Date Published:

2017 11

Abstract:

CT imaging is a readily quantifiable tool that can provide in-vivo assessments of lung structure in conditions such as chronic obstructive pulmonary disease (COPD). The information extracted from these data has been used in many clinical, epidemiological, and genetic investigations for patient stratification and prognostication, and to determine intermediate endpoints for clinical trials. Although these efforts have informed our understanding of the heterogeneity of pulmonary disease in smokers, they have not yet translated into new treatments for COPD or the personalisation of patient care. There are a multitude of potential reasons for this, including the lack of insight that static imaging provides for lung function and dysfunction, the limited resolution of clinical CT scanning for microscopic changes to the lung architecture, and the challenges that the biomedical community faces when trying to translate discovery to therapy. Such limitations might be addressed through novel image analysis techniques, up-and-coming CT-based and MRI-based technologies, closer ties between academia and industry, and an expanded endeavour to share data across the biomedical community.