Intraoperative Applications of Artificial Intelligence in Robotic Surgery: A Scoping Review of Current Development Stages and Levels of Autonomy

Baptiste Vasey; Karoline A N Lippert; Danyal Z Khan; Mudathir Ibrahim; Chan Hee Koh; Hugo Layard Horsfall; Keng Siang Lee; Simon Williams; Hani J Marcus; Peter McCulloch

doi:10.1097/SLA.0000000000005700

Intraoperative Applications of Artificial Intelligence in Robotic Surgery: A Scoping Review of Current Development Stages and Levels of Autonomy

Ann Surg. 2023 Dec 1;278(6):896-903. doi: 10.1097/SLA.0000000000005700. Epub 2022 Sep 30.

Authors

Baptiste Vasey^{1

2

3}, Karoline A N Lippert⁴, Danyal Z Khan^{5

6}, Mudathir Ibrahim^{1

7}, Chan Hee Koh^{5

6}, Hugo Layard Horsfall^{5

6}, Keng Siang Lee⁸, Simon Williams^{5

6}, Hani J Marcus^{5

6}, Peter McCulloch¹

Affiliations

¹ Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
² Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK.
³ Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
⁴ Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁵ Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
⁶ Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.
⁷ Department of General Surgery, Maimonides Medical Center, Brooklyn, NY.
⁸ Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK.

Abstract

Objective: A scoping review of the literature was conducted to identify intraoperative artificial intelligence (AI) applications for robotic surgery under development and categorize them by (1) purpose of the applications, (2) level of autonomy, (3) stage of development, and (4) type of measured outcome.

Background: In robotic surgery, AI-based applications have the potential to disrupt a field so far based on a master-slave paradigm. However, there is no available overview about this technology's current stage of development and level of autonomy.

Methods: MEDLINE and EMBASE were searched between January 1, 2010 and May 21, 2022. Abstract screening, full-text review, and data extraction were performed independently by 2 reviewers. The level of autonomy was defined according to the Yang and colleagues' classification and stage of development according to the Idea, Development, Evaluation, Assessment, and Long-term follow-up framework.

Results: One hundred twenty-nine studies were included in the review. Ninety-seven studies (75%) described applications providing Robot Assistance (autonomy level 1), 30 studies (23%) application enabling Task Autonomy (autonomy level 2), and 2 studies (2%) application achieving Conditional autonomy (autonomy level 3). All studies were at Idea, Development, Evaluation, Assessment, and Long-term follow-up stage 0 and no clinical investigations on humans were found. One hundred sixteen (90%) conducted in silico or ex vivo experiments on inorganic material, 9 (7%) ex vivo experiments on organic material, and 4 (3%) performed in vivo experiments in porcine models.

Conclusions: Clinical evaluation of intraoperative AI applications for robotic surgery is still in its infancy and most applications have a low level of autonomy. With increasing levels of autonomy, the evaluation focus seems to shift from AI-specific metrics to process outcomes, although common standards are needed to allow comparison between systems.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Animals
Artificial Intelligence
Benchmarking
Humans
Robotic Surgical Procedures*
Swine

Abstract

Publication types

MeSH terms

Grants and funding