Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy

ObjectiveEsophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to...

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Published inGut Vol. 68; no. 12; pp. 2161 - 2169
Main Authors Wu, Lianlian, Zhang, Jun, Zhou, Wei, An, Ping, Shen, Lei, Liu, Jun, Jiang, Xiaoda, Huang, Xu, Mu, Ganggang, Wan, Xinyue, Lv, Xiaoguang, Gao, Juan, Cui, Ning, Hu, Shan, Chen, Yiyun, Hu, Xiao, Li, Jiangjie, Chen, Di, Gong, Dexin, He, Xinqi, Ding, Qianshan, Zhu, Xiaoyun, Li, Suqin, Wei, Xiao, Li, Xia, Wang, Xuemei, Zhou, Jie, Zhang, Mengjiao, Yu, Hong Gang
Format Journal Article
LanguageEnglish
Published England BMJ Publishing Group LTD 01.12.2019
BMJ Publishing Group
SeriesOriginal article
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Abstract ObjectiveEsophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to construct a real-time quality improving system, WISENSE, to monitor blind spots, time the procedure and automatically generate photodocumentation during EGD and thus raise the quality of everyday endoscopy.DesignWISENSE system was developed using the methods of deep convolutional neural networks and deep reinforcement learning. Patients referred because of health examination, symptoms, surveillance were recruited from Renmin hospital of Wuhan University. Enrolled patients were randomly assigned to groups that underwent EGD with or without the assistance of WISENSE. The primary end point was to ascertain if there was a difference in the rate of blind spots between WISENSE-assisted group and the control group.ResultsWISENSE monitored blind spots with an accuracy of 90.40% in real EGD videos. A total of 324 patients were recruited and randomised. 153 and 150 patients were analysed in the WISENSE and control group, respectively. Blind spot rate was lower in WISENSE group compared with the control (5.86% vs 22.46%, p<0.001), and the mean difference was −15.39% (95% CI −19.23 to −11.54). There was no significant adverse event.ConclusionsWISENSE significantly reduced blind spot rate of EGD procedure and could be used to improve the quality of everyday endoscopy.Trial registration numberChiCTR1800014809; Results.
AbstractList Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to construct a real-time quality improving system, WISENSE, to monitor blind spots, time the procedure and automatically generate photodocumentation during EGD and thus raise the quality of everyday endoscopy. WISENSE system was developed using the methods of deep convolutional neural networks and deep reinforcement learning. Patients referred because of health examination, symptoms, surveillance were recruited from Renmin hospital of Wuhan University. Enrolled patients were randomly assigned to groups that underwent EGD with or without the assistance of WISENSE. The primary end point was to ascertain if there was a difference in the rate of blind spots between WISENSE-assisted group and the control group. WISENSE monitored blind spots with an accuracy of 90.40% in real EGD videos. A total of 324 patients were recruited and randomised. 153 and 150 patients were analysed in the WISENSE and control group, respectively. Blind spot rate was lower in WISENSE group compared with the control (5.86% vs 22.46%, p<0.001), and the mean difference was -15.39% (95% CI -19.23 to -11.54). There was no significant adverse event. WISENSE significantly reduced blind spot rate of EGD procedure and could be used to improve the quality of everyday endoscopy. ChiCTR1800014809; Results.
Objective Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to construct a real-time quality improving system, WISENSE, to monitor blind spots, time the procedure and automatically generate photodocumentation during EGD and thus raise the quality of everyday endoscopy. Design WISENSE system was developed using the methods of deep convolutional neural networks and deep reinforcement learning. Patients referred because of health examination, symptoms, surveillance were recruited from Renmin hospital of Wuhan University. Enrolled patients were randomly assigned to groups that underwent EGD with or without the assistance of WISENSE. The primary end point was to ascertain if there was a difference in the rate of blind spots between WISENSE-assisted group and the control group. Results WISENSE monitored blind spots with an accuracy of 90.40% in real EGD videos. A total of 324 patients were recruited and randomised. 153 and 150 patients were analysed in the WISENSE and control group, respectively. Blind spot rate was lower in WISENSE group compared with the control (5.86% vs 22.46%, p<0.001), and the mean difference was −15.39% (95% CI −19.23 to −11.54). There was no significant adverse event. Conclusions WISENSE significantly reduced blind spot rate of EGD procedure and could be used to improve the quality of everyday endoscopy. Trial registration number ChiCTR1800014809; Results.
ObjectiveEsophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers and precursor lesions. The aim of this study was to construct a real-time quality improving system, WISENSE, to monitor blind spots, time the procedure and automatically generate photodocumentation during EGD and thus raise the quality of everyday endoscopy.DesignWISENSE system was developed using the methods of deep convolutional neural networks and deep reinforcement learning. Patients referred because of health examination, symptoms, surveillance were recruited from Renmin hospital of Wuhan University. Enrolled patients were randomly assigned to groups that underwent EGD with or without the assistance of WISENSE. The primary end point was to ascertain if there was a difference in the rate of blind spots between WISENSE-assisted group and the control group.ResultsWISENSE monitored blind spots with an accuracy of 90.40% in real EGD videos. A total of 324 patients were recruited and randomised. 153 and 150 patients were analysed in the WISENSE and control group, respectively. Blind spot rate was lower in WISENSE group compared with the control (5.86% vs 22.46%, p<0.001), and the mean difference was −15.39% (95% CI −19.23 to −11.54). There was no significant adverse event.ConclusionsWISENSE significantly reduced blind spot rate of EGD procedure and could be used to improve the quality of everyday endoscopy.Trial registration numberChiCTR1800014809; Results.
Author Lv, Xiaoguang
Li, Suqin
Zhou, Jie
An, Ping
Huang, Xu
Wu, Lianlian
Zhu, Xiaoyun
Hu, Shan
Zhang, Mengjiao
Ding, Qianshan
Liu, Jun
Jiang, Xiaoda
Gao, Juan
Li, Jiangjie
Mu, Ganggang
Cui, Ning
Wang, Xuemei
Gong, Dexin
Wei, Xiao
He, Xinqi
Zhou, Wei
Shen, Lei
Hu, Xiao
Wan, Xinyue
Yu, Hong Gang
Chen, Di
Chen, Yiyun
Li, Xia
Zhang, Jun
AuthorAffiliation 2 Key Laboratory of Hubei Province for Digestive System Disease , Renmin Hospital of Wuhan University , Wuhan , China
1 Department of Gastroenterology , Renmin Hospital of Wuhan University , Wuhan , China
3 Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision , Wuhan University Renmin Hospital , Wuhan , China
4 School of Resources and Environmental Sciences of Wuhan University , Wuhan , China
AuthorAffiliation_xml – name: 1 Department of Gastroenterology , Renmin Hospital of Wuhan University , Wuhan , China
– name: 3 Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision , Wuhan University Renmin Hospital , Wuhan , China
– name: 4 School of Resources and Environmental Sciences of Wuhan University , Wuhan , China
– name: 2 Key Laboratory of Hubei Province for Digestive System Disease , Renmin Hospital of Wuhan University , Wuhan , China
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  organization: Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Wuhan University Renmin Hospital, Wuhan, China
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  organization: Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Wuhan University Renmin Hospital, Wuhan, China
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  organization: Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Wuhan University Renmin Hospital, Wuhan, China
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  organization: Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Wuhan University Renmin Hospital, Wuhan, China
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  email: yuhonggang1968@163.com
  organization: Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Wuhan University Renmin Hospital, Wuhan, China
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30858305$$D View this record in MEDLINE/PubMed
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Snippet ObjectiveEsophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant...
Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant variations in EGD...
Objective Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions. However, there are significant...
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SourceType Open Access Repository
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Publisher
StartPage 2161
SubjectTerms Colonoscopy
Decision making
Deep learning
Dopamine
Efficiency
Endoscopy
Gastric cancer
Gastroenterology
Human body
Hypotheses
Neural networks
Polyps
Quality
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Title Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy
URI http://dx.doi.org/10.1136/gutjnl-2018-317366
https://www.ncbi.nlm.nih.gov/pubmed/30858305
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