Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study

Endoscopy. 2016 Dec;48(12):1110-1118. doi: 10.1055/s-0042-113609. Epub 2016 Aug 5.

Abstract

Background and study aims: Optical diagnosis of colorectal polyps is expected to improve the cost-effectiveness of colonoscopy, but achieving a high accuracy is difficult for trainees. Computer-aided diagnosis (CAD) is therefore receiving attention as an attractive tool. This study aimed to validate the efficacy of the latest CAD model for endocytoscopy (380-fold ultra-magnifying endoscopy). Patients and methods: This international web-based trial was conducted between August and November 2015. A web-based test comprising one white-light and one endocytoscopic image of 205 small colorectal polyps (≤ 10 mm) from 123 patients was undertaken by both CAD and by endoscopists (three experts and ten non-experts from three countries). Outcome measures were accuracy in identifying neoplastic change in diminutive (≤ 5 mm) and small (≤ 10 mm) polyps, and accuracy in predicting post-polypectomy surveillance intervals according to current guidelines for high confidence optical diagnoses of diminutive polyps. Results: Of the 205 small polyps (147 neoplastic and 58 non-neoplastic), 139 were diminutive. CAD was accurate for 89 % (95 % confidence interval [CI] 83 % - 94 %) of diminutive polyps and 89 % (84 % - 93 %) of small polyps, which was significantly greater than results for the non-experts (73 % [71 % - 76 %], P < 0.001; and 76 % [74 % - 78 %], P < 0.001, respectively) and comparable with the experts' results (90 % [87 % - 93 %], P = 0.703; and 91 % [89 % - 93 %], P = 0.106, respectively). The surveillance interval predicted by CAD provided 98 % (93 % - 100 %) and 96 % (91 % - 99 %) agreement with pathology-directed intervals of the European and American guidelines, respectively. Conclusions: The use of CAD in endocytoscopy can be effective in the management of diminutive/small colorectal polyps.UMIN Clinical Trial Registry: UMIN000018185.

Publication types

  • Clinical Trial
  • Multicenter Study
  • Validation Study
  • Video-Audio Media

MeSH terms

  • Adenoma / diagnostic imaging*
  • Adenoma / pathology
  • Aged
  • Colonic Neoplasms / diagnostic imaging*
  • Colonic Neoplasms / pathology
  • Colonic Polyps / diagnostic imaging*
  • Colonic Polyps / pathology
  • Colonoscopy
  • Diagnosis, Computer-Assisted*
  • Female
  • Humans
  • Internationality
  • Internet
  • Male
  • Middle Aged
  • Observer Variation
  • Optical Imaging
  • Population Surveillance*
  • Practice Guidelines as Topic
  • Rectal Neoplasms / diagnostic imaging*
  • Rectal Neoplasms / pathology
  • Tumor Burden