Background:In colonoscopy screening for colorectal cancer,human vision limitationsmay lead to highermiss rate of lesions;artificial intelligence(AI)assistance has been demonstrated to improve polyp detection.However,t...Background:In colonoscopy screening for colorectal cancer,human vision limitationsmay lead to highermiss rate of lesions;artificial intelligence(AI)assistance has been demonstrated to improve polyp detection.However,there still lacks direct evidence to demonstrate whether AI is superior to trainees or experienced nurses as a second observer to increase adenoma detection during colonoscopy.In this study,we aimed to compare the effectiveness of assistance fromAI and human observer during colonoscopy.Methods:A prospective multicenter randomized study was conducted from 2 September 2019 to 29 May 2020 at four endoscopy centers in China.Eligible patients were randomized to either computer-aided detection(CADe)-assisted group or observer-assisted group.The primary outcome was adenoma per colonoscopy(APC).Secondary outcomes included polyp per colonoscopy(PPC),adenoma detection rate(ADR),and polyp detection rate(PDR).We compared continuous variables and categorical variables by using R studio(version 3.4.4).Results:A total of 1,261(636 in the CADe-assisted group and 625 in the observer-assisted group)eligible patients were analysed.APC(0.42 vs 0.35,P=0.034),PPC(1.13 vs 0.81,P<0.001),PDR(47.5%vs 37.4%,P<0.001),ADR(25.8%vs 24.0%,P=0.464),the number of detected sessile polyps(683 vs 464,P<0.001),and sessile adenomas(244 vs 182,P=0.005)were significantly higher in the CADe-assisted group than in the observer-assisted group.False detections of the CADe system were lower than those of the human observer(122 vs 191,P<0.001).Conclusions:Compared with the human observer,the CADe system may improve the clinical outcome of colonoscopy and reduce disturbance to routine practice(Chictr.org.cn No.:ChiCTR1900025235).展开更多
文摘Background:In colonoscopy screening for colorectal cancer,human vision limitationsmay lead to highermiss rate of lesions;artificial intelligence(AI)assistance has been demonstrated to improve polyp detection.However,there still lacks direct evidence to demonstrate whether AI is superior to trainees or experienced nurses as a second observer to increase adenoma detection during colonoscopy.In this study,we aimed to compare the effectiveness of assistance fromAI and human observer during colonoscopy.Methods:A prospective multicenter randomized study was conducted from 2 September 2019 to 29 May 2020 at four endoscopy centers in China.Eligible patients were randomized to either computer-aided detection(CADe)-assisted group or observer-assisted group.The primary outcome was adenoma per colonoscopy(APC).Secondary outcomes included polyp per colonoscopy(PPC),adenoma detection rate(ADR),and polyp detection rate(PDR).We compared continuous variables and categorical variables by using R studio(version 3.4.4).Results:A total of 1,261(636 in the CADe-assisted group and 625 in the observer-assisted group)eligible patients were analysed.APC(0.42 vs 0.35,P=0.034),PPC(1.13 vs 0.81,P<0.001),PDR(47.5%vs 37.4%,P<0.001),ADR(25.8%vs 24.0%,P=0.464),the number of detected sessile polyps(683 vs 464,P<0.001),and sessile adenomas(244 vs 182,P=0.005)were significantly higher in the CADe-assisted group than in the observer-assisted group.False detections of the CADe system were lower than those of the human observer(122 vs 191,P<0.001).Conclusions:Compared with the human observer,the CADe system may improve the clinical outcome of colonoscopy and reduce disturbance to routine practice(Chictr.org.cn No.:ChiCTR1900025235).
