Exploring Multimodal Respiratory Monitoring and Ultrasound-based Quantification of Diaphragm Functio

Abstract

Mechanical ventilation (MV) in the intensive care unit is inherently associated with both life-saving benefits and the risk of lung and diaphragm injury, making the timing of ventilator detachment a well-studied clinical challenge. This creates a need for reliable monitoring of respiratory effort to tailor MV to individual patient requirements. Diaphragm ultrasound is a non-invasive technique with respiratory monitoring potential. However, its application is limited by operator dependency and the lack of automated, continuous analysis. To help overcome these limitations, the Sonoskin project aims to develop a wearable and operator-independent ultrasound-based respiratory monitoring system, integrating diaphragm ultrasound with surface electromyography (sEMG) as a multimodal monitoring approach. The European consortium Sonoskin forms the framework of this thesis.
The primary objective of this thesis was to evaluate the feasibility of continuous ultrasound-based diaphragm monitoring and to develop automated methods for extracting clinically relevant diaphragm parameters, with a specific focus on diaphragm thickening fraction (DTF). This thesis consists of two parts.
In Part I, a physiological study design was developed to enable synchronized acquisition of diaphragm ultrasound, sEMG, esophageal pressure, ventilator data, and gas-exchange parameters in healthy volunteers.
In Part II, a semi-automated algorithm for diaphragm parameter extraction was developed using a Radon transform-based adaptive M-mode approach. This method explicitly accounts for changes in diaphragm orientation and enables robust tracking of both pleural and peritoneal interfaces. When applied to 110 ultrasound recordings from ten healthy volunteers, the Radon-based method showed markedly improved line-tracking performance and superior image quality compared with a conventional static M-mode approach. These improvements were reflected by significantly higher contrast and smoother, more traceable signals in both spatial and intensity domains. Automated DTF measurements showed a moderate correlation between the left and right hemidiaphragms. Absolute diaphragm thickness and DTF values were within the lower range of normal values reported in the literature, supporting the need for further evaluation and potential redefinition of reference values when using automated Radon-based tracking methods.
In addition to diaphragm thickening, angular motion of the diaphragm was quantified through analysis of the diaphragmatic angle (θd). Cyclic changes in θd were consistently detected but showed only a moderate relationship with DTF, and in approximately half of the recordings the dominant frequency of θd and of DTF was similar. This cautiously suggests that angular motion captures complementary mechanical information about diaphragm behavior. Both DTF- and θd-derived parameters exhibited substantial inter-individual variability, while no significant differences were observed across controlled conditions with varying levels of breathing effort in healthy volunteers.
In conclusion, this thesis demonstrates that automated ultrasound-based quantification of diaphragm thickening is feasible using a Radon-based approach and outlines a physiological study to further explore the relevance and interpretation of diaphragm ultrasound and sEMG monitoring. Parameters derived from diaphragmatic angular motion represent a novel measure that warrants further investigation to determine potential clinical relevance. By improving tracking robustness and signal quality compared with conventional methods, this work provides a methodological foundation for future development of continuous, operator-independent, and multimodal respiratory monitoring systems to support personalized ventilation strategies.