INTRODUCTION: Abnormal ventilation is the functional consequence of airway obstruction. In patients with severe asthma, ventilation patterns visualized by magnetic resonance imaging (MRI) exhibit significant inter-patient heterogeneity. Therefore, our objectives were to identify MRI ventilation phenotypes of severe asthma using an unsupervised clustering approach and examine their associated demographic, clinical, physiologic, and inflammatory characteristics. METHODS: This retrospective analysis included 58 adults with severe asthma who underwent hyperpolarized 129Xe ventilation MRI. Nineteen quantitative variables were extracted from ventilation MRI (including ventilation defect percent (VDP), ventilation defect size, and ventilation texture features) and transformed to principal components for hierarchical clustering. Differences in demographics, clinical characteristics, spirometry, inflammatory biomarkers, and computed tomography (CT) measurements between phenotypes were evaluated using one-way ANOVA or Kruskal-Wallis tests.
RESULTS: Three ventilation phenotypes of severe asthma were identified. They were significantly different with respect to their age, prevalence of obesity, spirometry, sputum neutrophil percent, sputum cytokines (interleukin-4, interleukin-6, interleukin-15, B-cell activating factor), total lung capacity, CT air-trapping, and CT mucus score (all p<0.05). They were not different with respect to their asthma control or medication requirement, and ~75% of each phenotype reported uncontrolled asthma (ACQ-5≥1.5). Phenotype 1 had normal ventilation (VDP=1.7±0.9%) and predominantly consisted of young, obese females (88% female, 41±11 years old, 63% obese). They had normal-to-moderately reduced FEV1 (80±15%pred), normal post-bronchodilator FEV1/FVC, and reduced total lung capacity (85%pred [57-108]). 25% had intraluminal inflammation (all eosinophilic) and their sputum interleukin-4 levels were elevated. Phenotype 2 had markedly abnormal ventilation (VDP=6.2±3.8%) and was older than Phenotype 1, but also predominantly consisted of obese females (63% female, 54±13 years old, 59% obese). They had mildly-to-severely reduced FEV1 (61±17%pred) and partially reversible obstructive spirometry (72%, post-bronchodilator FEV1/FVC<0.70). 50% had intraluminal inflammation (28% eosinophilic/13% neutrophilic/9% mixed-granulocytic) and their sputum interleukin-6 levels were elevated. Phenotype 3 had severely abnormal ventilation (VDP=24.8±10.2%) and was also older than Phenotype 1 but was gender-balanced and not obese (50% female, 56±12 years old, 11% obese). They had moderately-to-very severely reduced FEV1 (41±12%pred) and partially reversible obstructive spirometry (89%, post-bronchodilator FEV1/FVC<0.70). 73% had intraluminal inflammation (39% eosinophilic/17% neutrophilic/17% mixed-granulocytic) and their sputum interleukin-15 and B-cell activating factor levels were elevated. They had the highest burden of gas-trapping and mucus on CT. CONCLUSION: Three distinct MRI ventilation phenotypes of severe asthma were identified through unbiased analysis, all of which reported uncontrolled asthma. The discordance in ventilation between phenotypes, and their characteristics, suggest different mechanisms that may be driving severe asthma. / Thesis / Master of Science (MSc) / Severe asthma is an airways disease that is characterized by inflamed, twitchy and obstructed airways. There is remarkable clinical heterogeneity between asthma patients due to the various mechanisms of disease. Abnormal ventilation is the functional consequence of abnormal airway pathology in asthma, which can be directly visualized by hyperpolarized 129Xe magnetic resonance imaging (MRI). Each ventilation pattern is unique and there is significant inter-patient variability. Thus, the goal of the thesis was to extract quantitative information from the 129Xe MRI ventilation patterns of patients with severe asthma, identify novel ventilation phenotypes, and determine their clinical relevance. An unsupervised machine learning approach using quantitative ventilation MRI features identified three unique, clinically relevant ventilation phenotypes of severe asthma with distinct clinical, physiological, and biological characteristics. The discordance in ventilation between phenotypes, and their characteristics, suggest different mechanisms that may be driving severe asthma.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29280 |
| Date | January 2024 |
| Creators | Thakar, Ashutosh |
| Contributors | Svenningsen, Sarah, Medical Sciences (Division of Physiology/Pharmacology) |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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