*Result*: Man Plus Machine: A Randomized Control Trial of Artificial Intelligence Including the Impact of Adjunctive Polyp Detection Techniques.
Title:
Man Plus Machine: A Randomized Control Trial of Artificial Intelligence Including the Impact of Adjunctive Polyp Detection Techniques.
Authors:
Schauer C; Te Whatu Ora Health New Zealand Waitemata, Gastroenterology, Auckland, New Zealand.; Department of Medicine, University of Auckland, Auckland, New Zealand., van Rijnsoever M; Te Whatu Ora Health New Zealand Waitemata, Gastroenterology, Auckland, New Zealand., Jafer A; Te Whatu Ora Health New Zealand Waitemata, Gastroenterology, Auckland, New Zealand., Walmsley R; Te Whatu Ora Health New Zealand Waitemata, Gastroenterology, Auckland, New Zealand.; Department of Medicine, University of Auckland, Auckland, New Zealand., Wang MTM; Department of Medicine, University of Auckland, Auckland, New Zealand., Atkinson N; Te Whatu Ora Health New Zealand Waitemata, Gastroenterology, Auckland, New Zealand.
Source:
Journal of gastroenterology and hepatology [J Gastroenterol Hepatol] 2026 Jan; Vol. 41 (1), pp. 117-127. Date of Electronic Publication: 2025 Nov 24.
Publication Type:
Journal Article; Randomized Controlled Trial
Language:
English
Journal Info:
Publisher: Blackwell Scientific Publications Country of Publication: Australia NLM ID: 8607909 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1440-1746 (Electronic) Linking ISSN: 08159319 NLM ISO Abbreviation: J Gastroenterol Hepatol Subsets: MEDLINE
Imprint Name(s):
Original Publication: Melbourne ; Boston : Blackwell Scientific Publications, c1986-
MeSH Terms:
References:
J. Makar, J. Abdelmalak, D. Con, B. Hafeez, and M. Garg, “Use of Artificial Intelligence Improves Colonoscopy Performance in Adenoma Detection: A Systematic Review and Meta‐Analysis,” Gastrointestinal Endoscopy 101, no. 1 (2025): 68–81.e8.
S. Soleymanjahi, J. Huebner, L. Elmansy, N. Rajashekar, N. Lüdtke, and R. Paracha, “Artificial Intelligence–Assisted Colonoscopy for Polyp Detection,” Annals of Internal Medicine 177, no. 12 (2024): 1652–1663.
D. A. Corley, C. D. Jensen, A. R. Marks, W. K. Zhao, J. K. Lee, and C. A. Doubeni, “Adenoma Detection Rate and Risk of Colorectal Cancer and Death,” New England Journal of Medicine 370, no. 14 (2014): 1298–1306.
D. K. Rex, P. S. Schoenfeld, J. Cohen, I. M. Pike, D. G. Adler, and M. B. Fennerty, “Quality Indicators for Colonoscopy,” Gastrointestinal Endoscopy 81, no. 1 (2015): 31–53.
C. Hassan, D. Piovani, M. Spadaccini, T. Parigi, K. Khalaf, and A. Facciorusso, “Variability in Adenoma Detection Rate in Control Groups of Randomized Colonoscopy Trials: A Systematic Review and Meta‐Analysis,” Gastrointestinal Endoscopy 97, no. 2 (2023): 212–225.e7.
Te Aho o Te Kahu, “Update on Polyp Surveillance Guidelines,” Wellington (2024).
A. Shaukat, A. Tuskey, V. L. Rao, J. A. Dominitz, M. H. Murad, and R. N. Keswani, “Interventions to Improve Adenoma Detection Rates for Colonoscopy,” Gastrointestinal Endoscopy 96, no. 2 (2022): 171–183.
D. Gong, L. Wu, J. Zhang, G. Mu, L. Shen, and J. Liu, “Detection of Colorectal Adenomas With a Real‐Time Computer‐Aided System (ENDOANGEL): A Randomised Controlled Study,” Lancet Gastroenterology & Hepatology 5, no. 4 (2020): 352–361.
