After Detection: The Improved Accuracy of Lung Cancer Assessment Using Radiologic Computer-aided Diagnosis

Acad Radiol. 2016 Feb;23(2):186-91. doi: 10.1016/j.acra.2015.10.014. Epub 2015 Nov 23.

Abstract

Rationale and objectives: The aim of this study was to evaluate the improved accuracy of radiologic assessment of lung cancer afforded by computer-aided diagnosis (CADx).

Materials and methods: Inclusion/exclusion criteria were formulated, and a systematic inquiry of research databases was conducted. Following title and abstract review, an in-depth review of 149 surviving articles was performed with accepted articles undergoing a Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-based quality review and data abstraction.

Results: A total of 14 articles, representing 1868 scans, passed the review. Increases in the receiver operating characteristic (ROC) area under the curve of .8 or higher were seen in all nine studies that reported it, except for one that employed subspecialized radiologists.

Conclusions: This systematic review demonstrated improved accuracy of lung cancer assessment using CADx over manual review, in eight high-quality observer-performance studies. The improved accuracy afforded by radiologic lung-CADx suggests the need to explore its use in screening and regular clinical workflow.

Keywords: Computer-aided; cancer; imaging; lung; medical.

Publication types

  • Research Support, N.I.H., Extramural
  • Review
  • Systematic Review

MeSH terms

  • Diagnosis, Computer-Assisted / statistics & numerical data
  • Humans
  • Image Processing, Computer-Assisted / statistics & numerical data
  • Lung Neoplasms / diagnostic imaging*
  • ROC Curve
  • Radiographic Image Interpretation, Computer-Assisted / standards*
  • Radiography, Thoracic / statistics & numerical data
  • Tomography, X-Ray Computed / statistics & numerical data