Bronchiolar disorders: A clinical-radiological diagnostic algorithm Academic Article uri icon

Overview

MeSH Major

  • Algorithms
  • Bronchial Diseases
  • Tomography, X-Ray Computed

abstract

  • Bronchiolar disorders are generally difficult to diagnose because most patients present with nonspecific respiratory symptoms of variable duration and severity. A detailed clinical history may point toward a specific diagnosis. Pertinent clinical questions include history of smoking, collagen vascular disease, inhalational injury, medication usage, and organ transplant. It is important also to evaluate possible systemic and pulmonary signs of infection, evidence of air trapping, and high-pitched expiratory wheezing, which may suggest small airways involvement. In this context, pulmonary function tests and plain chest radiographs may demonstrate abnormalities; however, they rarely prove sufficiently specific to obviate bronchoscopic or surgical biopsy. Given these limitations, in our experience, high-resolution CT (HRCT) scanning of the chest often proves to be the most important diagnostic tool to guide diagnosis in these difficult cases, because different subtypes of bronchiolar disorders may present with characteristic image findings. Three distinct HRCT patterns in particular are of value in assisting differential diagnosis. A tree-in-bud pattern of well-defined nodules is seen primarily as a result of infectious processes. Ill-defined centrilobular ground-glass nodules point toward respiratory bronchiolitis when localized in upper lobes in smokers or subacute hypersensitivity pneumonitis when more diffuse. Finally, a pattern of mosaic attenuation, especially when seen on expiratory images, is consistent with air-trapping characteristic of bronchiolitis obliterans or constrictive bronchiolitis. Based on an appreciation of the critical role played by HRCT scanning, this article provides clinicians with a practical algorithmic approach to the diagnosis of bronchiolar disorders.

publication date

  • April 2010

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1378/chest.09-0800

PubMed ID

  • 20371529

Additional Document Info

start page

  • 938

end page

  • 51

volume

  • 137

number

  • 4