Lung measurement and quantification of lung heterogeneity using the inspired sinewave test

Thesis

The lung is a complex organ. The most familiar and significant lung disease, chronic obstructive pulmonary disease (COPD), can be severely debilitating. Additionally, acute lung injury in the critically ill can be life-threatening. Lung diseases are known to be correlated with the heterogeneity of the lung (ventilation mismatch and perfusion mismatch). Currently, there is no “standard” method for assessing lung heterogeneity. Many lung function tests and computational methods have been proposed to diagnose and monitor lung heterogeneity. The Inspired Sinewave Test (IST) is a non-invasive and practical test to investigate lung pathophysiology.

To investigate the usability of the IST, we compare the IST results to similar lung function tests (current “standard” tests). A mathematical lung simulation is developed to enable the IST to quantify lung heterogeneity. This simulation is proved to work with the IST by testing with simulated data and sensitivity analysis. The resulting validated process is implemented in thirteen pigs (pre-injury and post-injury) and 104 human volunteers (healthy and COPD patients, including different phenotypes). The IST lung heterogeneity measurement is compared to CT scan results.

The IST results show that it is potentially a suitable device for bedside monitoring in mechanically ventilated patients. Additionally, by using the lung simulation, lung heterogeneity can be quantified by the IST using 60 s and 180 s period tracer gas. The ventilation and perfusion heterogeneity in injured animals are found to be higher than in non-injured animals. There is no clear distinction between healthy subjects and patients with COPD in the COPD human data set. The multiple alveolar compartments lung simulation is proposed to boost the COPD prediction accuracy using only IST data.

The results in this thesis suggest the translation of the IST into human medicine as a tool for detection and prevention of lung injury. Future investigations are proposed, which could potentially improve the works in this thesis.

Authors: Tran, MC

• DOI: 10.5287/ora-qykk0qxpg
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Lung diseases; Lung heterogeneity; Inspired Sinewave Test
• Subjects: Biomedical engineering