Development of novel biomarkers for assessing pulmonary and cardiopulmonary function utilizing hyperpolarized gas MRI
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[EMBARGOED UNTIL 08/01/2026] Magnetic Resonance Imaging (MRI) is an advanced imaging technique that transformed the field of Radiology. Its' capability of providing such high-resolution imaging without exposing patients to ionizing radiation changed the field of medical diagnosis and treatment. The presence of this imaging modality has allowed scientists to expand on quantitative methods to further improve the precision and application of MRI in disease management. Although an excellent imaging modality, it is unable to provide informative pulmonary images regarding lung structure and lung function due to low proton density in the lungs. HPG MRI is an innovative imaging modality that is now clinically used and allows for the visualization of ventilation capabilities and gas exchange efficiency in patients. Compared to the common clinical standard for assessing lung structure and lung function, pulmonary function tests (PFTs), HPG MRI provides regional specificity that PFTs lack. This dissertation presents various novel quantification methods utilizing HPG MRI so that personalized medicine and cost reduction can be achieved when used in clinical and research settings. The first novel technique developed and presented in this dissertation involves the development of a three-dimensional spatial ventilation defect focality/sparseness quantifier utilizing HPG MRI, a Cluster Index (CI). This technique was validated utilizing synthesized spherical data and synthesized lung defects to assimilate real pulmonary ventilation defects. This new method was also utilized to compare CIs among different pulmonary diseases such as ventilation images from asthmatic, CF, and COPD subjects. This method may allow for the investigation of potential information regarding underlying pathophysiology that has yet to be found and potential differences in defect focality across different diseases and disease severities. The second study presented in this dissertation involved the development of a graphical user interface that would allow for the assessment of reader manually selected thresholds and compare these to existing VDP quantifying methods. Image features and potential influence of these in threshold selections were also assessed and compared among readers. The results provide insight into what would be the best VDP quantifying method, if the existing thresholds match visual assessments, and the agreement between reader selected thresholds and visually estimated VDPs. The third technique developed and presented entails the performance of singular value decomposition to construct low-noise approximation of FID data, and time domain curve fitting on all free induction decays to obtain a dynamic RBC/membrane ratio and oscillation amplitude quantification. This new marker has the potential to be used as an imaging biomarker to assess disease severity, treatment response, and allow for reduced costs in HPG MRI due to the denoising properties in SVD. The findings from this dissertation will contribute to the development of new imaging biomarker methods to quantify defect focality, disease state/progression, and a standardized DP quantifying protocol.
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Ph. D