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Eur Radiol ; 22(12): 2736-42, 2012 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-22814825

RESUMEN

OBJECTIVES: To determine the diagnostic accuracy of high-resolution computed tomography (HRCT) for the detection of nontuberculous mycobacterium infection (NTM) in adult cystic fibrosis (CF) patients. METHODS: Twenty-seven CF patients with sputum-culture-proven NTM (NTM+) underwent HRCT. An age, gender and spirometrically matched group of 27 CF patients without NTM (NTM-) was included as controls. Images were randomly and blindly analysed by two readers in consensus and scored using a modified Bhalla scoring system. RESULTS: Significant differences were seen between NTM (+) and NTM (-) patients in the severity of the bronchiectasis subscore [45 % (1.8/4) vs. 35 % (1.4/4), P = 0.029], collapse/consolidation subscore [33 % (1.3/3 vs. 15 % (0.6/3)], tree-in-bud/centrilobular nodules subscore [43 % (1.7/3) vs. 25 % (1.0/3), P = 0.002] and the total CT score [56 % (18.4/33) vs. 46 % (15.2/33), P = 0.002]. Binary logistic regression revealed BMI, peribronchial thickening, collapse/consolidation and tree-in-bud/centrilobular nodules to be predictors of NTM status (R(2 )= 0.43). Receiver-operator curve analysis of the regression model showed an area under the curve of 0.89, P < 0.0001. CONCLUSION: In adults with CF, seven or more bronchopulmonary segments showing tree-in-bud/centrilobular nodules on HRCT is highly suggestive of NTM colonisation. KEY POINTS: Lung function declines rapidly in cystic fibrosis patients with nontuberculous mycobacterium infection. High-resolution computed tomography can help identify nontuberculous mycobacterium in CF patients. Extensive collapse/consolidation and tree-in-bud/centrilobular nodules are predictive of NTM infection. Multiple bronchopulmonary segments showing tree-in-bud/centrilobular nodules strongly suggest nontuberculous mycobacterium infection.


Asunto(s)
Fibrosis Quística/diagnóstico por imagen , Infecciones por Mycobacterium no Tuberculosas/diagnóstico por imagen , Tomografía Computarizada por Rayos X/métodos , Adolescente , Adulto , Distribución de Chi-Cuadrado , Femenino , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Curva ROC , Índice de Severidad de la Enfermedad , Espirometría , Esputo/microbiología
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