Assessment of the incremental benefit of computer-aided detection (CAD) for interpretation of CT colonography by experienced and inexperienced readers

Darren Boone, Susan Mallett, Justine McQuillan, Stuart A. Taylor, Douglas G. Altman, Steve Halligan

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Objectives: To quantify the incremental benefit of computer-assisted-detection (CAD) for polyps, for inexperienced readers versus experienced readers of CT colonography. Methods: 10 inexperienced and 16 experienced radiologists interpreted 102 colonography studies unassisted and with CAD utilised in a concurrent paradigm. They indicated any polyps detected on a study sheet. Readers' interpretations were compared against a ground-truth reference standard: 46 studies were normal and 56 had at least one polyp (132 polyps in total). The primary study outcome was the difference in CAD net benefit (a combination of change in sensitivity and change in specificity with CAD, weighted towards sensitivity) for detection of patients with polyps. Results: Inexperienced readers' per-patient sensitivity rose from 39.1% to 53.2% with CAD and specificity fell from 94.1 % to 88.0%, both statistically significant. Experienced readers' sensitivity rose from 57.5% to 62.1% and specificity fell from 91.0% to 88.3%, both non-significant. Net benefit with CAD assistance was significant for inexperienced readers but not for experienced readers: 11.2% (95%CI 3.1% to 18.9%) versus 3.2% (95%CI-1.9% to 8.3%) respectively. Conclusions: Concurrent CAD resulted in a significant net benefit when used by inexperienced readers to identify patients with polyps by CT colonography. The net benefit was nearly four times the magnitude of that observed for experienced readers. Experienced readers did not benefit significantly from concurrent CAD.

Original languageEnglish
Article numbere0136624
JournalPLoS ONE
Volume10
Issue number9
DOIs
Publication statusPublished - 10 Sep 2015

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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