Real-time computer-aided diagnosis of diminutive rectosigmoid polyps using an auto-fluorescence imaging system and novel color intensity analysis software

Abstract

Objectives: An endoscopic technique that provides ≥90% negative predictive value (NPV) for differentiating neoplastic polyps is needed for the management of diminutive (≤5 mm) rectosigmoid polyps. This study aimed to assess whether a newly developed software can achieve ≥90% NPV for differentiating rectosigmoid diminutive polyps based on the green-to-red (G/R) ratio, obtained by dividing the green color tone intensity by the red color tone intensity on autofluorescence imaging (AFI).

Methods: From December 2017 to May 2018, consecutive patients with known polyps who were scheduled for endoscopic treatment at our institution were prospectively recruited. All colorectal diminutive polyps were differentiated by computer-aided diagnosis using autofluorescence imaging (CAD-AFI) using a novel software-based automatic color intensity analysis; subsequent diagnosis was made by endoscopists based on trimodal imaging endoscopy (TME), which combines AFI, white-light imaging (WLI) and magnifying narrow-band imaging (M-NBI) findings. Thereafter, all polyps were removed endoscopically, and the histopathological diagnosis was evaluated.

Results: Ninety-five patients with 258 diminutive rectosigmoid polyps and 171 diminutive non-rectosigmoid polyps were enrolled. Regarding diminutive rectosigmoid polyps, the NPV for differentiating neoplastic polyps was 93.4% (184/197) [95% confidence interval (CI), 89.0%–96.4%] with CAD-AFI and 94.9% (185/195) (95% CI, 90.8%–97.5%) with TME. The accuracy, sensitivity, specificity, and positive predictive value for differentiating diminutive rectosigmoid neoplastic polyps by CAD-AFI were 91.5%, 80.0%, 95.3% and 85.2%, respectively.

Conclusions: Real-time CAD-AFI was effective for differentiating diminutive rectosigmoid polyps. This objective technology, which does not require extensive training or endoscopic expertise, can contribute to the effective management of diminutive rectosigmoid polyps.

Keywords:

• Computer-aided diagnosis
• diminutive
• polyp differentiation
• negative predictive value
• auto-fluorescence imaging

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was supported by research funds from Jikei University.