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The single-monitor trial: an embedded CADe system increased adenoma detection during colonoscopy: a prospective randomized study.

作者信息

Liu Peixi, Wang Pu, Glissen Brown Jeremy R, Berzin Tyler M, Zhou Guanyu, Liu Weihui, Xiao Xun, Chen Ziyang, Zhang Zhihong, Zhou Chao, Lei Lei, Xiong Fei, Li Liangping, Liu Xiaogang

机构信息

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, Sichuan, China.

Department of Gastroenterology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, No.32 West Second Section First Ring Road, Chengdu, Sichuan, China.

出版信息

Therap Adv Gastroenterol. 2020 Dec 15;13:1756284820979165. doi: 10.1177/1756284820979165. eCollection 2020.


DOI:10.1177/1756284820979165
PMID:33403003
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7745558/
Abstract

BACKGROUND: Computer-aided detection (CADe) of colon polyps has been demonstrated to improve colon polyp and adenoma detection during colonoscopy by indicating the location of a given polyp on a parallel monitor. The aim of this study was to investigate whether embedding the CADe system into the primary colonoscopy monitor may serve to increase polyp and adenoma detection, without increasing physician fatigue level. METHODS: Consecutive patients presenting for colonoscopies were prospectively randomized to undergo routine colonoscopy with or without the assistance of a real-time polyp detection CADe system. Fatigue level was evaluated from score 0 to 10 by the performing endoscopists after each colonoscopy procedure. The main outcome was adenoma detection rate (ADR). RESULTS: Out of 790 patients analyzed, 397 were randomized to routine colonoscopy (control group), and 393 to a colonoscopy with computer-aided diagnosis (CADe group). The ADRs were 20.91% and 29.01%, respectively (OR = 1.546, 95% CI 1.116-2.141,  = 0.009). The average number of adenomas per colonoscopy (APC) was 0.29 and 0.48, respectively (Change Folds = 1.64, 95% CI 1.299-2.063,  < 0.001). The improvement in polyp detection was mainly due to increased detection of non-advanced diminutive adenomas, serrated adenoma and hyperplastic polyps. The fatigue score for each procedure was 3.28 3.40 for routine and CADe group,  = 0.357. CONCLUSIONS: A real-time CADe system employed on the primary endoscopy monitor may lead to improvements in ADR and polyp detection rate without increasing fatigue level during colonoscopy. The integration of a low-latency and high-performance CADe systems may serve as an effective quality assurance tool during colonoscopy. www.chictr.org.cn number, ChiCTR1800018058.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93c5/7745558/73d83fd7dc59/10.1177_1756284820979165-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93c5/7745558/69d2a1889e44/10.1177_1756284820979165-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93c5/7745558/73d83fd7dc59/10.1177_1756284820979165-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93c5/7745558/69d2a1889e44/10.1177_1756284820979165-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93c5/7745558/73d83fd7dc59/10.1177_1756284820979165-fig2.jpg

相似文献

[1]
The single-monitor trial: an embedded CADe system increased adenoma detection during colonoscopy: a prospective randomized study.

Therap Adv Gastroenterol. 2020-12-15

[2]
Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.

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[3]
Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

Lancet Gastroenterol Hepatol. 2020-1-22

[4]
Effect of Real-Time Computer-Aided Polyp Detection System (ENDO-AID) on Adenoma Detection in Endoscopists-in-Training: A Randomized Trial.

Clin Gastroenterol Hepatol. 2024-3

[5]
Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).

Clin Gastroenterol Hepatol. 2022-7

[6]
Real-time use of a computer-aided system for polyp detection during colonoscopy, an ambispective study.

J Dig Dis. 2021-5

[7]
Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis.

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[8]
Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

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[9]
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[10]
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Int J Colorectal Dis. 2022-10

引用本文的文献

[1]
Artificial intelligence for reducing missed detection of adenomas and polyps in colonoscopy: A systematic review and meta-analysis.

World J Gastroenterol. 2025-6-7

[2]
Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.

EClinicalMedicine. 2025-5-12

[3]
Artificial Intelligence in Colorectal Cancer: From Patient Screening over Tailoring Treatment Decisions to Identification of Novel Biomarkers.

Digestion. 2024

[4]
Single Versus Second Observer vs Artificial Intelligence to Increase the ADENOMA Detection Rate of Colonoscopy-A Network Analysis.

Dig Dis Sci. 2024-4

[5]
The absolute number of small and diminutive adenomas with high-grade dysplasia is substantially higher compared with large adenomas: a retrospective pooled study.

Front Oncol. 2024-2-12

[6]
Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.

Nat Commun. 2024-2-22

[7]
Artificial intelligence for colorectal neoplasia detection during colonoscopy: a systematic review and meta-analysis of randomized clinical trials.

EClinicalMedicine. 2023-11-30

[8]
The Role of Artificial Intelligence in Colorectal Cancer Screening: Lesion Detection and Lesion Characterization.

Cancers (Basel). 2023-10-24

[9]
Usefulness of AI-Equipped Endoscopy for Detecting Colorectal Adenoma during Colonoscopy Screening: Confirm That Colon Neoplasm Finely Can Be Identified by AI without Overlooking Study (Confidential Study).

J Clin Med. 2023-10-2

[10]
AI-clinician collaboration via disagreement prediction: A decision pipeline and retrospective analysis of real-world radiologist-AI interactions.

Cell Rep Med. 2023-10-17

本文引用的文献

[1]
Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.

Gastroenterology. 2020-10

[2]
Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.

Gastroenterology. 2020-8

[3]
Computer aided detection for laterally spreading tumors and sessile serrated adenomas during colonoscopy.

PLoS One. 2020-4-21

[4]
Introducing computer-aided detection to the endoscopy suite.

VideoGIE. 2020-2-14

[5]
Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.

Lancet Gastroenterol Hepatol. 2020-1-22

[6]
Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

Nat Biomed Eng. 2018-10-10

[7]
Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study.

Gut. 2019-2-27

[8]
Participation and yield of a population-based colorectal cancer screening programme in China.

Gut. 2018-10-30

[9]
Artificial intelligence in gastrointestinal endoscopy: The future is almost here.

World J Gastrointest Endosc. 2018-10-16

[10]
Gaze patterns hold key to unlocking successful search strategies and increasing polyp detection rate in colonoscopy.

Endoscopy. 2018-2-7

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