D. K. Rex, Y. Mori, P. Sharma, R. E. Lahr, K. C. Vemulapalli, and C. Hassan, “Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High‐Detecting Endoscopist,” Gastroenterology 163, no. 2 (2022): 354–358.e1.
P. Wang, P. Liu, J. R. Glissen Brown, T. M. Berzin, G. Zhou, and S. Lei, “Lower Adenoma Miss Rate of Computer‐Aided Detection‐Assisted Colonoscopy vs. Routine White‐Light Colonoscopy in a Prospective Tandem Study,” Gastroenterology 159, no. 4 (2020): 1252–1261.e5.
J. R. Glissen Brown, N. M. Mansour, P. Wang, et al., “Deep Learning Computer‐Aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi‐Center Randomized Tandem Colonoscopy Study (CADeT‐CS Trial),” Clinical Gastroenterology and Hepatology 20, no. 7 (2022): 1499–1507.e4.
L. H. S. Lau, J. C. L. Ho, J. C. T. Lai, A. H. Y. Ho, C. W. K. Wu, and V. W. H. Lo, “Effect of Real‐Time Computer‐Aided Polyp Detection System (ENDO‐AID) on Adenoma Detection in Endoscopists‐in‐Training: A Randomized Trial,” Clinical Gastroenterology and Hepatology 22, no. 3 (2024): 630–641.e4.
E. J. Lai, A. H. Calderwood, G. Doros, O. K. Fix, and B. C. Jacobson, “The Boston Bowel Preparation Scale: A Valid and Reliable Instrument for Colonoscopy‐Oriented Research,” Gastrointestinal Endoscopy 69, no. 3 (2009): 620–625.
Conjoint Board of the Royal College of Physicians and Royal College of Surgeons Working Group, “Guidelines for the Implementation of a National Quality Assurance Programme in GI Endoscopy—Version 2.0,” Royal College of Physicians of Ireland. Royal College of Physicians of Ireland. (2011).
Participants in the Paris Workshop, “The Paris Endoscopic Classification of Superficial Neoplastic Lesions: Esophagus, Stomach, and Colon,” Gastrointestinal Endoscopy 58, no. 6 (2003): S3–S43.
R. J. Schlemper, “The Vienna Classification of Gastrointestinal Epithelial Neoplasia,” Gut 47, no. 2 (2000): 251–255.
C. Mangas‐Sanjuan, L. de‐Castro, J. Cubiella, P. Díez‐Redondo, A. Suárez, and M. Pellisé, “Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias,” Annals of Internal Medicine 176, no. 9 (2023): 1145–1152.
A. Ahmad, A. Wilson, A. Haycock, A. Humphries, K. Monahan, and N. Suzuki, “Evaluation of a Real‐Time Computer‐Aided Polyp Detection System During Screening Colonoscopy: AI‐DETECT Study,” Endoscopy 55, no. 4 (2023): 313–319.
L. Caillo, C. Delliot, T. Chevallier, J. F. Bourgaux, A. Prost, and B. Brunaud‐Gagniard, “COLODETECT 1: Comparative Evaluation of Endocuff With Computer‐Aided Detection Versus Computer‐Aided Detection Alone Versus Standard Colonoscopy for Enhancing Adenoma Detection Rates During Screening Colonoscopy—A Pilot Study,” Therapeutic Advances in Gastroenterology 17 (2024): 17562848241290433.
M. Spadaccini, C. Hassan, E. Rondonotti, G. Antonelli, G. Andrisani, and G. Lollo, “Combination of Mucosa‐Exposure Device and Computer‐Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial,” Gastroenterology 165, no. 1 (2023): 244–251.e3.
T. K. L. Lui, C. P. M. Lam, E. W. P. To, M. K. L. Ko, V. W. M. Tsui, and K. S. H. Liu, “Endocuff With or Without Artificial Intelligence‐Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial,” American Journal of Gastroenterology 119, no. 7 (2024): 1318–1325.
