Needleman, Sarah Helen;
(2024)
Signal characterisation for functional lung imaging using oxygen-enhanced MRI.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Clinical approaches for lung function assessment are limited by either a lack of regional information or the use of ionising radiation during imaging. Lung oxygen-enhanced MRI (OE-MRI) offers a safe technique to assess regional lung function. However, the analysis of dynamic lung OE-MRI is challenging both due to the presence of confounding signals and poor signal-to-noise ratio, particularly at 3 T, which can compromise the accuracy and sensitivity of lung function measures derived from OE-MRI. The aim of this thesis was to overcome the challenges in the analysis of dynamic OE-MRI by developing a robust automatic analysis pipeline to separate the oxygen-enhancement response of the lung from confounds and noise. The analysis pipeline was developed for application to a dynamic dual-echo gradient echo OE-MRI acquisition at 3 T. Independent component analysis (ICA) was utilised to isolate the oxygen-enhancement response of the lung. The developed OE-MRI acquisition and analysis pipeline approach demonstrated the sensitivity to, and resolution of, the different oxygen-induced MR signal changes of lung tissue from oxygenated blood, which has not previously been observed using OE-MRI. The approach also demonstrated good scan-rescan repeatability, good analysis-reanalysis repeatability, and feasibility for use in multi-centre multi-vendor studies. The OE-MRI acquisition and analysis approach demonstrated a sensitivity to smoking status, suggesting a likely sensitivity to pathology. The sensitivity to pathology was explored in cystic fibrosis (CF) data acquired at 1.5 T. The lung function measures extracted from the CF data demonstrated significant correlations with pulmonary function tests, suggesting a sensitivity to CF disease severity and supporting future use of the approach in clinical studies. In summary, this thesis develops a new approach to analysing lung OE-MRI data and presents an initial implementation in healthy lungs and in cystic fibrosis, indicating the potential future utility of the developed approach.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Signal characterisation for functional lung imaging using oxygen-enhanced MRI |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10200569 |
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