Visualization of Human Spine Biomechanics for Spinal Surgery

Quantifying the Impact of Spinal Fusion Systems by Multibody Simulation

The established surgical procedure of spinal fusion, in which two or more spinal vertebrae are permanently connected, is constantly increasing worldwide due to new developments in fusion procedures and surgical techniques, as well as improved implants, even though there is still no consensus on whether fusion leads to subsequent degeneration of adjacent spinal segments. We outline the potential biomechanical impacts of mono-segmental and multi-segmental fusion on the spinal structures, especially on the adjacent functional spinal units (FSU), using MultiBody Simulation (MBS). In addition, we investigated the influence of the implant size on the loading situation of the spinal structures by analyzing suitable human MBS models, focusing on a highly detailed spinal region. Our results showed no significant increase in the load on adjacent intervertebral discs (IVD) in the present specific model configurations due to mono-segmental and multi-segmental fusion. Instead, the load was redistributed to the disadvantage of the posterior facet joints in the lumbar spine's upper section. Analysis of the influence of different implant sizes on the spinal structures' load revealed that choosing an implant size that did not correspond to the original IVD space led to a massive increase in the IVD loads.Clinical relevance: gaining new insights to improve surgical outcomes to minimize the risk of adverse effects.

A Survey of Designs for Combined 2D+3D Visual Representations

We examine visual representations of data that make use of combinations of both 2D and 3D data mappings. Combining 2D and 3D representations is a common technique that allows viewers to understand multiple facets of the data with which they are interacting. While 3D representations focus on the spatial character of the data or the dedicated 3D data mapping, 2D representations often show abstract data properties and take advantage of the unique benefits of mapping to a plane. Many systems have used unique combinations of both types of data mappings effectively. Yet there are no systematic reviews of the methods in linking 2D and 3D representations. We systematically survey the relationships between 2D and 3D visual representations in major visualization publications-IEEE VIS, IEEE TVCG, and EuroVis-from 2012 to 2022. We closely examined 105 articles where 2D and 3D representations are connected visually, interactively, or through animation. These approaches are designed based on their visual environment, the relationships between their visual representations, and their possible layouts. Through our analysis, we introduce a design space as well as provide design guidelines for effectively linking 2D and 3D visual representations.

Intuitive assessment of modeled lumbar spinal motion by clustering and visualization of finite helical axes

A variety of medical imaging procedures, cadaver experiments, and computer models have been utilized to capture, depict, and understand the motion of the human lumbar spine. Particular interest lies in assessing the relative movement between two adjacent vertebrae, which can be represented by a temporal evolution of finite helical axes (FHA). Mathematically, this FHA evolution constitutes a seven-dimensional quantity: one dimension for the time, two for the (normalized) direction vector, another two for the (unique) position vector, as well as one for each the angle of rotation around and the amount of translation along the axis. Predominantly in the literature, however, movements are assumed to take place in certain physiological planes on which FHA are projected. The resulting three-dimensional quantity - the so-called centrode - is easily presentable but leaves out substantial pieces of available data. Here, we investigate and assess several possibilities to visualize subsets of FHA data of increasing dimensionality. Finally, we utilize an agglomerative hierarchical clustering algorithm and propose a novel visualization technique, namely the quiver principal axis plot (QPAP), to depict the entirety of information inherent to hundreds or thousands of FHA. The QPAP method is applied to flexion-extension, lateral bending, and axial rotation movements of a lumbar spine within both a reduced model as well as a complex upper body system.