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Abstract #5364

Modelling Whole-Lung and Regional Carbon Monoxide Transfer Factor with Hyperpolarized 129Xe MRI in Asthma and COPD Patients

Jemima H Pilgrim-Morris1, Laurie J Smith1, Joshua R Astley1,2, Laura C Saunders1, Guilhem J Collier1, Alberto M Biancardi1, Bilal A Tahir1,2,3, Helen Marshall1, Latife Hardaker4, Titti Fihn-Wikander5, Rod Hughes6, Roger Thompson1, Neil J Stewart1, and Jim M Wild1,3
1POLARIS, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom, 2Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom, 3Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom, 4Priory Medical Group, York, United Kingdom, 5Evidence Delivery, BioPharmaceuticals Medical, BioPharmaceuticals Business Unit, AstraZeneca, Gothenburg, Sweden, 6Clinical Development, Research and Early Development, Respiratory & Immunology, AstraZeneca, Cambridge, United Kingdom

Synopsis

Keywords: Hyperpolarized MR (Gas), Lung, ModellingHyperpolarized 129Xe ventilation and dissolved-phase MRI metrics were used to predict the carbon monoxide transfer factor (TLCO) in the lungs of patients with asthma and/or Chronic Obstructive Pulmonary Disease (COPD) using two linear regression models: (1) an existing analytical model based on physiology and (2) a machine learning model, which also included patient age and sex in the prediction. The machine learning model was further extended to create TLCO maps, providing a regional visualization of this gold standard measure of gas transfer.

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