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Imaging-derived biomarkers in Asthma: Current status and future perspectives.
Pompe, Esther; Kwee, Anastasia Kal; Tejwani, Vickram; Siddharthan, Trishul; Mohamed Hoesein, Firdaus Aa.
Afiliação
  • Pompe E; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands. Electronic address: esther.pompe@gmail.com.
  • Kwee AK; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands. Electronic address: A.K.A.L.Kwee-2@umcutrecht.nl.
  • Tejwani V; Respiratory Institute, Cleveland Clinic (VT), USA. Electronic address: tejwanv@ccf.org.
  • Siddharthan T; Division of Pulmonary, Critical Care and Sleep Medicine, University of Miami (TS), USA. Electronic address: tsiddhar@miami.edu.
  • Mohamed Hoesein FA; Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands. Electronic address: fmohamedhoesein@gmail.com.
Respir Med ; 208: 107130, 2023 03.
Article em En | MEDLINE | ID: mdl-36702169
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Asma / Inteligência Artificial Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Revista: Respir Med Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Asma / Inteligência Artificial Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Revista: Respir Med Ano de publicação: 2023 Tipo de documento: Article
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