Computer-aided detection of colorectal polyps in CT colonography with and without fecal tagging: A stand-alone evaluation

Thomas Mang, Luca Bogoni, Marcos Salganicoff, Matthias Wolf, Vikas Raykar, Michael MacAri, Perry J. Pickhardt, Franco Iafrate, Andrea Laghi, Michael Weber, Mark E. Baker, Helmut Ringl, Christian J. Herold, Anno Graser

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To evaluate the stand-alone performance of a computer-aided detection (CAD) algorithm for colorectal polyps in a large heterogeneous CT colonography (CTC) database that included both tagged and untagged datasets. Methods: Written, informed consent was waived for this institutional review board-approved, HIPAA-compliant retrospective study. CTC datasets from 2063 patients were assigned to training (n = 374) and testing (n = 1689). The test set consisted of 836 untagged and 853 tagged examinations not used for CAD training. Examinations were performed at 15 sites in the United States, Asia, and Europe, using 4-to 64-multidetector-row computed tomography and various acquisition parameters. CAD sensitivities were calculated on a per-patient and per-polyp basis for polyps measuring ≥6 mm. The reference standard was colonoscopy in 1588 (94%) and consensus interpretation by expert radiologists in 101 (6%) patients. Statistical testing employed χ 2, logistic regression, and Mann-Whitney U tests. Results: In 383 of 1689 individuals, 564 polyps measuring ≥6 mm were identified by the reference standard (347 polyps: 6-9 mm and 217 polyps: ≥10 mm). Overall, CAD per-patient sensitivity was 89.6% (343/383), with 89.0% (187/210) for untagged and 90.2% (156/173) for tagged datasets (P = 0.72). Overall, per-polyp sensitivity was 86.9% (490/564), with 84.4% (270/320) for untagged and 90.2% (220/244) for tagged examinations (P = 068). The mean false-positive rate per patient was 5.14 (median, 4) in untagged and 4.67 (median, 4) in tagged patient datasets (P = 0.353). Conclusion: Stand-alone CAD can be applied to both tagged and untagged CTC studies without significant performance differences. Detection rates are comparable to human readers at a relatively low false-positive rate, making CAD a useful tool in clinical practice.

Original languageEnglish (US)
Pages (from-to)99-108
Number of pages10
JournalInvestigative radiology
Volume47
Issue number2
DOIs
StatePublished - Feb 2012

Keywords

  • CT colonography
  • colorectal cancer
  • colorectal polyps
  • computer-aided detection
  • virtual colonoscopy

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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