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World J Gastroenterol. May 14, 2021; 27(18): 2122-2130
Published online May 14, 2021. doi: 10.3748/wjg.v27.i18.2122
Magnetic resonance imaging-based artificial intelligence model in rectal cancer
Pei-Pei Wang, Chao-Lin Deng, Bin Wu
Pei-Pei Wang, Chao-Lin Deng, Bin Wu, Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
Author contributions: Wu B designed and revised the review; Wang PP collected the literature for recent advances in the field and wrote the manuscript; Deng CL modified the article format; all authors have read and approved the final version to be published.
Conflict-of-interest statement: The authors have nothing to declare.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Bin Wu, MD, Professor, Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifu Yuan, Dongcheng District, Beijing 100730, China. wubin0279@hotmail.com
Received: January 10, 2021
Peer-review started: January 10, 2021
First decision: February 11, 2021
Revised: February 23, 2021
Accepted: March 16, 2021
Article in press: March 16, 2021
Published online: May 14, 2021
Processing time: 120 Days and 3.8 Hours
Abstract

Rectal magnetic resonance imaging (MRI) is the preferred method for the diagnosis of rectal cancer as recommended by the guidelines. Rectal MRI can accurately evaluate the tumor location, tumor stage, invasion depth, extramural vascular invasion, and circumferential resection margin. We summarize the progress of research on the use of artificial intelligence (AI) in rectal cancer in recent years. AI, represented by machine learning, is being increasingly used in the medical field. The application of AI models based on high-resolution MRI in rectal cancer has been increasingly reported. In addition to staging the diagnosis and localizing radiotherapy, an increasing number of studies have reported that AI models based on high-resolution MRI can be used to predict the response to chemotherapy and prognosis of patients.

Keywords: Artificial intelligence; Deep learning; Colorectal cancer; Magnetic resonance imaging; Radiomics

Core Tip: Recently, there has been an increase in the use of artificial intelligence (AI) models based on magnetic resonance (MR) images in locally advanced rectal cancer. MR imaging based on big datasets helps in the provision of systematic and precise medical services to patients with rectal cancer in the treatment process. This review summarizes recent research progress on the application of AI based on MR images in rectal cancer.