iSurgARy: A mobile augmented reality solution for ventriculostomy in resource-limited settings

TL;DR

The paper tackles high ventriculostomy misplacement rates in emergency and resource-limited settings by introducing iSurgARy, a stand-alone mobile augmented reality system that uses LiDAR-based landmark registration on iOS devices. The approach eliminates external trackers by employing markerless registration and AR visualization to guide external ventricular drain placement, evaluated through a two-phase user study with novice and expert participants. Results show an average usability score around 81% and an RMSE of approximately $2.54\pm0.46\mathrm{mm}$, with a moderate NASA TLX workload, indicating practical usability and accuracy for LMIC contexts. The work highlights affordability, portability, and iterative, user-centered design as key advantages, while outlining future work to densify registration, remove QR tracking, and compare against head-mounted displays for further improvements and broader clinical adoption.

Abstract

Global disparities in neurosurgical care necessitate innovations addressing affordability and accuracy, particularly for critical procedures like ventriculostomy. This intervention, vital for managing life-threatening intracranial pressure increases, is associated with catheter misplacement rates exceeding 30% when using a freehand technique. Such misplacements hold severe consequences including haemorrhage, infection, prolonged hospital stays, and even morbidity and mortality. To address this issue, we present a novel, stand-alone mobile-based augmented reality system (iSurgARy) aimed at significantly improving ventriculostomy accuracy, particularly in resource-limited settings such as those in low- and middle-income countries. iSurgARy uses landmark based registration by taking advantage of Light Detection and Ranging (LiDaR) to allow for accurate surgical guidance. To evaluate iSurgARy, we conducted a two-phase user study. Initially, we assessed usability and learnability with novice participants using the System Usability Scale (SUS), incorporating their feedback to refine the application. In the second phase, we engaged human-computer interaction (HCI) and clinical domain experts to evaluate our application, measuring Root Mean Square Error (RMSE), System Usability Scale (SUS) and NASA Task Load Index (TLX) metrics to assess accuracy usability, and cognitive workload, respectively

Figures (5)

• Figure 1: iSurgARy general workflow. (From left to right):(1) The 'acquire' button sets a reference landmark and displays a red sphere to visualize its placement in AR. Above, we display all landmarks from a head top point of view (2) The system displays the 3D model of the ventricles in AR with the registration's RMSE. The process of selecting landmarks more accurately can be repeated until the user is satisfied with the RMSE. (3) The entry point placement feature enables the user to choose the catheter entry point on the surface of the head. We display the top view of Kocher's point, a common entry point for ventriculostomy. (4) The catheter tracking feature tracks a QR code image and renders the tip of the catheter in AR. The insertion of the catheter through the entry point from a head top point of view is shown.
• Figure 2: Left: Neurosurgeon performing registration by selecting the left tragus landmark. Right: Visualization of internal ventricular structure in AR and simulation of catheter insertion.
• Figure 3: Participant uses the aim cursor positioned at the center of the screen to select landmarks.
• Figure 4: NASA TLX Scores for each dimension of workload.
• Figure 5: After feedback from clinicians we began using a mobile phone holder to improve ergonomic issues.