Opinion Review
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Nov 14, 2021; 27(42): 7240-7246
Published online Nov 14, 2021. doi: 10.3748/wjg.v27.i42.7240
Digital surgery for gastroenterological diseases
Niall Philip Hardy, Ronan Ambrose Cahill
Niall Philip Hardy, Ronan Ambrose Cahill, UCD Centre for Precision Surgery, University College Dublin, Dublin D07 Y9AW, Ireland
Author contributions: Hardy NP and Cahill RA were involved in the ideation, collation and drafting of this work.
Supported by Disruptive Technologies and Innovation Fund, Enterprise Ireland, Ireland.
Conflict-of-interest statement: Cahill RA receives speaker fees from Stryker Corp, Johnson and Johnson/Ethicon and Olympus, consultancy fees from Touch Surgery and DistalMotion, and research funding from Intuitive Surgery. Cahill RA also holds research funding from EU Horizon 2020 with Palliare and the Irish Government in collaboration with IBM Research in Ireland and Deciphex. Hardy NP is employed as a researcher in this collaboration.
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: Ronan Ambrose Cahill, FRCS, MBChB, MD, Professor, UCD Centre for Precision Surgery, University College Dublin, Eccles Street, Dublin D07 Y9AW, Ireland. ronan.cahill@ucd.ie
Received: April 30, 2021
Peer-review started: April 30, 2021
First decision: June 13, 2021
Revised: June 27, 2021
Accepted: October 20, 2021
Article in press: October 20, 2021
Published online: November 14, 2021

Advances in machine learning, computer vision and artificial intelligence methods, in combination with those in processing and cloud computing capability, portend the advent of true decision support during interventions in real-time and soon perhaps in automated surgical steps. Such capability, deployed alongside technology intraoperatively, is termed digital surgery and can be delivered without the need for high-end capital robotic investment. An area close to clinical usefulness right now harnesses advances in near infrared endolaparoscopy and fluorescence guidance for tissue characterisation through the use of biophysics-inspired algorithms. This represents a potential synergistic methodology for the deep learning methods currently advancing in ophthalmology, radiology, and recently gastroenterology via colonoscopy. As databanks of more general surgical videos are created, greater analytic insights can be derived across the operative spectrum of gastroenterological disease and operations (including instrumentation and operative step sequencing and recognition, followed over time by surgeon and instrument performance assessment) and linked to value-based outcomes. However, issues of legality, ethics and even morality need consideration, as do the limiting effects of monopolies, cartels and isolated data silos. Furthermore, the role of the surgeon, surgical societies and healthcare institutions in this evolving field needs active deliberation, as the default risks relegation to bystander or passive recipient. This editorial provides insight into this accelerating field by illuminating the near-future and next decade evolutionary steps towards widespread clinical integration for patient and societal benefit.

Keywords: Digital surgery, Artificial intelligence, Gastrointestinal disease, Biophysics, Deep learning, Fluorescence-guided surgery

Core Tip: Here, we introduce the concept of digital surgery and why it is important for everyone involved in the area of gastroenterological disease management. The current state and near-future of the art in this area are discussed, including the use of artificial intelligence methods to provide intraoperative real-time augmented decision making. Moral, ethical and legal challenges pertinent to digital surgery are explored, including the concerns relating to big data in health care and the transitioning role of industry in surgical development, as well as the implications such profound and imminent changes may have on the role of the clinician.