Development of functional lung 1H magnetic resonance imaging
Publication Date
December 11, 2024
Creator
Abstract
The lungs are complex organs that are responsible for gas exchange. Lung function, and the decline in lung function, are primary predictors of the life expectancy of a population. Typical methods of clinical investigation of the lungs include Pulmonary Function Tests (PFTs), which provide no spatial information, and Computed Tomography (CT) for morphology, which employs ionising radiation. The proliferation of personalised therapies in respiratory medicine has created an urgent clinical need for new pulmonary diagnostics that provide highly sensitive measures of regional lung function. Recent advancements in lung Magnetic Resonance Imaging (MRI) methods have led to several promising non-contrast-based approaches.
The work presented in this thesis is on 1H-based, non-contrast lung MRI development, and includes the development of a novel image analysis method for functional assessment termed VOxel-wise Lung VEntilation (VOLVE) analysis. VOLVE compares the signal from each lung parenchyma voxel to a navigator-type signal, enabling computation of correlation and gradient metrics which describe how the local MR signal varies across the respiratory cycle. This technique is applied in healthy volunteers and lung disease cohorts, and is extended to evaluate pulmonary perfusion by replacing the respiratory navigator with a cardiac signal timecourse, and assess local biomechanical expansion by exploiting the Jacobian determinant from the image registration. The sensitivity of the presented approaches to lung disease are demonstrated throughout with statistically significant differences between healthy volunteers and people with lung disease.
Throughout the development of these techniques, the lung MRI data is explored, and the analysis techniques validated and optimised. Computation of lung volume changes, and optimisation of the acquisition parameters (flip angle, temporal resolution and dynamic image series length) are explored. Future work can apply these techniques in multiparametric pulmonary MRI studies, including longitudinal observational studies and assessment of response to targeted therapeutic interventions.
Item Type
ethesis
Thesis Type
PhD
Subjects (LC)
Associated Schools / Departments
School of Medicine
eprints ID
78684
UoN Repository URI
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