본문 바로가기
KERD
논문KCI 등재

Assessing the potential of artificial intelligence to enhance colonoscopy adenoma detection in clinical practice: a prospective observational trial

3

조회

0

다운로드

1

인용

0

참고문헌

키워드

주제분류내과학

초록

Background/Aims: This study aimed to evaluate the effectiveness of the GI Genius (Medtronic) module in clinical practice, focusing on the adenoma detection rate (ADR) during colonoscopy. Computer-aided polyp detection (CADe) systems using artificial intelligence have been shown to improve adenoma detection in controlled trials. However, the effectiveness of these systems in clinical practice has recently been questioned. Methods: This single-center prospective observational study was conducted at the University Hospital of Southern Denmark and included all individuals referred for colonoscopy between November 2020 and January 2021. The primary outcome was ADR, comparing patients examined with CADe to those examined without it. The selection of patients to be examined with the CADe module was completely random. Results: A total of 502 patients were analyzed (318 in the control group and 184 in the CADe group). The overall ADR was 32.1% with a slight increase in the CADe group (34.7% vs. 30.5%). Multivariable analysis showed a very modest and statistically insignificant increase in ADR (risk ratio, 1.12; 95% confidence interval, 0.88–1.43). Conclusions: The use of CADe in clinical practice did not increase ADR with statistical significance when compared to colonoscopy without CADe. These findings suggest that the impact of CADe systems in everyday clinical practice are modest.

Abstract

Background/Aims: This study aimed to evaluate the effectiveness of the GI Genius (Medtronic) module in clinical practice, focusing on the adenoma detection rate (ADR) during colonoscopy. Computer-aided polyp detection (CADe) systems using artificial intelligence have been shown to improve adenoma detection in controlled trials. However, the effectiveness of these systems in clinical practice has recently been questioned. Methods: This single-center prospective observational study was conducted at the University Hospital of Southern Denmark and included all individuals referred for colonoscopy between November 2020 and January 2021. The primary outcome was ADR, comparing patients examined with CADe to those examined without it. The selection of patients to be examined with the CADe module was completely random. Results: A total of 502 patients were analyzed (318 in the control group and 184 in the CADe group). The overall ADR was 32.1% with a slight increase in the CADe group (34.7% vs. 30.5%). Multivariable analysis showed a very modest and statistically insignificant increase in ADR (risk ratio, 1.12; 95% confidence interval, 0.88–1.43). Conclusions: The use of CADe in clinical practice did not increase ADR with statistical significance when compared to colonoscopy without CADe. These findings suggest that the impact of CADe systems in everyday clinical practice are modest.

참고문헌 (22)

