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Abstract #2266

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

Amy V Simmons1, Laurie J Smith1, Zoe Somerville1, Hannah Faulke1, Bilal Tahir1, David Hughes2, Noreen West2, Alberto M Biancardi1,3, Neil J Stewart1,3, and Jim M Wild1,3
1POLARIS, Division of Clinical Medicine, Faculty of Health, The University of Sheffield, Sheffield, United Kingdom, 2Sheffield Children's Hospital NHS Foundation Trust, Sheffield, United Kingdom, Sheffield, United Kingdom, 3INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, United Kingdom

Synopsis

Keywords: Lung, Lung, Cystic Fibrosis

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.

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