finding the relevant respiration-related pixels during the pre-processing step of EIT data
analysis. In chapter 11 we introduce a novel method for functional lung space selection in
EIT data that prevents the accidental removal of data in the presence of pendelluft.