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

Publication ,  Journal Article
Glissen Brown, JR; Mansour, NM; Wang, P; Chuchuca, MA; Minchenberg, SB; Chandnani, M; Liu, L; Gross, SA; Sengupta, N; Berzin, TM
Published in: Clin Gastroenterol Hepatol
July 2022

BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are intended to address the issue of missed polyps during colonoscopy. The effect of CADe during screening and surveillance colonoscopy has not previously been studied in a United States (U.S.) population. METHODS: We conducted a prospective, multi-center, single-blind randomized tandem colonoscopy study to evaluate a deep-learning based CADe system (EndoScreener, Shanghai Wision AI, China). Patients were enrolled across 4 U.S. academic medical centers from 2019 through 2020. Patients presenting for colorectal cancer screening or surveillance were randomized to CADe colonoscopy first or high-definition white light (HDWL) colonoscopy first, followed immediately by the other procedure in tandem fashion by the same endoscopist. The primary outcome was adenoma miss rate (AMR), and secondary outcomes included sessile serrated lesion (SSL) miss rate and adenomas per colonoscopy (APC). RESULTS: A total of 232 patients entered the study, with 116 patients randomized to undergo CADe colonoscopy first and 116 patients randomized to undergo HDWL colonoscopy first. After the exclusion of 9 patients, the study cohort included 223 patients. AMR was lower in the CADe-first group compared with the HDWL-first group (20.12% [34/169] vs 31.25% [45/144]; odds ratio [OR], 1.8048; 95% confidence interval [CI], 1.0780-3.0217; P = .0247). SSL miss rate was lower in the CADe-first group (7.14% [1/14]) vs the HDWL-first group (42.11% [8/19]; P = .0482). First-pass APC was higher in the CADe-first group (1.19 [standard deviation (SD), 2.03] vs 0.90 [SD, 1.55]; P = .0323). First-pass ADR was 50.44% in the CADe-first group and 43.64 % in the HDWL-first group (P = .3091). CONCLUSION: In this U.S. multicenter tandem colonoscopy randomized controlled trial, we demonstrate a decrease in AMR and SSL miss rate and an increase in first-pass APC with the use of a CADe-system when compared with HDWL colonoscopy alone.

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Published In

Clin Gastroenterol Hepatol

DOI

EISSN

1542-7714

Publication Date

July 2022

Volume

20

Issue

7

Start / End Page

1499 / 1507.e4

Location

United States

Related Subject Headings

  • United States
  • Single-Blind Method
  • Prospective Studies
  • Missed Diagnosis
  • Humans
  • Gastroenterology & Hepatology
  • Diagnosis, Computer-Assisted
  • Deep Learning
  • Colorectal Neoplasms
  • Colonoscopy
 

Citation

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Glissen Brown, J. R., Mansour, N. M., Wang, P., Chuchuca, M. A., Minchenberg, S. B., Chandnani, M., … Berzin, T. M. (2022). 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, 20(7), 1499-1507.e4. https://doi.org/10.1016/j.cgh.2021.09.009
Glissen Brown, Jeremy R., Nabil M. Mansour, Pu Wang, Maria Aguilera Chuchuca, Scott B. Minchenberg, Madhuri Chandnani, Lin Liu, Seth A. Gross, Neil Sengupta, and Tyler M. Berzin. “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 20, no. 7 (July 2022): 1499-1507.e4. https://doi.org/10.1016/j.cgh.2021.09.009.
Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, et al. 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 Jul;20(7):1499-1507.e4.
Glissen Brown, Jeremy R., et al. “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, vol. 20, no. 7, July 2022, pp. 1499-1507.e4. Pubmed, doi:10.1016/j.cgh.2021.09.009.
Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, Liu L, Gross SA, Sengupta N, Berzin TM. 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 Jul;20(7):1499-1507.e4.
Journal cover image

Published In

Clin Gastroenterol Hepatol

DOI

EISSN

1542-7714

Publication Date

July 2022

Volume

20

Issue

7

Start / End Page

1499 / 1507.e4

Location

United States

Related Subject Headings

  • United States
  • Single-Blind Method
  • Prospective Studies
  • Missed Diagnosis
  • Humans
  • Gastroenterology & Hepatology
  • Diagnosis, Computer-Assisted
  • Deep Learning
  • Colorectal Neoplasms
  • Colonoscopy