ArticleBritish journal of anaesthesia2023
Evaluation of the impact of assistive artificial intelligence on ultrasound scanning for regional anaesthesia.
Article in British journal of anaesthesia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Pilot Study to Evaluate Anaesthetists' Ultrasound Scanning & Interpretation Performance for Ultrasound-guided Regional Anaesthesia - With & Without the Assistance of an Artificial Intelligence Device ScanNav Anatomy Peripheral Nerve Block
Application of Ultrasound-guided Non-invasive Simulated Puncture Technique in Standardized Residency Training in Anesthesiology
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of artificial intelligence in peripheral neurosurgery: a systematic review.Neurosurgical review · 2026Pooled it
- Artificial intelligence-generated color overlay for ultrasound identification of the brachial plexus in regional anesthesia: an external validation study.Journal of anesthesia · 2026Article
- Deep Learning-Based Tracking of Neurovascular Features Toward Semi-Automated Ultrasound-Guided Peripheral Nerve Blocks by Non-Specialists.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial intelligence in anesthesiology education: transformative applications, challenges, and future perspectives.Frontiers in medicine · 2026Review
- Precision perioperative AI: from signals, images, and records to applications in anesthesia-a narrative mini-review proposing an operational framework.Frontiers in medicine · 2026Review
- Artificial Intelligence in Anaesthesiology: Current Applications, Challenges, and Future Directions.Turkish journal of anaesthesiology and reanimation · 2025Article
- Artificial intelligence in ultrasound-guided regional anesthesia: bridging the gap between potential and practice: a narrative review.Anesthesia and pain medicine · 2025Review
- Review
- Thoracic segmental spinal anaesthesia: expanding applications while keeping it safe.British journal of anaesthesia · 2025Article
- Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.EClinicalMedicine · 2025Article
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
- Artificial intelligence in anesthesiology: a bibliometric analysis.Perioperative medicine (London, England) · 2024Review
- Current evidence on artificial intelligence in regional anesthesia.World journal of clinical cases · 2024Review
- Artificial intelligence-assisted ultrasound-guided regional anaesthesia: An explorative scoping review.Journal of experimental orthopaedics · 2024Article
- Artificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines.British journal of anaesthesia · 2024Article
- Research priorities in regional anaesthesia: an international Delphi study.British journal of anaesthesia · 2024Review
- Artificial Intelligence-Supported Ultrasonography in Anesthesiology: Evaluation of a Patient in the Operating Theatre.Journal of personalized medicine · 2024Review
- Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review.Healthcare (Basel, Switzerland) · 2024Review
- Prospective randomized evaluation of the sustained impact of assistive artificial intelligence on anesthetists' ultrasound scanning for regional anesthesia.BMJ surgery, interventions, & health technologies · 2024Article
- Regional anaesthesia training in the UK - a national survey.BJA open · 2023Article
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUltrasound-guided regional anaesthesia relies on the visualisation of key landmark, target, and safety structures on ultrasound. However, this can be challenging, particularly for inexperienced practitioners. Artificial intelligence (AI) is increasingly being applied to medical image interpretation, including ultrasound. In this exploratory study, we evaluated ultrasound scanning performance by non-experts in ultrasound-guided regional anaesthesia, with and without the use of an assistive AI device.
methodsTwenty-one anaesthetists, all non-experts in ultrasound-guided regional anaesthesia, underwent a standardised teaching session in ultrasound scanning for six peripheral nerve blocks. All then performed a scan for each block; half of the scans were performed with AI assistance and half without. Experts assessed acquisition of the correct block view and correct identification of sono-anatomical structures on each view. Participants reported scan confidence, experts provided a global rating score of scan performance, and scans were timed.
resultsExperts assessed 126 ultrasound scans. Participants acquired the correct block view in 56/62 (90.3%) scans with the device compared with 47/62 (75.1%) without (P=0.031, two data points lost). Correct identification of sono-anatomical structures on the view was 188/212 (88.8%) with the device compared with 161/208 (77.4%) without (P=0.002). There was no significant overall difference in participant confidence, expert global performance score, or scan time.
conclusionsUse of an assistive AI device was associated with improved ultrasound image acquisition and interpretation. Such technology holds potential to augment performance of ultrasound scanning for regional anaesthesia by non-experts, potentially expanding patient access to these techniques. CLINICAL
trial registrationNCT05156099.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.