Dr. Hira Awan is the lead author of this review paper: Seeing is believing—on the utility of CT in phenotyping chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) presents complex structural and functional impairments, for which chest CT has long been instrumental in quantifying abnormalities. This review details the progression of CT biomarkers in COPD, starting with foundational thresholding techniques used to assess emphysema and airway dimensions. It then moves to discuss texture analysis methods for subtyping lung tissue and image registration-based biomarkers that offer spatially-aware insights into localized abnormalities. More recent advancements, particularly with deep learning, are highlighted for their ability to automate biomarker extraction with enhanced precision in phenotype characterization and outcome prediction. Despite these significant strides, the review also acknowledges persistent challenges such as dataset heterogeneity, model generalizability, and clinical interpretability, ultimately outlining a future vision for CT biomarkers in personalized COPD management.