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

Colon Polyp Clinical Trial

Official title:

Polyp Detection and False Alarm Rates by Computer-Aided Analysis of Videos of Withdrawal Phase of Colonoscopy in a Randomized Controlled Trial of Water Exchange Versus Air Insufflation

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT04727814
• Other study ID #: B10903009
• Status: Active, not recruiting
• Start date: August 1, 2020
• Est. completion date: April 10, 2021

Study information

• Verified date: April 2021
• Source: Dalin Tzu Chi General Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Description:

Worldwide colorectal cancer (CRC) is the second most common cancer in women and the third in men. Early detection and removal of the colon polyps (cancer precursors) reduce the incidence of CRC. However, interval colon cancers still occur within 3-5 years after colonoscopy among patients of colonoscopists with low adenoma detection rate (ADR), defined as the proportion of patients with at least one adenoma. ADR was widely variable, suggesting that some adenomas were missed. Twenty six percent of adenomas were missed during tandem examination reported in a recent meta-analysis. Missed adenomas accounted for about 58% of interval cancers. Adenomas are more likely to be missed in the right colon than in other segments because of their flat morphology and hiding behind the accentuated folds and curvatures. Innovations in colonoscopy to increase ADR and decrease adenoma miss rate (AMR) hold the potential to reduce interval cancers.

The consensus statements in a recent modified Delphi review confirmed water exchange (WE) as a standardized insertion method produced less insertion pain, better bowel cleanliness and higher ADR than gas insufflation. It is characterized by infusing water to guide insertion in an airless lumen and almost simultaneous suctioning of the infused water during insertion, aiming at near-complete removal of the infused water and debris upon cecal intubation. Although an RCT with tandem examination showed WE significantly decreased right colon adenoma miss rate (rAMR) compared with CO2 insufflation (18.0% [33/183] vs. 34.6% [62/179], P = 0.0025), a considerable percentage of polyps in the right colon were still overlooked.

In recent years, the field of machine learning and artificial intelligence has made remarkable progress, and an increasing number of publications showed improved polyp detection rate (PDR) and ADR using computer-aided detection (CADe). CADe can detect polyps overlooked by the colonoscopist due to human limitations of inattention or inexperience. However, one major drawback of current CADe systems is false alarms (FAs), or false positives (FPs). Usually triggered by bubbles and fecal debris, FAs might distract the endoscopists with potential unfavorable effect on ADR. One study reported a FP rate of up to 60%.

In an overview on applying deep learning algorithms and WE in colonoscopy to improve adenoma detection, the authors noted that WE could enhance the performance of artificial intelligence (CADe) by improving bowel cleanliness and thus the exposure of polyps. In a follow-up review, the authors reported that artificial intelligence might mitigate operator-dependent factors that limited the potential of WE, while WE might provide the platform to optimize the performance of artificial intelligence by increasing bowel cleanliness and improving visualization, Therefore, the strengths of WE and artificial intelligence may complement the weaknesses of each other to maximize adenoma detection.

One of our recently completed studies compared right colon ADR evaluated by a blinded endoscopist using either air insufflation or WE for insertion, with all the colonoscopies video recorded (NCT02737514). We developed and applied a CADe system to detect the polyps in the videos. The current report is a proof of principle study to test the hypothesis that WE could yield a significantly higher additional PDR (APDR) and reduce false alarms rate (FAR) as compared to air insufflation in the right colon.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 250
• Est. completion date: April 10, 2021
• Est. primary completion date: September 1, 2020
• Gender: All
• Age group: 40 Years to 80 Years

Eligibility

Inclusion Criteria:

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

Exclusion Criteria:

• 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.

Related Conditions & MeSH terms

• Colon Polyp
• Polyps

Intervention

Other:
• Computer-aided detection system overlaid colonoscopy videos analysis
Analysis of computer-aided detection system overlaid videos from colonoscopies performed with water exchange or air insufflation method.

Locations

Country	Name	City	State
Taiwan	Chia Pei Tang	Chiayi City	Chiayi

Sponsors (3)

Lead Sponsor	Collaborator
Dalin Tzu Chi General Hospital	National Chiayi University, University of California

Country where clinical trial is conducted

Taiwan, 

References & Publications (10)

Barua I, Vinsard DG, Jodal HC, Løberg M, Kalager M, Holme Ø, 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 Jun 17. — View Citation

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, Al — View Citation

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. 2020 Oct 16. doi: 10.1097/MCG.0000000000001454. [Epub ahead of print] — View Citation

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, Rösch 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. Review. — View Citation

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. Review. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Erratum in: Lancet Gastroenterol Hepatol. 2020 Apr;5(4):e3. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Polyp detection rate	To find out and compare the polyp detection rate on water exchange and air insufflation group	One month
Secondary	False positive rate of computer-aided detection system	To find out and compare the false positive rates on water exchange and air insufflation group	One month
Secondary	False alarm rate of computer-aided detection system	To find out and compare the false alarm rates on water exchange and air	One month