Real-time AI-assisted nerve tracking for ultrasound-guided nerve identification: a prospective randomized trial

Artificial intelligence (AI)-assisted nerve tracking facilitates real-time ultrasound-guided nerve identification, but its effect on independent nerve identification after AI support is removed remains uncertain.

In this prospective randomized trial, 80 ultrasound novices (60 medical students and 20 anesthesiology residents) were assigned to either a control group receiving B-mode ultrasound training without AI assistance or an AI-assisted group using a real-time nerve tracking system (NerveTrack). Following a standardized lecture and a 10-minute hands-on training session, participants underwent assessment with the AI function disabled. The primary outcome was first-attempt independent identification success for the median nerve and supraclavicular brachial plexus. Secondary outcomes included performance after additional training and self-reported confidence.

78 participants completed the study. First-attempt independent identification success rates did not differ significantly between the control and AI-assisted groups for the median nerve (57.5% vs 65.8%; RR 1.14, 95% CI 0.81 to 1.62; p=0.452) or the brachial plexus (35.0% vs 42.1%; RR 1.20, 95% CI 0.68 to 2.11; p=0.519). Following additional AI-assisted training, participants in the AI-assisted group reported greater confidence in identifying the brachial plexus than those in the control group (4.7±0.5 vs 4.4±0.9; p=0.046). No significant differences were observed in independent identification success after additional training.

Brief AI-assisted training did not improve immediate independent ultrasound identification of the median nerve or supraclavicular brachial plexus after AI support was removed. These findings do not establish long-term retention, transfer to unfamiliar anatomy, or clinical procedural performance.

NCT05857787.