Early lung cancer detection, mucosal, and alveolar imaging

Alejandro H. Sardi, Shaheen Islam

Research output: Contribution to journalReview articlepeer-review

10 Scopus citations

Abstract

Purpose of review Lung cancer is the leading cause of cancer deaths worldwide. Early detection is essential for long-term survival. Screening of high-risk individuals with low-dose computed tomography screening has proven to increase survival. However, current radiological imaging techniques have poor specificity for lung cancer detection and poor sensitivity for detection of mucosal or alveolar preinvasive malignant lesions. Bronchoscopy allows imaging and sampling of early lung cancer, with the highest safety profile and high diagnostic accuracy. Recent findings Available technologies, such as autofluorescence bronchoscopy, narrow band imaging, and radial ultrasound bronchoscopy can significantly increase the yield and diagnostic accuracy of bronchoscopy for early cancer detection in the central airways. Newer technologies such as optical coherence tomography, confocal bronchoscopy, and Raman spectroscopy may significantly increase the diagnostic yield of both central and parenchymal early cancer lesions. Summary Although some of these technologies are still investigational and are not readily available in most centers, they may identify early mucosal and alveolar cancer lesions accurately in the least invasive manner to provide appropriate therapy and prolong patient survival from lung cancer.

Original languageEnglish (US)
Pages (from-to)271-280
Number of pages10
JournalCurrent Opinion in Pulmonary Medicine
Volume22
Issue number3
DOIs
StatePublished - May 1 2016
Externally publishedYes

Keywords

  • bronchoscopy
  • confocal bronchoscopy
  • early detection of lung cancer
  • mucosal and alveolar imaging
  • optical coherence tomography

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Fingerprint

Dive into the research topics of 'Early lung cancer detection, mucosal, and alveolar imaging'. Together they form a unique fingerprint.

Cite this