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

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.

International consensus on anatomical structures to identify on ultrasound for the performance of basic blocks in ultrasound-guided regional anesthesia.

There is no universally agreed set of anatomical structures that must be identified on ultrasound for the performance of ultrasound-guided regional anesthesia (UGRA) techniques. This study aimed to produce standardized recommendations for core (minimum) structures to identify during seven basic blocks. An international consensus was sought through a modified Delphi process. A long-list of anatomical structures was refined through serial review by key opinion leaders in UGRA. All rounds were conducted remotely and anonymously to facilitate equal contribution of each participant. Blocks were considered twice in each round: for "orientation scanning" (the dynamic process of acquiring the final view) and for the "block view" (which visualizes the block site and is maintained for needle insertion/injection). Strong recommendations for inclusion were made if ≥75% of participants rated a structure as "definitely include" in any round. Weak recommendations were made if >50% of participants rated a structure as "definitely include" or "probably include" for all rounds (but the criterion for "strong recommendation" was never met). Thirty-six participants (94.7%) completed all rounds. 128 structures were reviewed; a "strong recommendation" is made for 35 structures on orientation scanning and 28 for the block view. A "weak recommendation" is made for 36 and 20 structures, respectively. This study provides recommendations on the core (minimum) set of anatomical structures to identify during ultrasound scanning for seven basic blocks in UGRA. They are intended to support consistent practice, empower non-experts using basic UGRA techniques, and standardize teaching and research.