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

被引:11
作者
Vasey, Baptiste [1 ,2 ,3 ]
Lippert, Karoline A. N. [4 ]
Khan, Danyal Z. [5 ,6 ]
Ibrahim, Mudathir [1 ,8 ]
Koh, Chan Hee [5 ,6 ]
Horsfall, Hugo Layard [5 ,6 ]
Lee, Keng Siang [7 ]
Williams, Simon [5 ,6 ]
Marcus, Hani J. [5 ,6 ]
McCulloch, Peter [1 ]
机构
[1] Univ Oxford, Nuffield Dept Surg Sci, Oxford, England
[2] Univ Oxford, Inst Biomed Engn, Dept Engn Sci, Oxford, England
[3] Univ Oxford, Nuffield Dept Clin Neurosci, Crit Care Res Grp, Oxford, England
[4] Kings Coll London, Inst Psychiat Psychol & Neurosci, London, England
[5] Natl Hosp Neurol & Neurosurg, Dept Neurosurg, London, England
[6] UCL, Wellcome EPSRC Ctr Intervent & Surg Sci, London, England
[7] Univ Bristol, Fac Hlth Sci, Bristol Med Sch, Bristol, England
[8] Maimonides Hosp, Dept Gen Surg, Brooklyn, NY 11219 USA
基金
英国惠康基金; 英国工程与自然科学研究理事会;
关键词
artificial intelligence; autonomy; evaluation; IDEAL; intraoperative; machine learning; outcomes; performance; robotic; surgery; FRAMEWORK;
D O I
10.1097/SLA.0000000000005700
中图分类号
R61 [外科手术学];
学科分类号
摘要
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.
引用
收藏
页码:896 / 903
页数:8
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