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Ultrasound-guided acquisition of correct block view in novice anaesthetists improved by AI

23rd September 2022

The ultrasound-guided acquisition of the correct block view is significantly better among novice anaesthetists with AI assistance

Ultrasound-guided image acquisition of the correct block view and identification of the correct sono-anatomical structure is significantly improved among novice anaesthetists when given access to an assistive artificial intelligence (AI) device according to the findings of a randomised trial by UK researchers.

Successful ultrasound-guided regional anaesthesia requires adequate visualisation of neural and surrounding structures together with monitoring the spread of a local anaesthetic. In fact, the initial challenge presented to a practitioner during ultrasound-guided regional anaesthesia is the interpretation of sono-anatomy upon placing a probe on the patient.

The use of AI for real-time anatomy identification can successfully interpret anatomical structures in real-time sonography and assist young anaesthesiologists during ultrasound-guided peripheral nerve block. Moreover, the use of an AI system has been shown to be helpful in identifying specific anatomical structures and for confirming the correct ultrasound view in scans.

Nevertheless, while AI systems aid recognition of structures, the additional value of an AI system over that of a novice anaesthetist who has undergone training, is somewhat less clear. For the present study, the UK recruited non-expert anaesthetics who underwent standard training in ultrasound scanning for six peripheral nerve blocks.

The researchers undertook a randomised, prospective interventional study to evaluate the impact of an AI system (ScanNav) on the performance of these novice anaesthetists during ultrasound scanning for specific nerve blocks.

The secondary aim was to determine if the AI system improved upon the correct identification of sono-anatomical structures on the block view. The novices performed a single scan of 6 peripheral nerve blocks while being assessed by an expert. Following this training, all performed a scan for each of the six blocks, half of which were performed using the AI tool.

Ultrasound-guided scanning and the AI support tool

A total of 21 novice anaesthetists were recruited and a total of 126 scans were undertaken. Participants identified the correct block view in 75.1% of scans without the AI system, though this figure increased to 90.3% (p = 0.031) with the system.

Additionally, identification of the correct structure improved from 77.4% to 88.8% when using the AI system (p = 0.002). However, there were no significant differences in self-reported confidence or the time required to perform the scan between aided and unaided scans.

The authors concluded that use of the AI system among non-expert anaesthetists, improved ultrasound image acquisition and interpretation, adding that in the future such technology may be of value to augment the performance of non-experts and expand patient access to the technique.

Bowness JS et al. Evaluation of the impact of assistive artificial intelligence on ultrasound scanning for regional anaesthesia Br J Anaesth 2022