Augmented reality-guided craniofacial and airway nerve block training for anesthesiology residents.

Abstract

The acquisition of craniofacial and airway nerve block (ANB) skills is hindered by the complex anatomy involved, reliance on landmark-guided techniques, and the absence of simulation-based training tools. Augmented reality offers a promising platform for procedural training by providing real-time visual feedback, yet its potential to improve accuracy in ANBs has not been evaluated. This exploratory study assessed the feasibility of AR guidance for improving nerve block performance among anesthesiology faculty and residents.20 participants performed infraorbital, inferior alveolar, superior laryngeal, and glossopharyngeal nerve blocks with and without AR guidance using volumetric Digital Imaging and Communications in Medicine (DICOM) reconstructions superimposed on body donor heads via Hololens headset, from Microsoft Corporation and SurgicalAR software from Medivis. AR guidance included a localizer instrument for real-time tracking of a physical needle along a premapped virtual needle path. Performance was assessed by dissection-based accuracy (proximity of methylene blue to the nerve) and procedure time.Overall clinical acceptability was similar between AR and non-AR conditions (65.0% vs 55.0%, McNemar's p=0.754). There were no differences in performance when stratified by level of training (McNemar p=0.219 for residents; McNemar p=0.625 for faculty). However, AR significantly increased procedure time (overall 49.9±8.4 vs 14.5±2.6 s, Wilcoxon p<0.001) and time increases were consistent across training levels (faculty: +34.9 s, p=0.016; residents: +36.0 s, p=0.062). Additionally, there was no difference in nerve block success or procedure length between an overlay mode with the DICOM superimposed onto the body donor and a detached mode with the DICOM floating above or next to the body donor.In this small, exploratory study, AR did not significantly impact the rates of clinically acceptable nerve blocks when performed by faculty or resident anesthesiologists; however, AR significantly increased the amount of time required to perform the procedures. This proof-of-concept study successfully demonstrated the feasibility of using AR to learn and/or perform various craniofacial and ANBs using commercially available technology.