Several studies have shown a significant adenoma miss rate up to 35%during screening colonoscopy,especially in patients with diminutive adenomas.The use of artificial intelligence(AI)in colonoscopy has been gaining po...Several studies have shown a significant adenoma miss rate up to 35%during screening colonoscopy,especially in patients with diminutive adenomas.The use of artificial intelligence(AI)in colonoscopy has been gaining popularity by helping endoscopists in polyp detection,with the aim to increase their adenoma detection rate(ADR)and polyp detection rate(PDR)in order to reduce the incidence of interval cancers.The efficacy of deep convolutional neural network(DCNN)-based AI system for polyp detection has been trained and tested in ex vivo settings such as colonoscopy still images or videos.Recent trials have evaluated the real-time efficacy of DCNN-based systems showing promising results in term of improved ADR and PDR.In this review we reported data from the preliminary ex vivo experiences and summarized the results of the initial randomized controlled trials.展开更多
Barrett’s esophagus(BE)is a well-established risk factor for esophageal adenocarcinoma.It is recommended that patients have regular endoscopic surveillance,with the ultimate goal of detecting early-stage neoplastic l...Barrett’s esophagus(BE)is a well-established risk factor for esophageal adenocarcinoma.It is recommended that patients have regular endoscopic surveillance,with the ultimate goal of detecting early-stage neoplastic lesions before they can progress to invasive carcinoma.Detection of both dysplasia or early adenocarcinoma permits curative endoscopic treatments,and with this aim,thorough endoscopic assessment is crucial and improves outcomes.The burden of missed neoplasia in BE is still far from being negligible,likely due to inappropriate endoscopic surveillance.Over the last two decades,advanced imaging techniques,moving from traditional dye-spray chromoendoscopy to more practical virtual chromoendoscopy technologies,have been introduced with the aim to enhance neoplasia detection in BE.As witnessed in other fields,artificial intelligence(AI)has revolutionized the field of diagnostic endoscopy and is set to cover a pivotal role in BE as well.The aim of this commentary is to comprehensively summarize present evidence,recent research advances,and future perspectives regarding advanced imaging technology and AI in BE;the combination of computer-aided diagnosis to a widespread adoption of advanced imaging technologies is eagerly awaited.It will also provide a useful step-by-step approach for performing high-quality endoscopy in BE,in order to increase the diagnostic yield of endoscopy in clinical practice.展开更多
文摘Several studies have shown a significant adenoma miss rate up to 35%during screening colonoscopy,especially in patients with diminutive adenomas.The use of artificial intelligence(AI)in colonoscopy has been gaining popularity by helping endoscopists in polyp detection,with the aim to increase their adenoma detection rate(ADR)and polyp detection rate(PDR)in order to reduce the incidence of interval cancers.The efficacy of deep convolutional neural network(DCNN)-based AI system for polyp detection has been trained and tested in ex vivo settings such as colonoscopy still images or videos.Recent trials have evaluated the real-time efficacy of DCNN-based systems showing promising results in term of improved ADR and PDR.In this review we reported data from the preliminary ex vivo experiences and summarized the results of the initial randomized controlled trials.
文摘Barrett’s esophagus(BE)is a well-established risk factor for esophageal adenocarcinoma.It is recommended that patients have regular endoscopic surveillance,with the ultimate goal of detecting early-stage neoplastic lesions before they can progress to invasive carcinoma.Detection of both dysplasia or early adenocarcinoma permits curative endoscopic treatments,and with this aim,thorough endoscopic assessment is crucial and improves outcomes.The burden of missed neoplasia in BE is still far from being negligible,likely due to inappropriate endoscopic surveillance.Over the last two decades,advanced imaging techniques,moving from traditional dye-spray chromoendoscopy to more practical virtual chromoendoscopy technologies,have been introduced with the aim to enhance neoplasia detection in BE.As witnessed in other fields,artificial intelligence(AI)has revolutionized the field of diagnostic endoscopy and is set to cover a pivotal role in BE as well.The aim of this commentary is to comprehensively summarize present evidence,recent research advances,and future perspectives regarding advanced imaging technology and AI in BE;the combination of computer-aided diagnosis to a widespread adoption of advanced imaging technologies is eagerly awaited.It will also provide a useful step-by-step approach for performing high-quality endoscopy in BE,in order to increase the diagnostic yield of endoscopy in clinical practice.