S. Aniwan, K. Mekritthikrai, S. J. Kerr, K. Tiankanon, K. Vandaungden, and Y. Sritunyarat, “Computer‐Aided Detection, Mucosal Exposure Device, Their Combination, and Standard Colonoscopy for Adenoma Detection: A Randomized Controlled Trial,” Gastrointestinal Endoscopy 97, no. 3 (2023): 507–516.
L. Yao, L. Zhang, J. Liu, W. Zhou, C. He, and J. Zhang, “Effect of an Artificial Intelligence‐Based Quality Improvement System on Efficacy of a Computer‐Aided Detection System in Colonoscopy: A Four‐Group Parallel Study,” Endoscopy 54, no. 8 (2022): 757–768.
W. Liu, Y. Wu, X. Yuan, J. Zhang, Y. Zhou, and W. Zhang, “Artificial Intelligence‐Based Assessments of Colonoscopic Withdrawal Technique: A New Method for Measuring and Enhancing the Quality of Fold Examination,” Endoscopy 54, no. 10 (2022): 972–979.
I. Ashraf, S. Ashraf, S. Siddique, D. L. Nguyen, A. Choudhary, and M. L. Bechtold, “Hyoscine for Polyp Detection During Colonoscopy: A Meta‐Analysis and Systematic Review,” World Journal of Gastrointestinal Endoscopy 6, no. 11 (2014): 549–554.
N. S. S. Atkinson, S. Ket, P. Bassett, D. Aponte, S. De Aguiar, and N. Gupta, “Narrow‐Band Imaging for Detection of Neoplasia at Colonoscopy: A Meta‐Analysis of Data From Individual Patients in Randomized Controlled Trials,” Gastroenterology 157, no. 2 (2019): 462–471.
A. Shaukat, T. S. Rector, T. R. Church, F. A. Lederle, A. S. Kim, and J. M. Rank, “Longer Withdrawal Time Is Associated With a Reduced Incidence of Interval Cancer After Screening Colonoscopy,” Gastroenterology 149, no. 4 (2015): 952–957.
M. Spadaccini, C. Hassan, Y. Mori, D. Massimi, L. Correale, and A. Facciorusso, “Variability in Computer‐Aided Detection Effect on Adenoma Detection Rate in Randomized Controlled Trials: A Meta‐Regression Analysis,” Digestive and Liver Disease 57 (2025): 1141–1148.
D. Yamaguchi, R. Shimoda, K. Miyahara, T. Yukimoto, Y. Sakata, and A. Takamori, “Impact of an Artificial Intelligence‐Aided Endoscopic Diagnosis System on Improving Endoscopy Quality for Trainees in Colonoscopy: Prospective, Randomized, Multicenter Study,” Digestive Endoscopy 36, no. 1 (2024): 40–48.
M. T. Wei, U. Shankar, R. Parvin, S. H. Abbas, S. Chaudhary, and Y. Friedlander, “Evaluation of Computer‐Aided Detection During Colonoscopy in the Community (AI‐SEE): A Multicenter Randomized Clinical Trial,” American Journal of Gastroenterology 118, no. 10 (2023): 1841–1847.
M. B. Wallace, P. Sharma, P. Bhandari, J. East, G. Antonelli, and R. Lorenzetti, “Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia,” Gastroenterology 163, no. 1 (2022): 295–304.e5.
A. Liu, H. Wang, Y. Lin, L. Fu, Y. Liu, and S. Yan, “Gastrointestinal Endoscopy Nurse Assistance During Colonoscopy and Polyp Detection: A PRISMA‐Compliant Meta‐Analysis of Randomized Control Trials,” Medicine 99, no. 34 (2020): e21278.
K. Bishay, N. Causada‐Calo, M. A. Scaffidi, C. M. Walsh, J. T. Anderson, and A. Rostom, “Associations Between Endoscopist Feedback and Improvements in Colonoscopy Quality Indicators: A Systematic Review and Meta‐Analysis,” Gastrointestinal Endoscopy 92, no. 5 (2020): 1030–1040.e9.
