Real-World Validation of a Computer-Aided Diagnosis System for Prediction of Polyp Histology in Colonoscopy: A Prospective Multicenter Study.
Journal
The American journal of gastroenterology
ISSN: 1572-0241
Titre abrégé: Am J Gastroenterol
Pays: United States
ID NLM: 0421030
Informations de publication
Date de publication:
01 08 2023
01 08 2023
Historique:
received:
31
10
2022
accepted:
28
03
2023
medline:
4
8
2023
pubmed:
12
4
2023
entrez:
11
4
2023
Statut:
ppublish
Résumé
Computer-aided diagnosis (CADx) of polyp histology could support endoscopists in clinical decision-making. However, this has not been validated in a real-world setting. We performed a prospective, multicenter study comparing CADx and endoscopist predictions of polyp histology in real-time colonoscopy. Optical diagnosis based on visual inspection of polyps was made by experienced endoscopists. After this, the automated output from the CADx support tool was recorded. All imaged polyps were resected for histological assessment. Primary outcome was difference in diagnostic performance between CADx and endoscopist prediction of polyp histology. Subgroup analysis was performed for polyp size, bowel preparation, difficulty of location of the polyps, and endoscopist experience. A total of 661 eligible polyps were resected in 320 patients aged ≥40 years between March 2021 and July 2022. CADx had an overall accuracy of 71.6% (95% confidence interval [CI] 68.0-75.0), compared with 75.2% (95% CI 71.7-78.4) for endoscopists ( P = 0.023). The sensitivity of CADx for neoplastic polyps was 61.8% (95% CI 56.9-66.5), compared with 70.3% (95% CI 65.7-74.7) for endoscopists ( P < 0.001). The interobserver agreement between CADx and endoscopist predictions of polyp histology was moderate (83.1% agreement, κ 0.661). When there was concordance between CADx and endoscopist predictions, the accuracy increased to 78.1%. The overall diagnostic accuracy and sensitivity for neoplastic polyps was higher in experienced endoscopists compared with CADx predictions, with moderate interobserver agreement. Concordance in predictions increased this diagnostic accuracy. Further research is required to improve the performance of CADx and to establish its role in clinical practice.
Identifiants
pubmed: 37040553
doi: 10.14309/ajg.0000000000002282
pii: 00000434-990000000-00719
doi:
Banques de données
ClinicalTrials.gov
['NCT05034185']
Types de publication
Multicenter Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1353-1364Informations de copyright
Copyright © 2023 by The American College of Gastroenterology.
Références
Kaminski MF, Thomas-Gibson S, Bugajski M, et al. Performance measures for lower gastrointestinal endoscopy: A European Society of Gastrointestinal Endoscopy (ESGE) Quality Improvement Initiative. Endoscopy 2017;49(4):378–97.
Rex DK, Schoenfeld PS, Cohen J, et al. Quality indicators for colonoscopy. Gastrointest Endosc 2015;81(1):31–53.
Barua I, Vinsard DG, Jodal HC, et al. Artificial intelligence for polyp detection during colonoscopy: A systematic review and meta-analysis. Endoscopy 2021;53(3):277–84.
Gong D, Wu L, Zhang J, et al. Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): A randomised controlled study. Lancet Gastroenterol Hepatol 2020;5(4):352–61.
Repici A, Badalamenti M, Maselli R, et al. Efficacy of real-time computer-aided detection of colorectal neoplasia in a randomized trial. Gastroenterology 2020;159(2):512–20.e7.
Su JR, Li Z, Shao XJ, et al. Impact of a real-time automatic quality control system on colorectal polyp and adenoma detection: A prospective randomized controlled study (with videos). Gastrointest Endosc 2020;91(2):415–24.e4.
Wang P, Berzin TM, Glissen Brown JR, et al. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: A prospective randomised controlled study. Gut 2019;68(10):1813–9.
Wang P, Liu X, Berzin TM, et al. 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;5(4):343–51.
Hassan C, Spadaccini M, Iannone A, et al. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: A systematic review and meta-analysis. Gastrointest Endosc 2021;93(1):77–85.e6.
Kandel P, Wallace MB. Should we resect and discard low risk diminutive colon polyps. Clin Endosc 2019;52(3):239–46.
