Artificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going?

被引:3
|
作者
Spadaccini, Marco [1 ,2 ]
Troya, Joel [3 ]
Khalaf, Kareem [4 ]
Facciorusso, Antonio [5 ]
Maselli, Roberta [1 ,2 ]
Hann, Alexander [3 ]
Repici, Alessandro [1 ,2 ]
机构
[1] IRCCS, Humanitas Res Hosp, Dept Endoscopy, I-20089 Rozzano, Italy
[2] Humanitas Univ, Dept Biomed Sci, I-20089 Rozzano, Italy
[3] Univ Hosp Wurzburg, Dept Internal Med 2, Intervent & Expt Endoscopy InExEn, Wurzburg, Germany
[4] Univ Toronto, St Michaels Hosp, Div Gastroenterol, Toronto, ON, Canada
[5] Univ Foggia, Dept Surg & Med Sci, Gastroenterol Unit, Foggia, Italy
关键词
Cancer; Screening; Colonoscopy; Artificial intelligence; COMPUTER-AIDED DETECTION; ADENOMA DETECTION; POLYP DETECTION; DETECTION SYSTEM; CLASSIFICATION; DIAGNOSIS; PARTICIPATION; HISTOLOGY; INCREASES; NEOPLASIA;
D O I
10.1016/j.dld.2024.01.203
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Colorectal cancer is a significant global health concern, necessitating effective screening strategies to reduce its incidence and mortality rates. Colonoscopy plays a crucial role in the detection and removal of colorectal neoplastic precursors. However, there are limitations and variations in the performance of endoscopists, leading to missed lesions and suboptimal outcomes. The emergence of artificial intelligence (AI) in endoscopy offers promising opportunities to improve the quality and efficacy of screening colonoscopies. In particular, AI applications, including computer-aided detection (CADe) and computer-aided characterization (CADx), have demonstrated the potential to enhance adenoma detection and optical diagnosis accuracy. Additionally, AI-assisted quality control systems aim to standardize the endoscopic examination process. This narrative review provides an overview of AI principles and discusses the current knowledge on AI-assisted endoscopy in the context of screening colonoscopies. It highlights the significant role of AI in improving lesion detection, characterization, and quality assurance during colonoscopy. However, further well-designed studies are needed to validate the clinical impact and cost-effectiveness of AI-assisted colonoscopy before its widespread implementation. (c) 2024 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1148 / 1155
页数:8
相关论文
共 50 条
  • [1] Artificial Intelligence-Assisted Colonoscopy for Colorectal Cancer Screening: A Multicenter Randomized Controlled Trial
    Xu, Hong
    Tang, Raymond S. Y.
    Lam, Thomas Y. T.
    Zhao, Guijun
    Lau, James Y. W.
    Liu, Yunpeng
    Wu, Qi
    Rong, Long
    Xu, Weiran
    Li, Xue
    Wong, Sunny H.
    Cai, Shuntian
    Wang, Jing
    Liu, Guanyi
    Ma, Tantan
    Liang, Xiong
    Mak, Joyce W. Y.
    Xu, Hongzhi
    Yuan, Peng
    Cao, Tingting
    Li, Fudong
    Ye, Zhenshi
    Shutian, Zhang
    Sung, Joseph J. Y.
    CLINICAL GASTROENTEROLOGY AND HEPATOLOGY, 2023, 21 (02) : 337 - 346.e3
  • [2] Effectiveness of artificial intelligence-assisted colonoscopy in early diagnosis of colorectal cancer: a systematic review
    Mehta, Aashna
    Kumar, Harendra
    Yazji, Katia
    Wireko, Andrew A.
    Nagarajan, Jai Sivanandan
    Ghosh, Bikona
    Nahas, Ahmad
    Ojeda, Luis Morales
    Anand, Ayush
    Sharath, Medha
    Huang, Helen
    Garg, Tulika
    Isik, Arda
    INTERNATIONAL JOURNAL OF SURGERY, 2023, 109 (04) : 946 - 952
  • [3] Advancing Colorectal Cancer Screening: A Comprehensive Systematic Review of Artificial Intelligence (AI)-Assisted Versus Routine Colonoscopy
    Thomas, Jingle
    Ravichandran, Rakshana
    Nag, Aiswarya
    Gupta, Lovish
    Singh, Mansi
    Panjiyar, Binay K.
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2023, 15 (09)
  • [4] Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening
    Spadaccini, Marco
    Massimi, Davide
    Mori, Yuichi
    Alfarone, Ludovico
    Fugazza, Alessandro
    Maselli, Roberta
    Sharma, Prateek
    Facciorusso, Antonio
    Hassan, Cesare
    Repici, Alessandro
    DIAGNOSTICS, 2023, 13 (06)
  • [5] Artificial intelligence-assisted colonoscopy: A review of current state of practice and research
    Taghiakbari, Mahsa
    Mori, Yuichi
    von Renteln, Daniel
    WORLD JOURNAL OF GASTROENTEROLOGY, 2021, 27 (47) : 8103 - 8122
  • [6] Artificial Intelligence-Assisted Colonoscopy for Polyp Detection
    Soleymanjahi, Saeed
    Huebner, Jack
    Elmansy, Lina
    Rajashekar, Niroop
    Ludtke, Nando
    Paracha, Rumzah
    Thompson, Rachel
    Grimshaw, Alyssa A.
    Foroutan, Farid
    Sultan, Shahnaz
    Shung, Dennis L.
    ANNALS OF INTERNAL MEDICINE, 2024,
  • [7] Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial
    Lui, Thomas Ka-Luen
    Lam, Carla Pui-Mei
    To, Elvis Wai-Pan
    Ko, Michael Kwan-Lung
    Tsui, Vivien Wai Man
    Liu, Kevin Sze-Hang
    Hui, Cynthia Ka-Yin
    Cheung, Michael Ka-Shing
    Mak, Loey Lung-Yi
    Hui, Rex Wan-Hin
    Wong, Siu-Yin
    Seto, Wai Kay
    Leung, Wai K.
    AMERICAN JOURNAL OF GASTROENTEROLOGY, 2024, 119 (07): : 1318 - 1325
  • [8] Artificial intelligence-assisted detection and classification of colorectal polyps under colonoscopy: a systematic review and meta-analysis
    Wang, Aling
    Mo, Jiahao
    Zhong, Cailing
    Wu, Shaohua
    Wei, Sufen
    Tu, Binqi
    Liu, Chang
    Chen, Daman
    Xu, Qing
    Cai, Mengyi
    Li, Zhuoyao
    Xie, Wenting
    Xie, Miao
    Kato, Motohiko
    Xi, Xujie
    Zhang, Beiping
    ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (22)
  • [9] Application of artificial intelligence in colorectal cancer screening by colonoscopy: Future prospects (Review)
    Ding, Menglu
    Yan, Junbin
    Chao, Guanqun
    Zhang, Shuo
    ONCOLOGY REPORTS, 2023, 50 (05)
  • [10] The Role of Artificial Intelligence in Colorectal Cancer Screening: Lesion Detection and Lesion Characterization
    Young, Edward
    Edwards, Louisa
    Singh, Rajvinder
    CANCERS, 2023, 15 (21)