Amanda Randles

Immersive visual displays are becoming more common in the diagnostic imaging and pre-procedural planning of complex cardiology revascularization surgeries. One such procedure is coronary artery bypass grafting (CABG) surgery, which is a gold standard treat-ment for patients with advanced coronary heart disease. Treatment planning of the CABG surgery can be aided by extended reality (XR) displays as they are known for offering advantageous visual-ization of spatially heterogeneous and complex tasks. Despite the benefits of XR, it remains unknown whether clinicians will benefit from higher visual immersion offered by XR. In order to assess the impact of increased immersion as well as the latent factor of geometrical complexity, a quantitative user evaluation (n=14) was performed with clinicians of advanced cardiology training simulating CABG placement on sixteen 3D arterial tree models derived from 6 patients two levels of anatomic complexity. These arterial models were rendered on 3D/XR and 2D display modes with the same tactile interaction input device. The findings of this study reveal that compared to a monoscopic 2D display, the greater visual immersion of 3D/XR does not significantly alter clinician accuracy in the task of bypass graft placement. Latent factors such as arterial complexity and clinical experience both influence the accuracy of graft placement. In addition, an anatomically less complex model

The original version of this chapter was revised. The spelling of the last author’s name was corrected to Amanda Randles.

Three constitutive laws, that is the Skalak, neo-Hookean and Yeoh laws, commonly employed for describing the erythrocyte membrane mechanics are theoretically analyzed and numerically investigated to assess their accuracy for capturing erythrocyte deformation characteristics and morphology. Particular emphasis is given to the nonlinear deformation regime, where it is known that the discrepancies between constitutive laws are most prominent. Hence, the experiments of optical tweezers and micropipette aspiration are considered here, for which relationships between the individual shear elastic moduli of the constitutive laws can also be established through analysis of the tension-deformation relationship. All constitutive laws were found to adequately predict the axial and transverse deformations of a red blood cell subjected to stretching with optical tweezers for a constant shear elastic modulus value. As opposed to Skalak law, the neo-Hookean and Yeoh laws replicated the erythrocyte membrane folding, that has been experimentally observed, with the trade-off of sustaining significant area variations. For the micropipette aspiration, the suction pressure-aspiration length relationship could be excellently predicted for a fixed shear elastic modulus value only when Yeoh law was considered. Importantly, the neo-Hookean and Yeoh laws reproduced the membrane wrinkling at suction pressures close to those experimentally measured. None of the constitutive laws suffered from membrane area compressibility in the micropipette aspiration case.

The ability to track simulated cancer cells through the circulatory system, important for developing a mechanistic understanding of metastatic spread, pushes the limits of today's supercomputers by requiring the simulation of large fluid volumes at cellular-scale resolution. To overcome this challenge, we introduce a new adaptive physics refinement (APR) method that captures cellular-scale interaction across large domains and leverages a hybrid CPU-GPU approach to maximize performance. Through algorithmic advances that integrate multi-physics and multi-resolution models, we establish a finely resolved window with explicitly modeled cells coupled to a coarsely resolved bulk fluid domain. In this work we present multiple validations of the APR framework by comparing against fully resolved fluid-structure interaction methods and employ techniques, such as latency hiding and maximizing memory bandwidth, to effectively utilize heterogeneous node architectures. Collectively, these computational developments and performance optimizations provide a robust and scalable framework to enable system-level simulations of cancer cell transport.

<h4>Purpose</h4>Computational models of flow in patient-derived arterial geometries have become a key paradigm of biomedical research. These fluid models are often challenging to visualize due to high spatial heterogeneity and visual complexity. Virtual immersive environments can offer advantageous visualization of spatially heterogeneous and complex systems. However, as different VR devices offer varying levels of immersion, there remains a crucial lack of understanding regarding what level of immersion is best suited for interactions with patient-specific flow models.<h4>Methods</h4>We conducted a quantitative user evaluation with multiple VR devices testing an important use of hemodynamic simulations-analysis of surface parameters within complex patient-specific geometries. This task was compared for the semi-immersive zSpace 3D monitor and the fully immersive HTC Vive system.<h4>Results</h4>The semi-immersive device was more accurate than the fully immersive device. The two devices showed similar results for task duration and performance (accuracy/duration). The accuracy of the semi-immersive device was also higher for arterial geometries of greater complexity and branching.<h4>Conclusion</h4>This assessment demonstrates that the level of immersion plays a significant role in the accuracy of assessing arterial flow models. We found that the semi-immersive VR device was a generally optimal choice for arterial visualization.