  1. Rex DK, "Quality indicators for colo noscopy", Gastrointest Endosc, 81, pp.31~53 (2015)
  2. Kaminski MF, "Increased rate of ade noma detection associates with reduced risk of colorectal cancer and death", Gastroenterology, 153, pp.98~105 (2017)
  3. Lui TKL, "Is artificial intelligence the final answer to missed polyps in colonoscopy?", World J Gastroenterol, 26, pp.52485255~ (2020)
  4. Jaho F, "Time-of-day variation in the diagnostic quality of screening colonoscopies : a registry-based study", Ann Gas troenterol, 34, pp.815~819 (2021)
  5. Wei MT, "Artificial intelligence-assisted colo noscopy in real-world clinical practice : a systematic review and me ta-analysis", Clin Transl Gastroenterol, 15, pp.e00671~ (2024)
  6. Hassan C, "Real-time computer-aided detection of colorectal neoplasia during colonoscopy : a systematic review and meta-analysis", Ann Intern Med, 176, pp.1209~1220 (2023)
  7. Ishiyama M, "Impact of the clinical use of artificial intelligence-assisted neoplasia detection for colonoscopy : a large-scale prospective, propensity score-matched study(with vid eo)", Gastrointest Endosc, 95, pp.155~163 (2022)
  8. Schlemper RJ, "The Vienna classification of gastrointestinal epithelial neoplasia", Gut, 47, pp.251~255 (2000)
  9. Hassan C, "New artificial intelligence system : first validation study versus experienced endoscopists for colorectal polyp detection", Gut, 69, pp.799~800 (2020)
  10. Repici A, "Efficacy of per-oral methylene blue formulation for screening colonoscopy", Gastroenterology, 156, pp.2198~2207 (2019)
  11. Lai EJ, "The Boston bowel prepara tion scale : a valid and reliable instrument for colonoscopy-oriented research", Gastrointest Endosc, 69(3 Pt 2), pp.620~625 (2009)
  12. von Elm E, "The Strengthening the Reporting of Observational Studies in Epidemiology(STROBE)Statement : guidelines for reporting observational studies", Int J Surg, 12, pp.1495~1499 (2014)
  13. Naimi AI, "Can confidence intervals be interpreted?", Am J Epidemiol, 189, pp.631~633 (2020)
  14. Rondonotti E, "Efficacy of a comput er-aided detection system in a fecal immunochemical test-based organized colorectal cancer screening program : a randomized con trolled trial(AIFIT study)", Endoscopy, 54, pp.1171~1179 (2022)
  15. Mangas-Sanjuan C, "Role of artificial intelligence in colonoscopy detection of advanced neoplasias : a ran domized trial", Ann Intern Med, 176, pp.1145~1152 (2023)
  16. Wallace MB, "Impact of artificial in telligence on miss rate of colorectal neoplasia", Gastroenterology, 163, pp.295~304 (2022)
  17. "Yearly report 2020. The Danish Quality Database for Colon Cancer Screen ing"[URL]
  18. Repici A, "Artificial intelligence and colonoscopy experience : lessons from two randomised trials", Gut, 71, pp.757~765 (2022)
  19. Lau LH, "Effect of real-time computer-aided pol yp detection system(ENDO-AID)on adenoma detection in endos copists-in-training : a randomized trial", Clin Gastroenterol Hepatol, 22, pp.630~641 (2024)
  20. Hassan C, "Performance of artificial intelligence in colonoscopy for adenoma and polyp detection : a sys tematic review and meta-analysis", Gastrointest Endosc, 93, pp.7785~ (2021)
  21. Repici A, "Efficacy of real-time com puter-aided detection of colorectal neoplasia in a randomized trial", Gastroenterology, 159, pp.512~520 (2020)
  22. Barclay RL, "Colonoscopic withdrawal times and adenoma detection during screening colonoscopy", N Engl J Med, 355, pp.2533~2541 (2006)

관련 논문AI추천

Effect of artificial intelligence-aided colonoscopy on the adenoma detection rate: A systematic reviewAmjad Khan, Anson Mwango, Dua Sadaf Abbasi, Sameen Abbas, Tayyab Saeed Akhtar소화기인터벤션의학회 · International Journal of Gastrointestinal Intervention2024 · 제13권 제3호Effectiveness of a novel artificial intelligence-assisted colonoscopy system for adenoma detection: a prospective, propensity score-matched, non-randomized controlled study in KoreaJung-Bin Park, Jung Ho Bae대한소화기내시경학회 · Clinical Endoscopy2025 · 제58권 제1호Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled TrialChoi Hyuk Soon, Jeen Yoon Tae, Jeong Eui Sun, Jeon Han Jo, Keum Bora, Kim Eun Sun, Kim Sang Hyun, Kim Seong-Eun, Lee Bomee, Lee Jae Min, Moon Chang Mo거트앤리버 소화기연관학회협의회 · Gut and Liver2026 · 제20권 제1호GI Genius increases small and right-sided adenoma and sessile serrated lesion detection rate when used with EndoCuff in a real-world setting: a retrospective United States studyColton Pence, David Wan, Enad Dawod, Felice Schnoll-Sussman, Jade Wang, Jeong Hoon Kim, Patrick Magahis, Reem Z. Sharaiha대한소화기내시경학회 · Clinical Endoscopy2025 · 제58권 제3호Does computer-aided diagnostic endoscopy improve the detection of commonly missed polyps? A meta-analysisAra Darzi, Arun Sivananthan, Hutan Ashrafian, Kinesh Patel, Lakshmana Ayaru, Nisha Patel, Scarlet Nazarian대한소화기내시경학회 · Clinical Endoscopy2022 · 제55권 제3호Computer-aided diagnosis of colorectal polyps: assisted or autonomous?Cesare Hassan, Yuichi Mori대한소화기내시경학회 · Clinical Endoscopy2025 · 제58권 제4호

이 간행물의 다른 논문 (20건)