Computer-Aided Detection of Colorectal Polyps at CT Colonography: Prospective Clinical Performance and Third-Party Reimbursement

AJR Am J Roentgenol. 2017 Jun;208(6):1244-1248. doi: 10.2214/AJR.16.17499.

Abstract

Objective: We assessed the initial clinical performance and third-party reimbursement rates of supplementary computer-aided detection (CAD) at CT colonography (CTC) for detecting colorectal polyps 6 mm or larger in routine clinical practice.

Materials and methods: We retrospectively assessed the prospective clinical performance of a U.S. Food and Drug Administration-approved CAD system in second-reader mode in 347 consecutive adults (mean age, 57.6 years; 205 women, 142 men) undergoing CTC evaluation over a 5-month period. The reference standard consisted of the prospective interpretation by experienced CTC radiologists combined with subsequent optical colonoscopy (OC), if performed. We also assessed third-party reimbursement for CAD for studies performed over an 18-month period.

Results: In all, 69 patients (mean [± SD] age, 59.0 ± 7.7 years; 32 men, 37 women) had 129 polyps ≥ 6 mm. Per-patient CAD sensitivity was 91.3% (63 of 69). Per-polyp CAD-alone sensitivity was 88.4% (114 of 129), including 88.3% (83 of 94) for 6- to 9-mm polyps and 88.6% (31 of 35) for polyps 10 mm or larger. On retrospective review, three additional polyps 6 mm or larger were seen at OC and marked by CAD but dismissed as CAD false-positives at CTC. The mean number of false-positive CAD marks was 4.4 ± 3.1 per series. Of 1225 CTC cases reviewed for reimbursement, 31.0% of the total charges for CAD interpretation had been recovered from a variety of third-party payers.

Conclusion: In our routine clinical practice, CAD showed good sensitivity for detecting colorectal polyps 6 mm or larger, with an acceptable number of false-positive marks. Importantly, CAD is already being reimbursed by some third-party payers in our clinical CTC practice.

Keywords: CT; colonography; computer-aided detection; polyps; screening.

MeSH terms

  • Colonography, Computed Tomographic / economics*
  • Colonography, Computed Tomographic / statistics & numerical data
  • Colorectal Neoplasms / diagnostic imaging*
  • Colorectal Neoplasms / economics*
  • Female
  • Humans
  • Insurance, Health, Reimbursement / economics*
  • Insurance, Health, Reimbursement / statistics & numerical data
  • Intestinal Polyps / diagnostic imaging*
  • Intestinal Polyps / economics*
  • Machine Learning / economics
  • Machine Learning / statistics & numerical data
  • Male
  • Radiographic Image Interpretation, Computer-Assisted / statistics & numerical data
  • Reproducibility of Results
  • Sensitivity and Specificity
  • United States / epidemiology