Application of artificial intelligence in colorectal cancer screening by colonoscopy: Future prospects (Review)

被引:4
作者
Ding, Menglu [1 ]
Yan, Junbin [1 ]
Chao, Guanqun [2 ]
Zhang, Shuo [1 ]
机构
[1] Zhejiang Chinese Med Univ, Affiliated Hosp 2, Xin Hua Hosp Zhejiang Prov, 318 Chaowang Rd, Hangzhou 310000, Zhejiang, Peoples R China
[2] Zhejiang Univ, Sir Run Run Shaw Hosp, Dept Gen Practice, 3 East Qing Chun Rd, Hangzhou 310000, Zhejiang, Peoples R China
关键词
colorectal cancer; artificial intelligence; colonoscopy; CADe; CADx; prospect; COMPUTER-AIDED DIAGNOSIS; ADENOMA DETECTION RATE; DETECTION SYSTEM; CLASSIFICATION; MORTALITY; POLYPS; ASSOCIATION; SERVICES; LESIONS; TRIAL;
D O I
10.3892/or.2023.8636
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Colorectal cancer (CRC) has become a severe global health concern, with the third-high incidence and second-high mortality rate of all cancers. The burden of CRC is expected to surge to 60% by 2030. Fortunately, effective early evidence-based screening could significantly reduce the incidence and mortality of CRC. Colonoscopy is the core screening method for CRC with high popularity and accuracy. Yet, the accuracy of colonoscopy in CRC screening is related to the experience and state of operating physicians. It is challenging to maintain the high CRC diagnostic rate of colonoscopy. Artificial intelligence (AI)-assisted colonoscopy will compensate for the above shortcomings and improve the accuracy, efficiency, and quality of colonoscopy screening. The unique advantages of AI, such as the continuous advancement of high-performance computing capabilities and innovative deep-learning architectures, which hugely impact the control of colorectal cancer morbidity and mortality expectancy, highlight its role in colonoscopy screening.
引用
收藏
页数:11
相关论文
共 99 条
[11]   Protection From Colorectal Cancer After Colonoscopy A Population-Based, Case-Control Study [J].
Brenner, Hermann ;
Chang-Claude, Jenny ;
Seiler, Christoph M. ;
Rickert, Alexander ;
Hoffmeister, Michael .
ANNALS OF INTERNAL MEDICINE, 2011, 154 (01) :22-U156
[12]   National post-colonoscopy colorectal cancer data challenge services to improve quality of colonoscopy [J].
Burr, Nicholas ;
Valori, Roland .
ENDOSCOPY INTERNATIONAL OPEN, 2019, 7 (05) :E728-E729
[13]   Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model [J].
Byrne, Michael F. ;
Chapados, Nicolas ;
Soudan, Florian ;
Oertel, Clemens ;
Linares Perez, Milagros ;
Kelly, Raymond ;
Iqbal, Nadeem ;
Chandelier, Florent ;
Rex, Douglas K. .
GUT, 2019, 68 (01) :94-100
[14]   Colonoscopy Quality Metrics and Implementation [J].
Calderwood, Audrey H. ;
Jacobson, Brian C. .
GASTROENTEROLOGY CLINICS OF NORTH AMERICA, 2013, 42 (03) :599-+
[15]   Fecal DNA Testing for Colorectal Cancer Screening [J].
Carethers, John M. .
ANNUAL REVIEW OF MEDICINE, VOL 71, 2020, 2020, 71 :59-69
[16]   Accurate Classification of Diminutive Colorectal Polyps Using Computer-Aided Analysis [J].
Chen, Peng-Jen ;
Lin, Meng-Chiung ;
Lai, Mei-Ju ;
Lin, Jung-Chun ;
Lu, Henry Horng-Shing ;
Tseng, Vincent S. .
GASTROENTEROLOGY, 2018, 154 (03) :568-575
[17]   Effectiveness of fecal immunochemical testing in reducing colorectal cancer mortality from the One Million Taiwanese Screening Program [J].
Chiu, Han-Mo ;
Chen, Sam Li-Sheng ;
Yen, Amy Ming-Fang ;
Chiu, Sherry Yueh-Hsia ;
Fann, Jean Ching-Yuan ;
Lee, Yi-Chia ;
Pan, Shin-Liang ;
Wu, Ming-Shiang ;
Liao, Chao-Sheng ;
Chen, Hsiu-Hsi ;
Koong, Shin-Lan ;
Chiou, Shu-Ti .
CANCER, 2015, 121 (18) :3221-3229
[18]   Marketing and US Food and Drug Administration Clearance of Artificial Intelligence and Machine Learning Enabled Software in and as Medical Devices: A Systematic Review [J].
Clark, Phoebe ;
Kim, Jayne ;
Aphinyanaphongs, Yindalon .
JAMA NETWORK OPEN, 2023, 6 (07) :E2321792
[19]   Association of Colonoscopy Adenoma Findings With Long-term Colorectal Cancer Incidence [J].
Click, Benjamin ;
Pinsky, Paul F. ;
Hickey, Tom ;
Doroudi, Maryam ;
Schoen, Robert E. .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2018, 319 (19) :2021-2031
[20]  
Corley DA, 2014, NEW ENGL J MED, V370, P2541, DOI [10.1056/NEJMc1405329, 10.1056/NEJMoa1309086]