Neumann H, Neumann Sen H, Vieth M, et al. Leaving colorectal polyps in place can be achieved with high accuracy using blue light imaging (BLI). United European Gastroenterol J 2018;6(7):1099–105.
von Renteln D, Kaltenbach T, Rastogi A, et al. Simplifying resect and discard strategies for real-time assessment of diminutive colorectal polyps. Clin Gastroenterol Hepatol 2018;16(5):706–14.
Ang TL, Li JW. Colonoscopy and artificial intelligence: Bridging the gap or a gap needing to be bridged? Artif Intell Gastrointest Endosc 2021;2(2):36–49.
Bang CS, Lee JJ, Baik GH. Computer-aided diagnosis of diminutive colorectal polyps in endoscopic images: Systematic review and meta-analysis of diagnostic test accuracy. J Med Internet Res 2021;23(8):e29682.
Lui TKL, Guo CG, Leung WK. Accuracy of artificial intelligence on histology prediction and detection of colorectal polyps: A systematic review and meta-analysis. Gastrointest Endosc 2020;92(1):11–22 e6.
Zorron Cheng Tao Pu L, Maicas G, Tian Y, et al. Computer-aided diagnosis for characterization of colorectal lesions: Comprehensive software that includes differentiation of serrated lesions. Gastrointest Endosc 2020;92(4):891–9.
Cao RR, Wang L, Gao C, et al. Effect of oral simethicone on the quality of colonoscopy: A systematic review and meta-analysis of randomized controlled trials. J Dig Dis 2022;23(3):134–48.
Yeh JH, Hsu MH, Tseng CM, et al. The benefit of adding oral simethicone in bowel preparation regimen for the detection of colon adenoma: A systematic review and meta-analysis. J Gastroenterol Hepatol 2019;34(5):830–6.
Ang TL, Li JW, Wong YJ, et al. A prospective randomized study of colonoscopy using blue laser imaging and white light imaging in detection and differentiation of colonic polyps. Endosc Int Open 2019;7(10):E1207–13.
Yoshida N, Hisabe T, Inada Y, et al. The ability of a novel blue laser imaging system for the diagnosis of invasion depth of colorectal neoplasms. J Gastroenterol 2014;49(1):73–80.
Konda V, Abu Dayyeh BK, Thosani N, et al. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc 2015;81(3):502.e1–16.
Rex DK, Kahi C, O'Brien M, et al. The American Society for Gastrointestinal Endoscopy PIVI (Preservation and Incorporation of Valuable Endoscopic Innovations) on real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc 2011;73(3):419–22.
Hassan C, Pickhardt PJ, Rex DK. A resect and discard strategy would improve cost-effectiveness of colorectal cancer screening. Clin Gastroenterol Hepatol 2010;8(10):865–9.e3.
Vleugels JLA, Hassan C, Senore C, et al. Diminutive polyps with advanced histologic features do not increase risk for metachronous advanced colon neoplasia. Gastroenterology 2019;156(3):623–34.e3.
Hassan C, Balsamo G, Lorenzetti R, et al. Artificial intelligence allows leaving-in-situ colorectal polyps. Clin Gastroenterol Hepatol 2022;20(11):2505–13.e4.
Rondonotti E, Hassan C, Tamanini G, et al. Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: The Artificial intelligence BLI Characterization (ABC) study. Endoscopy 2023;55(1):14–22.
Barua I, Wieszczy P, Kudo SE, et al. Real-time artificial intelligence–based optical diagnosis of neoplastic polyps during colonoscopy. NEJM Evidence 2022;1(6):EVIDoa2200003.
Gupta S, Lieberman D, Anderson JC, et al. Spotlight: US Multi-Society Task Force on Colorectal Cancer recommendations for follow-up after colonoscopy and polypectomy. Gastroenterology 2020;158(4):1154.
Hassan C, Antonelli G, Dumonceau JM, et al. Post-polypectomy colonoscopy surveillance: European Society of Gastrointestinal Endoscopy (ESGE) guideline: Update 2020. Endoscopy 2020;52(8):687–700.
Koo CS, Dolgunov D, Koh CJ. Key tips for using computer-aided diagnosis in colonoscopy - observations from two different platforms. Endoscopy 2021;54(10):1018–9.