Visualization of Human Spine Biomechanics for Spinal Surgery

Pepe Eulzer, Sabine Bauer, Francis Kilian, Kai Lawonn

View presentation: 2020-10-30T14:30:00Z GMT-0600 Change your timezone on the schedule page
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We present a framework for the visual exploration of spine simulation data. We show the force distribution on spinal discs, enable assessments of imbalances, and reveal impact vectors that were inaccessible before. This is a novel direction in medical visualization and we hope that it might bridge the gap between biomechanical research and clinical application.
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Medical visualization, bioinformatics, coordinated views, focus and context, biomechanical simulation.


We propose a visualization application, designed for the exploration of human spine simulation data. Our goal is to support research in biomechanical spine simulation and advance efforts to implement simulation-backed analysis in surgical applications. Biomechanical simulation is a state-of-the-art technique for analyzing load distributions of spinal structures. Through the inclusion of patient-specific data, such simulations may facilitate personalized treatment and customized surgical interventions. Difficulties in spine modelling and simulation can be partly attributed to poor result representation, which may also be a hindrance when introducing such techniques into a clinical environment. Comparisons of measurements across multiple similar anatomical structures and the integration of temporal data make commonly available diagrams and charts insufficient for an intuitive and systematic display of results. Therefore, we facilitate methods such as multiple coordinated views, {\color{blue} abstraction} and focus and context to display simulation outcomes in a dedicated tool. By linking the result data with patient-specific anatomy, we make relevant parameters tangible for clinicians. Furthermore, we introduce new concepts to show the directions of impact force vectors, which were not accessible before. We integrated our toolset into a spine segmentation and simulation pipeline and evaluated our methods with both surgeons and biomechanical researchers. When comparing our methods against standard representations that are currently in use, we found increases in accuracy and speed in data exploration tasks. In a qualitative review, domain experts deemed the tool highly useful when dealing with simulation result data, which typically combines time-dependent patient movement and the resulting force distributions on spinal structures.