M. Spadaccini, A. Iannone, R. Maselli, M. Badalamenti, M. Desai, and V. T. Chandrasekar, “Computer‐Aided Detection Versus Advanced Imaging for Detection of Colorectal Neoplasia: A Systematic Review and Network Meta‐Analysis,” Lancet Gastroenterology & Hepatology 6, no. 10 (2021): 793–802.
I. Vilkoite, I. Tolmanis, H. A. Meri, I. Polaka, L. Mezmale, and L. Anarkulova, “The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy,” Diagnostics 13, no. 4 (2023): 701.
A. Z. Gimeno‐García, D. Hernández Negrin, A. Hernández, D. Nicolás‐Pérez, E. Rodríguez, and C. Montesdeoca, “Usefulness of a Novel Computer‐Aided Detection System for Colorectal Neoplasia: A Randomized Controlled Trial,” Gastrointestinal Endoscopy 97, no. 3 (2023): 528–536.e1.
L. Xu, X. He, J. Zhou, J. Zhang, X. Mao, and G. Ye, “Artificial Intelligence‐Assisted Colonoscopy: A Prospective, Multicenter, Randomized Controlled Trial of Polyp Detection,” Cancer Medicine 10, no. 20 (2021): 7184–7193.
J. E. Schottinger, C. D. Jensen, N. R. Ghai, J. Chubak, J. K. Lee, and A. Kamineni, “Association of Physician Adenoma Detection Rates With Postcolonoscopy Colorectal Cancer,” JAMA 327, no. 21 (2022): 2114–2122.
N. D. Pilonis, P. Spychalski, M. Kalager, M. Løberg, P. Wieszczy, and J. Didkowska, “Adenoma Detection Rates by Physicians and Subsequent Colorectal Cancer Risk,” Journal of the American Medical Association 333, no. 5 (2025): 400–407.
S. Soleymanjahi, J. Huebner, L. Elmansy, N. Rajashekar, N. Lüdtke, and R. Paracha, “Artificial Intelligence–Assisted Colonoscopy for Polyp Detection,” Annals of Internal Medicine 177, no. 12 (2024): 1652–1663.
D. A. Corley, C. D. Jensen, A. R. Marks, W. K. Zhao, J. K. Lee, and C. A. Doubeni, “Adenoma Detection Rate and Risk of Colorectal Cancer and Death,” New England Journal of Medicine 370, no. 14 (2014): 1298–1306.
D. K. Rex, P. S. Schoenfeld, J. Cohen, I. M. Pike, D. G. Adler, and M. B. Fennerty, “Quality Indicators for Colonoscopy,” Gastrointestinal Endoscopy 81, no. 1 (2015): 31–53.
C. Hassan, D. Piovani, M. Spadaccini, T. Parigi, K. Khalaf, and A. Facciorusso, “Variability in Adenoma Detection Rate in Control Groups of Randomized Colonoscopy Trials: A Systematic Review and Meta‐Analysis,” Gastrointestinal Endoscopy 97, no. 2 (2023): 212–225.e7.
Te Aho o Te Kahu, “Update on Polyp Surveillance Guidelines,” Wellington (2024).
A. Shaukat, A. Tuskey, V. L. Rao, J. A. Dominitz, M. H. Murad, and R. N. Keswani, “Interventions to Improve Adenoma Detection Rates for Colonoscopy,” Gastrointestinal Endoscopy 96, no. 2 (2022): 171–183.
D. Gong, L. Wu, J. Zhang, G. Mu, L. Shen, and J. Liu, “Detection of Colorectal Adenomas With a Real‐Time Computer‐Aided System (ENDOANGEL): A Randomised Controlled Study,” Lancet Gastroenterology & Hepatology 5, no. 4 (2020): 352–361.
