Abstract #3561

Hyperpolarized 3He MRI ADC and Ventilation Features Predict Rapidly Worsening Emphysema Using Machine-learning

Maksym Sharma¹, Alexander M Matheson¹, David G McCormack², David A Palma^1,3, and Grace Parraga^1,2,3

¹Medical Biophysics, Western University, London, ON, Canada, ²Division of Respirology, Department of Medicine, Western University, London, ON, Canada, ³Department of Oncology, Western University, London, ON, Canada

Pulmonary hyperpolarized ³He MRI provides a way to measure lung ventilation heterogeneity in patients with COPD, including terminal airspace enlargement or emphysema that is typically quantified using CT densitometry. Unfortunately, MRI-derived biomarkers of emphysema progression remain unconfirmed, and also likely because of radiation dose considerations, CT follow-up of emphysema is rarely performed, and hence its longitudinal progression is not well-understood. Here we developed a machine-learning pipeline that identified hyperpolarized ³He MRI texture features that independently and uniquely correlated and predicted rapidly-worsening emphysema nearly 3 years later, measured as CT RA₉₅₀, using a Decision Tree algorithm that achieved 82% prediction accuracy.

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