Veronica Ruozzi

HC
3papers
Novelty47%
AI Score41

3 Papers

14.0HCApr 24
Catheter Monitoring in Intelligent Endovascular Navigation Systems: Interactive Simulations and Mixed Reality for Enhanced Navigational Awareness

Veronica Ruozzi, Giovanni Battista Regazzo, Maria Chiara Palumbo et al.

Purpose: Developing and testing a framework that integrates real-time catheter shape reconstruction, interactive simulations, and mixed reality visualization to enable accurate monitoring of catheter-vessel interactions during endovascular navigation. Methods: A finite element model (FEM) of the venous pathway from the right femoral vein to the inferior vena cava was generated from computed tomography data and implemented into an interactive simulation. Catheter motion was imposed as boundary condition, and catheter-vessel contact was modeled with a Lagrange multiplier formulation to compute vessel deformation. The framework was tested in-vitro using a sensorized catheter with Fiber Bragg Grating and electromagnetic sensors as it was advanced through a silicone replica of the vascular anatomy. Real-time sensor read-outs fed the simulation, and the updated catheter and vessel geometries were streamed to Hololens 2. The performance and accuracy of FEM-computed vessel wall displacement were validated against experimental ground-truth obtained via stereo frames triangulation. Results: The simulated time exceeded the real temporal extent by 12% during initial navigation and by 45% when the catheter reached the most tortuous portion. Hololens 2 rendering remained stable at 35-40 frames per second. The median relative displacement error between FEM-computed and ground-truth vessel wall displacements remained below 1 mm and 2.33 mm for these two phases, respectively. Conclusion: The study demonstrates the feasibility of integrating interactive biomechanical simulation with real-time sensor data to enable continuous monitoring of catheter-vessel interactions, with mixed reality visualization serving as a user interface to support operator decision-making.

64.4HCApr 8
Physics-driven Sonification for Improving Multisensory Needle Guidance in Percutaneous Epicardial Access

Veronica Ruozzi, Sasan Matinfar, Pasquale Vergara et al.

Percutaneous epicardial access (PEA), performed on a beating heart under fluoroscopy, enables arrhythmia treatment. However, advancing a needle toward the thin and moving pericardium remains highly challenging and risky. To address this problem, we present a physics-driven sonification method for Extended Reality (XR)-based multisensory navigation to enhance user perception during the critical needle landing phase in PEA. Dynamic cardiac anatomy from 4D CTA was reconstructed and registered to a real-world coordinate system. Real-time needle tracking provided the position of the needle tip relative to moving cardiac structures and drove an audio-visual feedback module. The visual display presented navigational cues and dynamic anatomy, while the auditory display encoded physiological cardiac states using a multilayer physical membrane model. A phantom study was conducted with twelve cardiologists performing needle insertions under visual-only and multisensory feedback. The multisensory method significantly improved navigation safety ($χ^2 = 11.30$, $p < 0.01$), reducing myocardial contact (3.64% vs. 7.27%) and increasing correct access (90.91% vs. 52.73%). Needle placement accuracy improved, with closer membrane proximity (Cliff delta = 0.19) and reduced variability ($p < 0.05$). Execution time was comparable, while time-accuracy correlations differed significantly between modalities ($p < 0.01$). NASA-TLX indicated lower cognitive load with multisensory guidance ($p < 0.01$). These results demonstrate the feasibility of physics-driven sonification for improving spatiotemporal awareness and supporting user-centered surgical navigation.

26.9SDMay 14
Physics-Based iOCT Sonification for Real-time Interaction Awareness in Subretinal Injection

Luis D. Reyes Vargas, Veronica Ruozzi, Andrea K. M. Ross et al.

Subretinal injection is a delicate vitreoretinal procedure requiring precise needle placement within the subretinal space while avoiding perforation of the retinal pigment epithelium (RPE), a layer directly beneath the target with extremely limited regenerative capacity. To enhance depth perception during cannula advancement, intraoperative optical coherence tomography (iOCT) offers high-resolution cross-sectional visualization of needle-tissue interaction; however, interpreting these images requires sustained visual attention alongside the en face microscope view, thereby increasing cognitive load during critical phases and placing additional demands on the surgeon's proprioceptive control. In this paper, we propose a structured, real-time sonification framework designed for extensible mapping of iOCT-derived anatomical features into perceptual auditory feedback. The method employs a physics-inspired acoustic model driven by segmented retinal layers from a stream of iOCT B-scans, with needle motion and injection-induced retinal layer displacements serving as excitation inputs to the sound model, enabling perception of tool position and retinal deformation. In a controlled user study (n=34), the proposed sonification achieved high retinal layer identification accuracy and robust detection of retinal deformation-related events, significantly outperforming a state-of-the-art baseline in overall event identification (83.4% vs. 60.6%, p < 0.001), with gains driven primarily by enhanced detection of injection-induced retinal deformation. Evaluation by experts (n=4) confirmed the clinical relevance and potential intraoperative applicability of the method. These results establish structured iOCT sonification as a viable complementary modality for real-time surgical guidance in subretinal injection.