TY - JOUR
T1 - Imaging-derived biomarkers in Asthma
T2 - Current status and future perspectives
AU - Pompe, Esther
AU - Kwee, Anastasia Kal
AU - Tejwani, Vickram
AU - Siddharthan, Trishul
AU - Mohamed Hoesein, Firdaus Aa
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/3
Y1 - 2023/3
N2 - 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.
AB - 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.
KW - Artificial Intelligence
KW - Asthma
KW - Biomarkers
KW - Humans
KW - Magnetic Resonance Imaging/methods
KW - Tomography, X-Ray Computed
KW - Artificial intelligence (AI)
KW - Imaging
KW - Quantitative
UR - http://www.scopus.com/inward/record.url?scp=85147823422&partnerID=8YFLogxK
U2 - 10.1016/j.rmed.2023.107130
DO - 10.1016/j.rmed.2023.107130
M3 - Article
C2 - 36702169
SN - 0954-6111
VL - 208
SP - 1
EP - 6
JO - Respiratory Medicine
JF - Respiratory Medicine
M1 - 107130
ER -