Computer-aided detection (CAD) as a second reader using perspective filet view at CT colonography: effect on performance of inexperienced readers

Clin Radiol. 2009 Oct;64(10):972-82. doi: 10.1016/j.crad.2009.05.012. Epub 2009 Aug 13.

Abstract

Aim: To evaluate whether computer-aided detection (CAD) as a second reader using perspective filet view [three-dimensional (3D) filet] improves the performance of inexperienced readers at computed tomography colonography (CTC) compared with unassisted 3D filet and unassisted two-dimensional (2D) CTC.

Material and methods: Fifty symptomatic patients underwent CTC and same-day colonoscopy with segmental unblinding. Two inexperienced readers read the CTC studies on 3D filet and 2D several weeks apart. Four months later, readers re-read the cases only evaluating CAD marks using 3D filet. Suspicious CAD marks not previously described on 3D filet were recorded. Jackknife free-response receiver operating characteristic (JAFROC-1) analysis was used to compare the observers' performances in detecting lesions with 3D filet, 2D and 3D filet with CAD.

Results: One hundred and three lesions > or =3mm were detected at colonoscopy with segmental unblinding. CAD alone had a sensitivity of 73% (75/103) at a mean false-positive rate per patient of 12.8 in supine and 11.4 in prone. For inexperienced readers sensitivities with 3D filet with CAD were 58% (60/103) and 48% (50/103) with an improvement of 14-16 percentage points (p<0.05) compared with 2D and of 10-11 percentage points (p<0.05) compared with 3D filet. For inexperienced readers, the false-positive rate was 25-41% and 71-200% higher with 3D filet with CAD compared with 3D filet and 2D, respectively. JAFROC-1 analysis showed no significant differences in per-lesion overall performance among reading modes (p=0.8).

Conclusion: CAD applied as a second reader using 3D filet increased both sensitivity and the number of false positives by inexperienced readers compared with 3D filet and 2D, thus not improving overall performance, i.e., the ability to distinguish between lesions and non-lesions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Clinical Competence
  • Colon / diagnostic imaging*
  • Colonography, Computed Tomographic* / methods
  • Colonography, Computed Tomographic* / statistics & numerical data
  • Colonoscopy / methods*
  • Female
  • Humans
  • Imaging, Three-Dimensional / methods
  • Male
  • Middle Aged
  • Observer Variation
  • Prospective Studies
  • ROC Curve
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Sensitivity and Specificity
  • Software