Deep Learning Model for COPD Classification/Staging Using Lung CT

Abstract

Chronic Obstructive Lung Disease (COPD) is a progressive and prevalent lung disease which is associated with airflow obstruction due to inflamed airways and lung parenchyma. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) utilizes a combined assessment of COPD using three factors of lung function, symptoms, and exacerbation history to evaluate disease severity and prevent future risk through devising treatment tailored according to the three assessment factors. In this study, we developed a deep learning 3D-CNN model using patient’s thoracic CT images instead of the data pertaining to lung function to assess COPD severity based on a high-resolution 8-stage system. The developed COPD classification/staging system has demonstrated high accuracy of 83% in assessing COPD severity using the 8-staging COPD scheme, providing highly valuable diagnostic information useful for treatment planning.