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Imaging-derived biomarkers in Asthma: Current status and future perspectives
Esther Pompe1, Anastasia Kal Kwee1, Vickram Tejwani2
1Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands.
Respiratory Medicine
|January 26, 2023
Summary
Asthma imaging, including MRI, can help personalize treatment by identifying distinct patient subtypes. Artificial intelligence shows promise in analyzing these images for better asthma classification and care.
Area of Science:
- Pulmonology and Respiratory Medicine
- Medical Imaging
- Artificial Intelligence in Medicine
Background:
- Asthma affects over 315 million people globally, highlighting the need for personalized treatment strategies.
- Understanding asthma heterogeneity is crucial for tailoring therapies and assessing treatment responses.
- Radiological imaging, including CT and MRI, offers valuable insights into asthma, but quantitative analysis and standardization are needed.
Purpose of the Study:
- To explore the role of quantitative imaging, particularly MRI, in characterizing asthma phenotypes.
- To assess the potential of artificial intelligence (AI) in analyzing medical images for asthma subclassification.
- To identify how advanced imaging techniques can inform personalized asthma management and biologic therapy response.
Main Methods:
- Review of current radiological imaging modalities used in asthma research, including chest X-ray, CT, and MRI.
- Discussion of the potential of quantitative imaging analysis for identifying distinct asthma phenotypes.
- Exploration of early-stage artificial intelligence applications in analyzing asthma imaging data for subclassification.
Main Results:
- Quantitative imaging offers a promising avenue for identifying asthma phenotypes with different disease trajectories and treatment responses.
- Magnetic resonance imaging (MRI) in asthma is primarily used in research due to cost and standardization challenges.
- AI-driven image analysis has shown initial feasibility in subtyping asthma, indicating potential for clinical application.
Conclusions:
- Advanced imaging techniques, especially quantitative MRI, are vital for understanding asthma heterogeneity and personalizing treatment.
- Further research and standardization are required to integrate MRI and AI into routine clinical practice for asthma management.
- AI-powered asthma imaging analysis holds significant potential for improving patient stratification and therapeutic strategies, including the use of biologics.
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