Quantification of Gas Trapping in Cystic Fibrosis using Expiratory Breath-Hold Lung ¹H-MRI

Motivation: Early detection of cystic fibrosis lung disease is crucial for long-term lung health. Lung ¹H-MRI offers a non-ionising alternative to CT for assessing expiratory gas trapping, but lacks a method for quantification. Goal(s): Develop an automated approach to quantify gas trapping from expiratory breath-hold ¹H-MRI. Approach: We analyzed 3D SPGR MRI data from healthy participants and those with CF at full inspiration and expiration, applying an inspiration-derived threshold on the expiratory image to calculate gas-trapping volume (GTV%). Results: Our workflow successfully quantified gas trapping from ¹H-MRI, and detected abnormal GTV% in individuals with CF with normal lung function. Impact: We developed a workflow to quantify gas trapping in CF using a standard, easily implementable 1H-MRI sequence. Our proposed metric sensitively quantifies gas trapping in individuals with normal spirometry, suggesting its potential for early disease assessment.