D. K. Rex, Y. Mori, P. Sharma, R. E. Lahr, K. C. Vemulapalli, and C. Hassan, “Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High‐Detecting Endoscopist,” Gastroenterology 163, no. 2 (2022): 354–358.e1.
P. Wang, P. Liu, J. R. Glissen Brown, T. M. Berzin, G. Zhou, and S. Lei, “Lower Adenoma Miss Rate of Computer‐Aided Detection‐Assisted Colonoscopy vs. Routine White‐Light Colonoscopy in a Prospective Tandem Study,” Gastroenterology 159, no. 4 (2020): 1252–1261.e5.
J. R. Glissen Brown, N. M. Mansour, P. Wang, et al., “Deep Learning Computer‐Aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi‐Center Randomized Tandem Colonoscopy Study (CADeT‐CS Trial),” Clinical Gastroenterology and Hepatology 20, no. 7 (2022): 1499–1507.e4.
L. H. S. Lau, J. C. L. Ho, J. C. T. Lai, A. H. Y. Ho, C. W. K. Wu, and V. W. H. Lo, “Effect of Real‐Time Computer‐Aided Polyp Detection System (ENDO‐AID) on Adenoma Detection in Endoscopists‐in‐Training: A Randomized Trial,” Clinical Gastroenterology and Hepatology 22, no. 3 (2024): 630–641.e4.
E. J. Lai, A. H. Calderwood, G. Doros, O. K. Fix, and B. C. Jacobson, “The Boston Bowel Preparation Scale: A Valid and Reliable Instrument for Colonoscopy‐Oriented Research,” Gastrointestinal Endoscopy 69, no. 3 (2009): 620–625.
Conjoint Board of the Royal College of Physicians and Royal College of Surgeons Working Group, “Guidelines for the Implementation of a National Quality Assurance Programme in GI Endoscopy—Version 2.0,” Royal College of Physicians of Ireland. Royal College of Physicians of Ireland. (2011).
Participants in the Paris Workshop, “The Paris Endoscopic Classification of Superficial Neoplastic Lesions: Esophagus, Stomach, and Colon,” Gastrointestinal Endoscopy 58, no. 6 (2003): S3–S43.
R. J. Schlemper, “The Vienna Classification of Gastrointestinal Epithelial Neoplasia,” Gut 47, no. 2 (2000): 251–255.
C. Mangas‐Sanjuan, L. de‐Castro, J. Cubiella, P. Díez‐Redondo, A. Suárez, and M. Pellisé, “Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias,” Annals of Internal Medicine 176, no. 9 (2023): 1145–1152.
A. Ahmad, A. Wilson, A. Haycock, A. Humphries, K. Monahan, and N. Suzuki, “Evaluation of a Real‐Time Computer‐Aided Polyp Detection System During Screening Colonoscopy: AI‐DETECT Study,” Endoscopy 55, no. 4 (2023): 313–319.
L. Caillo, C. Delliot, T. Chevallier, J. F. Bourgaux, A. Prost, and B. Brunaud‐Gagniard, “COLODETECT 1: Comparative Evaluation of Endocuff With Computer‐Aided Detection Versus Computer‐Aided Detection Alone Versus Standard Colonoscopy for Enhancing Adenoma Detection Rates During Screening Colonoscopy—A Pilot Study,” Therapeutic Advances in Gastroenterology 17 (2024): 17562848241290433.
M. Spadaccini, C. Hassan, E. Rondonotti, G. Antonelli, G. Andrisani, and G. Lollo, “Combination of Mucosa‐Exposure Device and Computer‐Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial,” Gastroenterology 165, no. 1 (2023): 244–251.e3.
T. K. L. Lui, C. P. M. Lam, E. W. P. To, M. K. L. Ko, V. W. M. Tsui, and K. S. H. Liu, “Endocuff With or Without Artificial Intelligence‐Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial,” American Journal of Gastroenterology 119, no. 7 (2024): 1318–1325.
