Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening

被引:6
|
作者
Spadaccini, Marco [1 ,2 ]
Massimi, Davide [2 ]
Mori, Yuichi [3 ,4 ]
Alfarone, Ludovico [1 ]
Fugazza, Alessandro [2 ]
Maselli, Roberta [1 ,2 ]
Sharma, Prateek [5 ]
Facciorusso, Antonio [2 ]
Hassan, Cesare [1 ,2 ]
Repici, Alessandro [1 ,2 ]
机构
[1] Humanitas Univ, Dept Biomed Sci, I-20090 Rozzano, Italy
[2] Humanitas Clin & Res Ctr, Endoscopy Unit, IRCCS, I-20090 Rozzano, Italy
[3] Univ Oslo, Inst Hlth, Fac Med, Clin Effectiveness Res Grp, N-0315 Oslo, Norway
[4] Showa Univ, Digest Dis Ctr, Northern Yokohama Hosp, Yokohama 2240032, Japan
[5] Vet Affairs Med Ctr, Div Gastroenterol & Hepatol, Kansas City, MO 64128 USA
关键词
cancer; screening; colonoscopy; technology; innovation; DETECTION-ASSISTED COLONOSCOPY; ADENOMA DETECTION; DETECTION SYSTEM; SERRATED POLYPS; CLASSIFICATION; HISTOLOGY; RISK; PARTICIPATION; INCREASES; MORTALITY;
D O I
10.3390/diagnostics13061102
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest incidence reported in high-income countries. However, because of the slow progression of neoplastic precursors, along with the opportunity for their endoscopic detection and resection, a well-designed endoscopic screening program is expected to strongly decrease colorectal cancer incidence and mortality. In this regard, quality of colonoscopy has been clearly related with the risk of post-colonoscopy colorectal cancer. Recently, the development of artificial intelligence (AI) applications in the medical field has been growing in interest. Through machine learning processes, and, more recently, deep learning, if a very high numbers of learning samples are available, AI systems may automatically extract specific features from endoscopic images/videos without human intervention, helping the endoscopists in different aspects of their daily practice. The aim of this review is to summarize the current knowledge on AI-aided endoscopy, and to outline its potential role in colorectal cancer prevention.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] 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)
  • [22] Artificial Intelligence in Gastrointestinal Endoscopy
    Abadir, Alexander P.
    Ali, Mohammed Fahad
    Karnes, William
    Samarasena, Jason B.
    CLINICAL ENDOSCOPY, 2020, 53 (02) : 132 - 141
  • [23] 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
  • [24] Impact of an artificial intelligence-aided endoscopic diagnosis system on improving endoscopy quality for trainees in colonoscopy: Prospective, randomized, multicenter study
    Yamaguchi, Daisuke
    Shimoda, Ryo
    Miyahara, Koichi
    Yukimoto, Takahiro
    Sakata, Yasuhisa
    Takamori, Ayako
    Mizuta, Yumi
    Fujimura, Yutaro
    Inoue, Suma
    Tomonaga, Michito
    Ogino, Yuya
    Eguchi, Kohei
    Ikeda, Kei
    Tanaka, Yuichiro
    Takedomi, Hironobu
    Hidaka, Hidenori
    Akutagawa, Takashi
    Tsuruoka, Nanae
    Noda, Takahiro
    Tsunada, Seiji
    Esaki, Motohiro
    DIGESTIVE ENDOSCOPY, 2024, 36 (01) : 40 - 48
  • [25] Artificial intelligence-aided CT segmentation for body composition analysis: a validation study
    Borrelli, Pablo
    Kaboteh, Reza
    Enqvist, Olof
    Ulen, Johannes
    Traegardh, Elin
    Kjoelhede, Henrik
    Edenbrandt, Lars
    EUROPEAN RADIOLOGY EXPERIMENTAL, 2021, 5 (01)
  • [26] Effectiveness and application of artificial intelligence for endoscopic screening of colorectal cancer: the future is now
    Maida, Marcello
    Marasco, Giovanni
    Facciorusso, Antonio
    Shahini, Endrit
    Sinagra, Emanuele
    Pallio, Socrate
    Ramai, Daryl
    Murino, Alberto
    EXPERT REVIEW OF ANTICANCER THERAPY, 2023, 23 (07) : 719 - 729
  • [27] Effect of artificial intelligence-aided colonoscopy on the adenoma detection rate: A systematic review
    Mwango, Anson
    Akhtar, Tayyab Saeed
    Abbas, Sameen
    Abbasi, Dua Sadaf
    Khan, Amjad
    INTERNATIONAL JOURNAL OF GASTROINTESTINAL INTERVENTION, 2024, 13 (03): : 65 - 73
  • [28] Artificial intelligence in intestinal polyp and colorectal cancer prediction
    Sharma, Anju
    Kumar, Rajnish
    Yadav, Garima
    Garg, Prabha
    CANCER LETTERS, 2023, 565
  • [29] Disparities in Endoscopy Use for Colorectal Cancer Screening in the United States
    Gawron, Andrew J.
    Yadlapati, Rena
    DIGESTIVE DISEASES AND SCIENCES, 2014, 59 (03) : 530 - 537
  • [30] Artificial intelligence technologies for the detection of colorectal lesions: The future is now
    Attardo, Simona
    Chandrasekar, Viveksandeep Thoguluva
    Spadaccini, Marco
    Maselli, Roberta
    Patel, Harsh K.
    Desai, Madhav
    Capogreco, Antonio
    Badalamenti, Matteo
    Galtieri, Piera Alessia
    Pellegatta, Gaia
    Fugazza, Alessandro
    Carrara, Silvia
    Anderloni, Andrea
    Occhipinti, Pietro
    Hassan, Cesare
    Sharma, Prateek
    Repici, Alessandro
    WORLD JOURNAL OF GASTROENTEROLOGY, 2020, 26 (37) : 5606 - 5616