Imaging-derived biomarkers in Asthma: Current status and future perspectives

Asthma is a common disorder affecting around 315 million individuals worldwide. The heterogeneity of asthma is becoming increasingly important in the era of personalized treatment and response assessment. Several radiological imaging modalities are available in asthma including chest x-ray, computed tomography (CT) and magnetic resonance imaging (MRI) scanning. In addition to qualitative imaging, quantitative imaging could play an important role in asthma imaging to identify phenotypes with distinct disease course and response to therapy, including biologics. MRI in asthma is mainly performed in research settings given cost, technical challenges, and there is a need for standardization. Imaging analysis applications of artificial intelligence (AI) to subclassify asthma using image analysis have demonstrated initial feasibility, though additional work is necessary to inform the role of AI in clinical practice.

Automated summary

Asthma is a common disorder with a global impact, affecting approximately 315 million individuals. The heterogeneity of asthma has gained significance in the personalized treatment and assessment of response. Radiological imaging modalities such as X-ray, CT, and MRI are used for diagnosis and research purposes in asthma. Quantitative imaging analysis, along with artificial intelligence (AI), shows potential in identifying different phenotypes with distinct disease progression and therapeutic response. However, further research is needed to fully understand the role of AI in clinical practice.