Cystic Lung Diseases: Algorithmic Approach. Review uri icon

Overview

abstract

  • Cysts are commonly seen on CT scans of the lungs, and diagnosis can be challenging. Clinical and radiographic features combined with a multidisciplinary approach may help differentiate among various disease entities, allowing correct diagnosis. It is important to distinguish cysts from cavities because they each have distinct etiologies and associated clinical disorders. Conditions such as emphysema, and cystic bronchiectasis may also mimic cystic disease. A simplified classification of cysts is proposed. Cysts can occur in greater profusion in the subpleural areas, when they typically represent paraseptal emphysema, bullae, or honeycombing. Cysts that are present in the lung parenchyma but away from subpleural areas may be present without any other abnormalities on high-resolution CT scans. These are further categorized into solitary or multifocal/diffuse cysts. Solitary cysts may be incidentally discovered and may be an age related phenomenon or may be a remnant of prior trauma or infection. Multifocal/diffuse cysts can occur with lymphoid interstitial pneumonia, Birt-Hogg-Dubé syndrome, tracheobronchial papillomatosis, or primary and metastatic cancers. Multifocal/diffuse cysts may be associated with nodules (lymphoid interstitial pneumonia, light-chain deposition disease, amyloidosis, and Langerhans cell histiocytosis) or with ground-glass opacities (Pneumocystis jirovecii pneumonia and desquamative interstitial pneumonia). Using the results of the high-resolution CT scans as a starting point, and incorporating the patient's clinical history, physical examination, and laboratory findings, is likely to narrow the differential diagnosis of cystic lesions considerably.

publication date

  • May 13, 2016

Research

keywords

  • Algorithms
  • Cysts
  • Lung
  • Lung Diseases

Identity

PubMed Central ID

  • PMC7534033

Scopus Document Identifier

  • 84994501728

Digital Object Identifier (DOI)

  • 10.1016/j.chest.2016.04.026

PubMed ID

  • 27180915

Additional Document Info

volume

  • 150

issue

  • 4