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The Role of Immersion for Improving Extended Reality Analysis of Personalized Flow Simulations

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Abstract

Purpose

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.

Methods

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.

Results

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.

Conclusion

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.

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Conflict of interest

The authors have no conflicts of interests or competing interests to declare.

Funding

This work was supported by the NSF under grant 1943036 (A.R, H.S) and the American Heart Association Predoctoral Fellowship 20PRE35211158 (M.V.). This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. Computing support for this work came from the Lawrence Livermore National Laboratory (LLNL) Institutional Computing Grand Challenge program.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Duke University, 101 Science Drive, Campus Box 90281, Durham, NC, 27708, USA

    Harvey Shi, Madhurima Vardhan & Amanda Randles

  2. Department of Computer Science, Duke University, 308 Research Drive, Durham, NC, 27708, USA

    Amanda Randles

  3. Medical Scientist Training Program, Duke University, 8 Searle Center Drive Suite 4010, Durham, NC, 27710, USA

    Harvey Shi

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  1. Harvey Shi
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Correspondence to Amanda Randles.

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Associate Editor Zhenglun Alan Wei oversaw the review of this article.

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Shi, H., Vardhan, M. & Randles, A. The Role of Immersion for Improving Extended Reality Analysis of Personalized Flow Simulations. Cardiovasc Eng Tech 14, 194–203 (2023). https://doi.org/10.1007/s13239-022-00646-y

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