Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial

• Published in: Gastroenterology (New York, N.Y. 1943) Vol. 159; no. 2; pp. 512 - 520.e7
• Main Authors: Repici, Alessandro, Badalamenti, Matteo, Maselli, Roberta, Correale, Loredana, Radaelli, Franco, Rondonotti, Emanuele, Ferrara, Elisa, Spadaccini, Marco, Alkandari, Asma, Fugazza, Alessandro, Anderloni, Andrea, Galtieri, Piera Alessia, Pellegatta, Gaia, Carrara, Silvia, Di Leo, Milena, Craviotto, Vincenzo, Lamonaca, Laura, Lorenzetti, Roberto, Andrealli, Alida, Antonelli, Giulio, Wallace, Michael, Sharma, Prateek, Rosch, Thomas, Hassan, Cesare
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.08.2020
• Subjects: Adenoma - diagnosis; Adenoma - epidemiology; Adenoma - pathology; Adenoma Per Colonoscopy; Aged; Artificial Intelligence; Biopsy - statistics & numerical data; Colon - diagnostic imaging; Colon - pathology; Colonoscopy - instrumentation; Colonoscopy - methods; Colonoscopy - statistics & numerical data; Colorectal Neoplasms - diagnosis; Colorectal Neoplasms - epidemiology; Colorectal Neoplasms - pathology; Comparison; Deep Learning; Early Detection; Female; Humans; Image Interpretation, Computer-Assisted - instrumentation; Image Interpretation, Computer-Assisted - methods; Image Interpretation, Computer-Assisted - statistics & numerical data; Male; Mass Screening - instrumentation; Mass Screening - methods; Mass Screening - statistics & numerical data; Middle Aged; Time Factors; Adenoma Per Colonoscopy; Early Detection; FIT; CADe; RR; APC; Comparison; CRC; Artificial Intelligence; CI; SSL; ADR

One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Deep learning systems allow for real-time computer-aided detection (CADe) of polyps with high accuracy. We performed a multicenter, randomized trial to assess the safety and...