Systematic Reviews
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Gastroenterol. Dec 8, 2023; 4(3): 64-71
Published online Dec 8, 2023. doi: 10.35712/aig.v4.i3.64
Use of artificial intelligence in total mesorectal excision in rectal cancer surgery: State of the art and perspectives
Vinicio Mosca, Giacomo Fuschillo, Guido Sciaudone, Kapil Sahnan, Francesco Selvaggi, Gianluca Pellino
Vinicio Mosca, Giacomo Fuschillo, Francesco Selvaggi, Gianluca Pellino, Department of Advanced Medical and Surgical Sciences, Università degli Studi della Campania “Luigi Vanvitelli”, Napoli 80138, Italy
Guido Sciaudone, Department of Medicine and Health Sciences “Vincenzo Tiberio”, University of Molise, Campobasso 86100, Italy
Kapil Sahnan, Department of Colorectal Surgery, St Mark’s Hospital, London HA1 3UJ, United Kingdom
Kapil Sahnan, Department of Surgery and Cancer, Imperial College London, London SW7 5NH, United Kingdom
Gianluca Pellino, Colorectal Surgery, Vall d’Hebron University Hospital, Barcelona 08035, Spain
Author contributions: Mosca V and Pellino G conceived and presented the idea; Mosca V and Fuschillo G wrote the manuscript with the support of Sahnan K and Pellino G; Sciaudone G, Sahnan K, and Selvaggi F supervised the results of this work; Pellino G oversaw the process and was responsible for the overall planning and management; All authors discussed the results and contributed to the final manuscript.
Conflict-of-interest statement: Dr. Pellino has nothing to disclose. The other authors make no declarations regarding their potential conflicts of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Gianluca Pellino, FACS, FASCRS, FEBS, FRCP, FRCS (Gen Surg), MD, PhD, Associate Professor, Surgeon, Department of Advanced Medical and Surgical Sciences, Università degli Studi della Campania “Luigi Vanvitelli”, Policlinico CS, Piazza Miraglia 2, Napoli 80138, Italy. gianluca.pellino@unicampania.it
Received: July 27, 2023
Peer-review started: July 27, 2023
First decision: August 31, 2023
Revised: September 13, 2023
Accepted: October 23, 2023
Article in press: October 23, 2023
Published online: December 8, 2023
ARTICLE HIGHLIGHTS
Research background

Colorectal cancer is a major public health problem, with 1.9 million new cases and 953000 deaths worldwide in 2020. Total mesorectal excision (TME) is the standard of care for the treatment of rectal cancer, but it is a technically challenging surgery. Artificial intelligence (AI) has the potential to improve the performance of TME surgery, especially for surgeons who are still at the beginning of their learning curve.

Research motivation

AI in surgery is a rapidly evolving field with applications in the preoperative, intraoperative, and postoperative settings. In colorectal surgery, AI has been used to automate tasks such as instrument detection and anatomical structure identification. AI has also been used to develop image-guided navigation systems for TME surgery. One of the challenges of AI in surgery is the complexity of the images. Another challenge is the variability of surgical procedures. Recent advances in deep learning have made it possible to develop more accurate and robust AI algorithms for surgical applications.

Research objectives

To investigate the potential of AI in surgery, particularly in colorectal surgery, and the current state of the art. To describe AI algorithms for surgical applications, such as instrument detection, anatomical structure identification, and image-guided navigation systems. To describe their limitations and future developments, such as AI algorithms that can be used in real time. To propose the evaluation of the safety and efficacy of AI in surgery through clinical trials.

Research methods

A literature search was conducted to identify relevant studies on the use of AI in rectal cancer surgery and specifically in TME. The search was performed using the PubMed electronic database and was limited to studies published between 2020 and 2023. Only articles published in English were included.

Research results

The use of AI in rectal cancer surgery and specifically in TME is a rapidly evolving field. There are a number of different AI algorithms that have been developed for use in TME, including algorithms for instrument detection, anatomical structure identification, and image-guided navigation systems.

Research conclusions

The results of these studies are promising, but more research is needed to fully evaluate the safety and efficacy of AI in TME. Challenges that need to be overcome before AI can be widely adopted in TME include the need for large datasets of labeled images to train AI algorithms, the need to develop AI algorithms that can be used in real-time, and the need to address the ethical concerns raised by the use of AI in surgery.

Research perspectives

AI has the potential to revolutionize TME by providing real-time surgical guidance, preventing complications, and improving training. However, more research is needed to fully understand the benefits and risks of AI in TME.