Artificial intelligence for dysplasia detection during surveillance colonoscopy in patients with ulcerative colitis: A cross-sectional, non-inferiority, diagnostic test comparison study

Antonio López-Serrano; Alba Voces; José Ramón Lorente; Francisco José Santonja; Angela Algarra; Patricia Latorre; Pablo Del Pozo; José María Paredes

doi:10.1016/j.gastrohep.2024.502210

Artificial intelligence for dysplasia detection during surveillance colonoscopy in patients with ulcerative colitis: A cross-sectional, non-inferiority, diagnostic test comparison study

Gastroenterol Hepatol. 2024 May 11:S0210-5705(24)00168-7. doi: 10.1016/j.gastrohep.2024.502210. Online ahead of print.

[Article in English, Spanish]

Authors

Antonio López-Serrano¹, Alba Voces², José Ramón Lorente², Francisco José Santonja³, Angela Algarra², Patricia Latorre², Pablo Del Pozo², José María Paredes²

Affiliations

¹ Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain; Department of Medicine, Universitat de Valencia, Valencia, Spain. Electronic address: anlopezs@comv.es.
² Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain.
³ Statistics and Operational Research Department, Universitat de Valencia, Valencia, Spain.

PMID: 38740327
DOI: 10.1016/j.gastrohep.2024.502210

Abstract

Background and study aim: High-definition virtual chromoendoscopy, along with targeted biopsies, is recommended for dysplasia surveillance in ulcerative colitis patients at risk for colorectal cancer. Computer-aided detection (CADe) systems aim to improve colonic adenoma detection, however their efficacy in detecting polyps and adenomas in this context remains unclear. This study evaluates the CADe Discovery™ system's effectiveness in detecting colonic dysplasia in ulcerative colitis patients at risk for colorectal cancer.

Patients and methods: A prospective cross-sectional, non-inferiority, diagnostic test comparison study was conducted on ulcerative colitis patients undergoing colorectal cancer surveillance colonoscopy between January 2021 and April 2021. Patients underwent virtual chromoendoscopy (VCE) with iSCAN 1 and 3 with optical enhancement. One endoscopist, blinded to CADe Discovery™ system results, examined colon sections, while a second endoscopist concurrently reviewed CADe images. Suspicious areas detected by both techniques underwent resection. Proportions of dysplastic lesions and patients with dysplasia detected by VCE or CADe were calculated.

Results: Fifty-two patients were included, and 48 lesions analyzed. VCE and CADe each detected 9 cases of dysplasia (21.4% and 20.0%, respectively; p=0.629) in 8 patients and 7 patients (15.4% vs. 13.5%, respectively; p=0.713). Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy for dysplasia detection using VCE or CADe were 90% and 90%, 13% and 5%, 21% and 2%, 83% and 67%, and 29.2% and 22.9%, respectively.

Conclusions: The CADe Discovery™ system shows similar diagnostic performance to VCE with iSCAN in detecting colonic dysplasia in ulcerative colitis patients at risk for colorectal cancer.

Keywords: Artificial intelligence; Colitis ulcerosa; Colitis-associated neoplasm; Colonoscopia; Colonoscopy; Cromoendoscopia virtual; Inteligencia artificial; Neoplasia asociada a colitis; Ulcerative colitis; Virtual chromoendoscopy.