S. Aniwan, K. Mekritthikrai, S. J. Kerr, K. Tiankanon, K. Vandaungden, and Y. Sritunyarat, “Computer‐Aided Detection, Mucosal Exposure Device, Their Combination, and Standard Colonoscopy for Adenoma Detection: A Randomized Controlled Trial,” Gastrointestinal Endoscopy 97, no. 3 (2023): 507–516.
L. Yao, L. Zhang, J. Liu, W. Zhou, C. He, and J. Zhang, “Effect of an Artificial Intelligence‐Based Quality Improvement System on Efficacy of a Computer‐Aided Detection System in Colonoscopy: A Four‐Group Parallel Study,” Endoscopy 54, no. 8 (2022): 757–768.
W. Liu, Y. Wu, X. Yuan, J. Zhang, Y. Zhou, and W. Zhang, “Artificial Intelligence‐Based Assessments of Colonoscopic Withdrawal Technique: A New Method for Measuring and Enhancing the Quality of Fold Examination,” Endoscopy 54, no. 10 (2022): 972–979.
I. Ashraf, S. Ashraf, S. Siddique, D. L. Nguyen, A. Choudhary, and M. L. Bechtold, “Hyoscine for Polyp Detection During Colonoscopy: A Meta‐Analysis and Systematic Review,” World Journal of Gastrointestinal Endoscopy 6, no. 11 (2014): 549–554.
N. S. S. Atkinson, S. Ket, P. Bassett, D. Aponte, S. De Aguiar, and N. Gupta, “Narrow‐Band Imaging for Detection of Neoplasia at Colonoscopy: A Meta‐Analysis of Data From Individual Patients in Randomized Controlled Trials,” Gastroenterology 157, no. 2 (2019): 462–471.
A. Shaukat, T. S. Rector, T. R. Church, F. A. Lederle, A. S. Kim, and J. M. Rank, “Longer Withdrawal Time Is Associated With a Reduced Incidence of Interval Cancer After Screening Colonoscopy,” Gastroenterology 149, no. 4 (2015): 952–957.
M. Spadaccini, C. Hassan, Y. Mori, D. Massimi, L. Correale, and A. Facciorusso, “Variability in Computer‐Aided Detection Effect on Adenoma Detection Rate in Randomized Controlled Trials: A Meta‐Regression Analysis,” Digestive and Liver Disease 57 (2025): 1141–1148.
D. Yamaguchi, R. Shimoda, K. Miyahara, T. Yukimoto, Y. Sakata, and A. Takamori, “Impact of an Artificial Intelligence‐Aided Endoscopic Diagnosis System on Improving Endoscopy Quality for Trainees in Colonoscopy: Prospective, Randomized, Multicenter Study,” Digestive Endoscopy 36, no. 1 (2024): 40–48.
M. T. Wei, U. Shankar, R. Parvin, S. H. Abbas, S. Chaudhary, and Y. Friedlander, “Evaluation of Computer‐Aided Detection During Colonoscopy in the Community (AI‐SEE): A Multicenter Randomized Clinical Trial,” American Journal of Gastroenterology 118, no. 10 (2023): 1841–1847.
M. B. Wallace, P. Sharma, P. Bhandari, J. East, G. Antonelli, and R. Lorenzetti, “Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia,” Gastroenterology 163, no. 1 (2022): 295–304.e5.
A. Liu, H. Wang, Y. Lin, L. Fu, Y. Liu, and S. Yan, “Gastrointestinal Endoscopy Nurse Assistance During Colonoscopy and Polyp Detection: A PRISMA‐Compliant Meta‐Analysis of Randomized Control Trials,” Medicine 99, no. 34 (2020): e21278.
K. Bishay, N. Causada‐Calo, M. A. Scaffidi, C. M. Walsh, J. T. Anderson, and A. Rostom, “Associations Between Endoscopist Feedback and Improvements in Colonoscopy Quality Indicators: A Systematic Review and Meta‐Analysis,” Gastrointestinal Endoscopy 92, no. 5 (2020): 1030–1040.e9.
