Computed tomography in severe asthma assessment: a systematic review.

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Tác giả: Elena Bargagli, Laura Bergantini, Paolo Cameli, Sara Croce, Miriana D'Alessandro, Akter Dilroba, Simona Luzzi, Martina Meocci, Tommaso Pianigiani, Benedetta Picchi, Elisa Salvadori, Vittoria Ventura

Ngôn ngữ: eng

Ký hiệu phân loại: 616.075722 Diseases

Thông tin xuất bản: England : The Journal of asthma : official journal of the Association for the Care of Asthma , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 752834

OBJECTIVE: Chest computed tomography (CT) is usually performed in patients with severe asthma (SA) to exclude concomitant conditions related to poor clinical control. Despite the growing evidence regarding the utility of CT in the characterization of morphological abnormalities and airway remodeling, its role in SA assessment is still largely unexplored. The aim of our systematic review was to evaluate published data investigating the role of chest CT in patients with SA. DATA SOURCES: The systematic search was conducted on the Medline database through the Pubmed search engine. STUDY SELECTIONS: A total of 53 studies has been included. RESULTS: Quantitative CT (qCT) parameters generally differ between SA patients compared to mild to moderate asthmatic patients or healthy controls and are related to functional decline. CT parameters allow to identify image-based clusters reflecting remodeling patterns and/or air trapping features. The detection of mucus plugs is more frequent in severe eosinophilic asthma, and it is related to marked airway obstruction and ventilation defects. Benralizumab treatment appears to reduce or vanish mucus plugging. Most studies regarding CT and bronchial thermoplasty (BT) detect the usefulness of this investigation in predicting treatment response. Lastly, conflicting results surround the relation between chest CT and SA assessment in children due to also the scarcity of studies focusing on pediatric population. CONCLUSIONS: The role of CT scans in SA is still debated. Most studies focus on the identification of CT-derived disease clusters while studies primarily evaluating the predicting role of CT scan to different biologics are lacking and could represent an interesting research area.
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