2021
DOI: 10.1111/1754-9485.13169
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Quantitative evaluation of computed tomography findings in patients with bronchial asthma: prediction of therapeutic response

Abstract: Introduction: To compare pretreatment quantitative CT parameters between patients with well-controlled and those with poorly controlled bronchial asthma after treatment. Methods: We retrospectively reviewed 785 patients with clinical diagnosis of bronchial asthma from January 2009 to April 2015. Of these, 43 patients underwent high-resolution CT and pulmonary function tests at initial diagnosis. According to the Global Initiative for Asthma (GINA) 2015 guidelines, the patients were classified into two groups (… Show more

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“… 4 , 5 High-resolution CT scans can be used to observe the fine structures of the lungs, thereby understanding different degrees of emphysema, bronchial wall thickening, lung deformation and changes in surrounding blood vessels, etc., which can better evaluate the condition of asthma patients and help clinicians provide precise treatment to patients. 6 Studies have shown that quantitative imaging plays an important role in describing asthma phenotypes and predicting future asthma incidence. 7 , 8 This study explores the value of CT radiomics models in predicting the clinical stage of bronchial asthma, and constructs and evaluates prediction models.…”
Section: Introductionmentioning
confidence: 99%
“… 4 , 5 High-resolution CT scans can be used to observe the fine structures of the lungs, thereby understanding different degrees of emphysema, bronchial wall thickening, lung deformation and changes in surrounding blood vessels, etc., which can better evaluate the condition of asthma patients and help clinicians provide precise treatment to patients. 6 Studies have shown that quantitative imaging plays an important role in describing asthma phenotypes and predicting future asthma incidence. 7 , 8 This study explores the value of CT radiomics models in predicting the clinical stage of bronchial asthma, and constructs and evaluates prediction models.…”
Section: Introductionmentioning
confidence: 99%