Distinguishing Lung Disease from Normal Variation in 129Xe MRI Using Patient-Tailored Methods

Abstract

Lung diseases such as COPD, interstitial lung disease, and other obstructive or restrictive disorders often present diagnostic challenges with conventional tools like pulmonary function tests (PFTs) and computed tomography (CT). This thesis investigates the development of hyperpolarized 129Xe magnetic resonance imaging (MRI) as a patient-tailored modality to differentiate pathological changes from normal physiological variation. Two complementary studies are presented. First, a multisite demographic analysis of healthy volunteers (aged 19–87 years) is used to quantify the influences of patient demographic factors (age, sex, and body mass index (BMI)) on key gas exchange metrics. This analysis encourages the consideration of patient demographic factors when using 129Xe MRI as a diagnostic tool. Second, a volume correction method is developed and applied to patients with idiopathic pulmonary fibrosis (IPF) to mitigate variability arising from differences in lung inflation during breath holds. Multivariate statistical models demonstrate significant demographic dependencies, and Bland-Altman analyses reveal that volume correction reduces inter-scan variability by approximately 35%, thereby enhancing measurement repeatability. Together, these findings support the feasibility of employing patient-specific adjustments in 129Xe MRI for more reliable lung function assessment and early disease detection.