713 The Application of Artificial Intelligence for Digital Imaging in the Operating Theatre: A Systematic Review and Narrative Synthesis. (19th August 2022)
- Record Type:
- Journal Article
- Title:
- 713 The Application of Artificial Intelligence for Digital Imaging in the Operating Theatre: A Systematic Review and Narrative Synthesis. (19th August 2022)
- Main Title:
- 713 The Application of Artificial Intelligence for Digital Imaging in the Operating Theatre: A Systematic Review and Narrative Synthesis
- Authors:
- Hardacre, Conor
Fowler, George
Quek, Fang Fang
Skilton, Anni
Blencowe, Natalie
Macefield, Rhiannon - Abstract:
- Abstract: Introduction: Promising applications of artificial intelligence (AI) in healthcare are emerging. This systematic review aims to identify and synthesise applications of digital-imaging AI in surgery and inform future work. Method: Systematic database searches (Medline, Embase, CENTRAL) were undertaken. Studies concerning digital-imaging AI within the operating theatre were identified from title and abstract screening. Selection was further refined to identify video-based AI models with direct supportive output to the surgeon within the operating theatre. Results: 48 studies were included. Studies spanned 13 specialty groupings, with n=42 utilising a pre-specified dataset and the remaining n=6 using AI with human participants. The most common field using AI was urology (n=9 studies). Applications were most commonly for navigation and visualisation support (n=26 studies across 10 surgical specialties) and AI-based intelligent detection systems, intended to identify and highlight useful surgical information using computer-vision pattern recognition (n=18 articles across n=6 specialties). Other applications included video-processing algorithms (n=3 studies across 2 specialties), and a novel imaging modality for visualising blood perfusion (n=1 study), proposing operating theatre-based application. High-performance models were identified across a range of pathologies. This manifested as minimal overlay errors and acceptable frame rates for navigation tools, and highAbstract: Introduction: Promising applications of artificial intelligence (AI) in healthcare are emerging. This systematic review aims to identify and synthesise applications of digital-imaging AI in surgery and inform future work. Method: Systematic database searches (Medline, Embase, CENTRAL) were undertaken. Studies concerning digital-imaging AI within the operating theatre were identified from title and abstract screening. Selection was further refined to identify video-based AI models with direct supportive output to the surgeon within the operating theatre. Results: 48 studies were included. Studies spanned 13 specialty groupings, with n=42 utilising a pre-specified dataset and the remaining n=6 using AI with human participants. The most common field using AI was urology (n=9 studies). Applications were most commonly for navigation and visualisation support (n=26 studies across 10 surgical specialties) and AI-based intelligent detection systems, intended to identify and highlight useful surgical information using computer-vision pattern recognition (n=18 articles across n=6 specialties). Other applications included video-processing algorithms (n=3 studies across 2 specialties), and a novel imaging modality for visualising blood perfusion (n=1 study), proposing operating theatre-based application. High-performance models were identified across a range of pathologies. This manifested as minimal overlay errors and acceptable frame rates for navigation tools, and high diagnostic performance for detection systems (determined by area-under-the-receiver-operating-characteristic-curve, sensitivity/specificity, negative/positive predictive values). Conclusions: There is evidence to suggest AI for intraoperative surgeon-support has potential, particularly through augmented-reality navigation and AI-enabled information awareness. Further research and optimisations are required to produce clinically robust models, which remain high-performance despite case variability. Such AI may support improved surgical access, efficiency, and outcomes. … (more)
- Is Part Of:
- British journal of surgery. Volume 109(2022)Supplement 6
- Journal:
- British journal of surgery
- Issue:
- Volume 109(2022)Supplement 6
- Issue Display:
- Volume 109, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 109
- Issue:
- 6
- Issue Sort Value:
- 2022-0109-0006-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-19
- Subjects:
- Surgery -- Periodicals
617.005 - Journal URLs:
- http://www.bjs.co.uk/bjsCda/cda/microHome.do ↗
https://academic.oup.com/bjs# ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1093/bjs/znac268.011 ↗
- Languages:
- English
- ISSNs:
- 0007-1323
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2325.000000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23063.xml