Pulmonary Imaging of Chronic Obstructive Pulmonary Disease using Multi-Parametric Response Maps

Chronic obstructive pulmonary disease (COPD) is characterized by irreversible airflow obstruction caused by airway remodelling and parenchymal destruction. Clinically, observation of COPD is performed using spirometry, but this technique only provides a global measure of lung health. To supplement these clinical measurements, thoracic computed tomography (CT) and hyperpolarized gas magnetic resonance imaging (MRI) have been used to measure regional structure and function abnormalities. Although CT and MRI have been used to research COPD, combination of both modalities into an interrelated image has never been performed. Therefore, we developed an image processing pipeline to combine MRI-CT information into a multi-parametric response map. In a COPD cohort, multi-parametric measurements became more abnormal as disease severity increased, were related to pulmonary function and quality of life, and revealed novel disease labels. This technique has potential to visualize and quantify the transition phases of COPD allowing for the possible identification of new treatment targets