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Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia.

Abstract:
Introduction Ultrasound-guided regional anesthesia (UGRA) involves the acquisition and interpretation of ultrasound images to delineate sonoanatomy. This study explores the utility of a novel artificial intelligence (AI) device designed to assist in this task (ScanNav Anatomy Peripheral Nerve Block; ScanNav), which applies a color overlay on real-time ultrasound to highlight key anatomical structures.
Methods Thirty anesthesiologists, 15 non-experts and 15 experts in UGRA, performed 240 ultrasound scans across nine peripheral nerve block regions. Half were performed with ScanNav. After scanning each block region, participants completed a questionnaire on the utility of the device in relation to training, teaching, and clinical practice in ultrasound scanning for UGRA. Ultrasound and color overlay output were recorded from scans performed with ScanNav. Experts present during the scans (real-time experts) were asked to assess potential for increased risk associated with use of the device (eg, needle trauma to safety structures). This was compared with experts who viewed the AI scans remotely.
Results Non-experts were more likely to provide positive and less likely to provide negative feedback than experts (p=0.001). Positive feedback was provided most frequently by non-experts on the potential role for training (37/60, 61.7%); for experts, it was for its utility in teaching (30/60, 50%). Real-time and remote experts reported a potentially increased risk in 12/254 (4.7%) vs 8/254 (3.1%, p=0.362) scans, respectively.
Discussion ScanNav shows potential to support non-experts in training and clinical practice, and experts in teaching UGRA. Such technology may aid the uptake and generalizability of UGRA.
Trial registration number NCT04918693.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1136/rapm-2021-103368

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Oxford college:
Jesus College
Role:
Author
ORCID:
0000-0002-8665-1984
More by this author
Role:
Author
ORCID:
0000-0002-9912-717X
More by this author
Role:
Author
ORCID:
0000-0002-1924-801X
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Hilda's College
Role:
Author
ORCID:
0000-0002-3060-3772
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0001-5796-0377


Publisher:
BMJ Publishing Group
Journal:
Regional Anesthesia and Pain Medicin More from this journal
Volume:
47
Issue:
6
Pages:
375-379
Publication date:
2022-01-28
Acceptance date:
2022-01-10
DOI:
EISSN:
1532-8651
ISSN:
1098-7339
Pmid:
35091395


Language:
English
Keywords:
Pubs id:
1237610
Local pid:
pubs:1237610
Deposit date:
2022-08-05

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