Comparison of Polyp Detection and False Alarm Rates in Water Exchange and Air Insufflation Colonoscopy

NCT04727814 | Unknown DMC

• 1 other identifier: B10903009
• Study Type: observational
• Target: 250
• Locations: 1 country
• Sites: 1

Brief Summary

Water exchange (WE) improves adenoma detection rate (ADR) but missed polyps occur due to human limitations. Computer-aided detection (CADe) improves polyp detection and can overcome human omissions, but a limiting factor is feces and air bubbles related false alarms (FA). WE provides salvage cleansing and can potentially reduce FA. The investigators compared the additional polyp detection rate (APDR) and false alarm rate (FAR) by CADe between WE and air insufflation.

Conditions

Colon Polyp

Keywords

water exchange, polyp detection rate

Outcome Measures

Primary Outcomes (1)

• Polyp detection rate

  To find out and compare the polyp detection rate on water exchange and air insufflation group

  One month

Secondary Outcomes (2)

• False positive rate of computer-aided detection system

  One month

• False alarm rate of computer-aided detection system

  One month

Study Arms (2)

Water exchange with computer-aided detection system

Computer-aided detection system overlaid videos with water exchange colonoscopy method

Other: Computer-aided detection system overlaid colonoscopy videos analysis

Air insufflation with computer-aided detection system

Computer-aided detection system overlaid videos with air insufflation colonoscopy method

Other: Computer-aided detection system overlaid colonoscopy videos analysis

Interventions

Computer-aided detection system overlaid colonoscopy videos analysis OTHER

Analysis of computer-aided detection system overlaid videos from colonoscopies performed with water exchange or air insufflation method.

Air insufflation with computer-aided detection system; Water exchange with computer-aided detection system

Eligibility Criteria

• Age: 40 Years - 80 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients were undergoing screen, diagnostic or surveillance colonoscopy were enrolled.

You may qualify if:

• Patients aged 40 to 80 years old, undergoing screen, diagnostic or surveillance colonoscopy were enrolled.

You may not qualify if:

• Patients were excluded in case of having colonoscopy in the past 3 years, renal failure, previous colonic resection, scheduled for polypectomy, partial intake of bowel preparation, American Society of Anesthesiology (ASA) Risk Class 3 or higher, and lack of written informed consent.

Sponsors & Collaborators

• Dalin Tzu Chi General Hospital: lead
• University of California: collaborator
• National Chiayi University: collaborator

Study Sites (1)

Chia Pei Tang

Chiayi City, Chiayi, 62247, Taiwan

Location

Related Publications (10)

• Cheng CL, Kuo YL, Hsieh YH, Tang JH, Leung FW. Comparison of Right Colon Adenoma Miss Rates Between Water Exchange and Carbon Dioxide Insufflation: A Prospective Randomized Controlled Trial. J Clin Gastroenterol. 2021 Nov-Dec 01;55(10):869-875. doi: 10.1097/MCG.0000000000001454.

  PMID: 33074950 BACKGROUND

• Hsieh YH, Tseng CW, Hu CT, Koo M, Leung FW. Prospective multicenter randomized controlled trial comparing adenoma detection rate in colonoscopy using water exchange, water immersion, and air insufflation. Gastrointest Endosc. 2017 Jul;86(1):192-201. doi: 10.1016/j.gie.2016.12.005. Epub 2016 Dec 15.

  PMID: 27988288 BACKGROUND

• Leung FW, Hsieh YH. Artificial intelligence (computer-assisted detection) is the most recent novel approach to increase adenoma detection. Gastrointest Endosc. 2021 Jan;93(1):86-88. doi: 10.1016/j.gie.2020.07.059. No abstract available.

  PMID: 33353642 BACKGROUND

• Wang P, Liu X, Berzin TM, Glissen Brown JR, Liu P, Zhou C, Lei L, Li L, Guo Z, Lei S, Xiong F, Wang H, Song Y, Pan Y, Zhou G. 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 Apr;5(4):343-351. doi: 10.1016/S2468-1253(19)30411-X. Epub 2020 Jan 22.

  PMID: 31981517 BACKGROUND

• Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1.

  PMID: 32371116 BACKGROUND

• Barua I, Vinsard DG, Jodal HC, Loberg M, Kalager M, Holme O, Misawa M, Bretthauer M, Mori Y. Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis. Endoscopy. 2021 Mar;53(3):277-284. doi: 10.1055/a-1201-7165. Epub 2020 Sep 29.

  PMID: 32557490 BACKGROUND

• Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.

  PMID: 32598963 BACKGROUND

• Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.

  PMID: 30814121 BACKGROUND

• Hsieh YH, Leung FW. An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection. Expert Rev Gastroenterol Hepatol. 2019 Dec;13(12):1153-1160. doi: 10.1080/17474124.2019.1694903. Epub 2019 Nov 30.

  PMID: 31755802 BACKGROUND

• Cadoni S, Ishaq S, Hassan C, Falt P, Fuccio L, Siau K, Leung JW, Anderson J, Binmoeller KF, Radaelli F, Rutter MD, Sugimoto S, Muhammad H, Bhandari P, Draganov PV, de Groen P, Wang AY, Yen AW, Hamerski C, Thorlacius H, Neumann H, Ramirez F, Mulder CJJ, Albeniz E, Amato A, Arai M, Bak A, Barret M, Bayupurnama P, Cheung R, Ching HL, Cohen H, Dolwani S, Friedland S, Harada H, Hsieh YH, Hayee B, Kuwai T, Lorenzo-Zuniga V, Liggi M, Mizukami T, Mura D, Nylander D, Olafsson S, Paggi S, Pan Y, Parra-Blanco A, Ransford R, Rodriguez-Sanchez J, Senturk H, Suzuki N, Tseng CW, Uchima H, Uedo N, Leung FW. Water-assisted colonoscopy: an international modified Delphi review on definitions and practice recommendations. Gastrointest Endosc. 2021 Jun;93(6):1411-1420.e18. doi: 10.1016/j.gie.2020.10.011. Epub 2020 Oct 16.

  PMID: 33069706 RESULT

MeSH Terms

Conditions

Colonic Polyps

Condition Hierarchy (Ancestors)

Intestinal Polyps; Polyps; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms

Study Officials

• Chia Pei Tang

  Dalin Tzu Chi General Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Gastroeneterologist

Study Record Dates

• First Submitted: January 18, 2021
• First Posted: January 27, 2021
• Study Start: August 1, 2020
• Primary Completion: September 1, 2020
• Study Completion: April 10, 2021
• Last Updated: April 5, 2021

Record last verified: 2021-04

Locations

TW (1)