M. Spadaccini, A. Iannone, R. Maselli, M. Badalamenti, M. Desai, and V. T. Chandrasekar, “Computer‐Aided Detection Versus Advanced Imaging for Detection of Colorectal Neoplasia: A Systematic Review and Network Meta‐Analysis,” Lancet Gastroenterology & Hepatology 6, no. 10 (2021): 793–802.
I. Vilkoite, I. Tolmanis, H. A. Meri, I. Polaka, L. Mezmale, and L. Anarkulova, “The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy,” Diagnostics 13, no. 4 (2023): 701.
A. Z. Gimeno‐García, D. Hernández Negrin, A. Hernández, D. Nicolás‐Pérez, E. Rodríguez, and C. Montesdeoca, “Usefulness of a Novel Computer‐Aided Detection System for Colorectal Neoplasia: A Randomized Controlled Trial,” Gastrointestinal Endoscopy 97, no. 3 (2023): 528–536.e1.
L. Xu, X. He, J. Zhou, J. Zhang, X. Mao, and G. Ye, “Artificial Intelligence‐Assisted Colonoscopy: A Prospective, Multicenter, Randomized Controlled Trial of Polyp Detection,” Cancer Medicine 10, no. 20 (2021): 7184–7193.
J. E. Schottinger, C. D. Jensen, N. R. Ghai, J. Chubak, J. K. Lee, and A. Kamineni, “Association of Physician Adenoma Detection Rates With Postcolonoscopy Colorectal Cancer,” JAMA 327, no. 21 (2022): 2114–2122.
N. D. Pilonis, P. Spychalski, M. Kalager, M. Løberg, P. Wieszczy, and J. Didkowska, “Adenoma Detection Rates by Physicians and Subsequent Colorectal Cancer Risk,” Journal of the American Medical Association 333, no. 5 (2025): 400–407.
Grant Information:
Olympus America
Contributed Indexing:
Keywords: adenoma detection; artificial intelligence; colon polyps; colonoscopy
Entry Date(s):
Date Created: 20251125 Date Completed: 20260108 Latest Revision: 20260120
Update Code:
20260130
DOI:
10.1111/jgh.70145
PMID:
41287376
Database:
MEDLINE
*Further Information*
*Background and Aims: Computer-aided polyp detection tools (CADe) utilizing artificial intelligence (AI) have been shown to demonstrate benefit with improved polyp detection during colonoscopy. Questions remain around the impact of CADe when combined with additional techniques that improve polyp detection such as lengthening withdrawal time, cecal and rectal retroflexion, dynamic position change, and narrow band imaging (NBI) use.
Methods: A single-center prospective, randomized control trial comparing ENDO-AID AI module to conventional colonoscopy was conducted between October 11, 2023 and March 16, 2024 at Waitakere Hospital. Additional techniques to improve polyp detection were recorded but left to the discretion of participating 26 endoscopists.
Results: Seven hundred seventy-six patients (mean ± SD age, 61.2 ± 13.0 years; 344 females) were recruited, 383 patients allocated to AI and 393 to control. Position change was used in 43%, antispasmodic in 25%, distal cap in 25%, NBI in 21%. Overall, univariate analysis demonstrated a nonsignificant trend towards higher adenoma detection rate (ADR) in the CADe than control group (63.4% vs. 57.3%, p = 0.08). AI was most effective in the screening cohort (ADR 79% vs. 68%, average polyp rate 3.7 vs. 2.8 p < 0.05). Multivariable analysis demonstrated CADe was independently associated with increased adenoma detection rate (odds ratio [OR], 1.38; 95% confidence interval [CI], 1.01-1.89; p = 0.042), as was use of NBI, OR 2.00; (95% CI: 1.23-3.25; p = 0.006) and increased withdrawal time, OR 1.11; (95% CI: 1.08-1.15; p < 0.001).
Conclusion: ADR was increased by CADe in a cohort of high detectors and was further augmented by traditional techniques known to be beneficial. It is important to incorporate traditional techniques with CADe to maximize ADR.
(© 2025 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)*