Uso de inteligencia artificial en tiempo real durante la colonoscopia para la detección y caracterización de pólipos colorrectales. - Mauricio Aponte-Martín, Diego; Sebastián Salas-Robayo, Juan; Gaitán, Laura; Judith Huertas-Pacheco, Sandra; Carolina Córdoba, Andrea; Vergara, Hernán; Valentina Aponte-Aparicio, María; Carlos Sabbagh, Luis (Revista Colombiana de Gastroenterología)
Introduction: Colorectal cancer represents a significant public health concern in Colombia and worldwide. The detection and resection of adenomatous polyps via colonoscopy have contributed to reducing the incidence and mortality associated with colorectal cancer. Recently, numerous studies have been published regarding the use of artificial intelligence (AI) for detecting adenomatous polyps during colonoscopy; however, data on this topic in South America remain scarce. Materials and Methods: We conducted a prospective, descriptive study including patients over 45 years of age who underwent colonoscopy for colorectal cancer screening assisted by a real-time polyp detection system (Computer-Aided Detection, CAD EYE, Fujifilm, Tokyo, Japan) at two tertiary referral centers between May 2023 and June 2024. Demographic and procedural variables were recorded. The diagnostic performance of this tool was assessed through analysis of sensitivity, specificity, likelihood ratios, adenoma detection rate (ADR), polyp detection rate (PDR), and receiver operating characteristic (ROC) curves for lesion characterization (neoplastic and non-neoplastic). Results: A total of 86 patients were included in the final analysis. Of these, 80.2% (n = 69) were female, with a mean age of 63 years (± 9.83). The PDR with CAD EYE was 58.1%, whereas the ADR was 38.4% The concordance rate between AI and histopathology for lesions classified as neoplastic or hyperplastic was 73.13%. AI-based categorization of colorectal lesions as neoplastic demonstrated a sensitivity of 78.8% and specificity of 83.1%, with an area under the curve (AUC) of 0.73 (95% confidence interval [CI]: 0.686-0.882). Compared with the ADR previously reported by two of the study authors, the use of AI increased adenoma detection by more than 10%. Conclusion: This is the first study in Colombia evaluating the use of real-time AI software during colonoscopy, demonstrating a significant improvement in both ADR and PDR. Current evidence, alongside the findings of this study, indicates a promising discriminative ability for AI-assisted characterization of colonic polyps.