Lung nodule and cancer detection in computed tomography screening

Research output: Contribution to journalArticlepeer-review

66 Scopus citations

Abstract

Fundamental to the diagnosis of lung cancer in computed tomography (CT) scans is the detection and interpretation of lung nodules. As the capabilities of CT scanners have advanced, higher levels of spatial resolution reveal tinier lung abnormalities. Not all detected lung nodules should be reported; however, radiologists strive to detect all nodules that might have relevance to cancer diagnosis. Although medium to large lung nodules are detected consistently, interreader agreement and reader sensitivity for lung nodule detection diminish substantially as the nodule size falls below 8 to 10mm. The difficulty in establishing an absolute reference standard presents a challenge to the reliability of studies performed to evaluate lung nodule detection. In the interest of improving detection performance, investigators are using eye tracking to analyze the effectiveness with which radiologists search CT scans relative to their ability to recognize nodules within their search path in order to determine whether strategies might exist to improve performance across readers. Beyond the viewing of transverse CT reconstructions, image processing techniques such as thin-slab maximum-intensity projections are used to substantially improve reader performance. Finally, the development of computer-aided detection has continued to evolve with the expectation that one day it will serve routinely as a tireless partner to the radiologist to enhance detection performance without significant prolongation of the interpretive process. This review provides an introduction to the current understanding of these varied issues as we enter the era of widespread lung cancer screening.

Original languageEnglish (US)
Pages (from-to)130-138
Number of pages9
JournalJournal of Thoracic Imaging
Volume30
Issue number2
DOIs
StatePublished - Mar 6 2015
Externally publishedYes

Keywords

  • computed tomography
  • computer-Aided detection
  • eye tracking
  • image processing
  • lung cancer
  • lung nodule
  • pulmonary nodule

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Pulmonary and Respiratory Medicine

Fingerprint

Dive into the research topics of 'Lung nodule and cancer detection in computed tomography screening'. Together they form a unique fingerprint.

Cite this