Quantitative computed tomography analysis of the airways in patients with cystic fibrosis using automated software: correlation with spirometry in the evaluation of severity

• Autor(a) principal: Santos,Marcel Koenigkam
• Data de Publicação: 2016
• Outros Autores: Cruvinel,Danilo Lemos, Menezes,Marcelo Bezerra de, Teixeira,Sara Reis, Vianna,Elcio de Oliveira, Elias Júnior,Jorge, Martinez,José Antonio Baddini
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Radiologia Brasileira (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842016000600351
• topic: Cystic fibrosis; Tomography, X-ray computed; Airway remodeling/physiology

Abstract Objective: To perform a quantitative analysis of the airways using automated software, in computed tomography images of patients with cystic fibrosis, correlating the results with spirometric findings. Materials and Methods: Thirty-four patients with cystic fibrosis were studied-20 males and 14 females; mean age 18 ± 9 years-divided into two groups according to the spirometry findings: group I (n = 21), without severe airflow obstruction (forced expiratory volume in first second [FEV1] > 50% predicted), and group II (n = 13), with severe obstruction (FEV1 ≤ 50% predicted). The following tracheobronchial tree parameters were obtained automatically: bronchial diameter, area, thickness, and wall attenuation. Results: On average, 52 bronchi per patient were studied. The number of bronchi analyzed was higher in group II. The correlation with spirometry findings, especially between the relative wall thickness of third to eighth bronchial generation and predicted FEV1, was better in group I. Conclusion: Quantitative analysis of the airways by computed tomography can be useful for assessing disease severity in cystic fibrosis patients. In patients with severe airflow obstruction, the number of bronchi studied by the method is higher, indicating more bronchiectasis. In patients without severe obstruction, the relative bronchial wall thickness showed a good correlation with the predicted FEV1.