Automated subject-specific, hexahedral mesh generation via image registration

Ji, Songbai; Ford, James; Greenwald, Richard M.; Beckwith, Jonathan G.; Paulsen, Keith D.; Flashman, Laura A.; McAllister, Thomas W.

doi:10.1016/j.finel.2011.05.007

Cited by 38 publications

(25 citation statements)

References 26 publications

(51 reference statements)

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“…However, the millimeter node-to-surface error was notably larger than that of our previous head model where sub-millimeter accuracy was obtained. 56 This was because the segmented brain surface was not directly used for block projection in this study but was parameterized to generate geometrical entities to aid the meshing instead.…”

Section: Journal Of Neurotraumamentioning

confidence: 99%

Group-Wise Evaluation and Comparison of White Matter Fiber Strain and Maximum Principal Strain in Sports-Related Concussion

Zhao

Ford

et al. 2015

Journal of Neurotrauma

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141

206

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Sports-related concussion is a major public health problem in the United States and yet its biomechanical mechanisms remain unclear. In vitro studies demonstrate axonal elongation as a potential injury mechanism; however, current response-based injury predictors (e.g., maximum principal strain, ε(ep)) typically do not incorporate axonal orientations. We investigated the significance of white matter (WM) fiber orientation in strain estimation and compared fiber strain (ε(n)) with ε(ep) for 11 athletes with a clinical diagnosis of concussion. Geometrically accurate subject-specific head models with high mesh quality were created based on the Dartmouth Head Injury Model (DHIM), which was successfully validated (performance categorized as "good" to "excellent"). For WM regions estimated to be exposed to high strains using a range of injury thresholds (0.09-0.28), substantial differences existed between ε(n) and ε(ep) in both distribution (Dice coefficient of 0.13-0.33) and extent (∼ 5-10-fold differences), especially at higher threshold levels and higher rotational acceleration magnitudes. For example, an average of 3.2% vs. 29.8% of WM was predicted above an optimal threshold of 0.18 established from an in vivo animal study using ε(n) and ε(ep), respectively, with an average Dice coefficient of 0.14. The distribution of WM regions with high ε(n) was consistent with typical heterogeneous patterns of WM disruptions in diffuse axonal injury, and the group-wise extent at the optimal threshold matched well with the percentage of WM voxels experiencing significant longitudinal changes of fractional anisotropy and mean diffusivity (3.2% and 3.44%, respectively) found from a separate independent study. These results suggest the significance of incorporating WM microstructural anisotropy in future brain injury studies.

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Section: Journal Of Neurotraumamentioning

confidence: 99%

Group-Wise Evaluation and Comparison of White Matter Fiber Strain and Maximum Principal Strain in Sports-Related Concussion

Zhao

Ford

et al. 2015

Journal of Neurotrauma

Self Cite

141

206

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“…Additionally, individualized pcBRA could also be established if so desired using subject-specific models that can be developed with existing techniques. 23,25 …”

Section: Discussionmentioning

confidence: 99%

A Pre-computed Brain Response Atlas for Instantaneous Strain Estimation in Contact Sports

Zhao

2014

Ann Biomed Eng

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Finite element models of the human head play an important role in investigating the mechanisms of traumatic brain injury, including sports concussion. A critical limitation, however, is that they incur a substantial computational cost to simulate even a single impact. Therefore, current simulation schemes significantly hamper brain injury studies based on model-estimated tissue-level responses. In this study, we investigate the feasibility of a pre-computed brain response atlas (pcBRA) to substantially increase the simulation efficiency in estimating brain strains using isolated rotational acceleration impulses parameterized with four independent variables (peak magnitude and duration, and rotational axis azimuth and elevation angles) with values determined from on-field measurements. Using randomly generated testing datasets, the partially established pcBRA achieved a 100% success rate in interpolation based on element-wise differences in accumulated peak strain (εp) according to a “double-10%” criterion or average regional εp in generic regions and the corpus callosum. A similar performance was maintained in extrapolation. The pcBRA performance was further successfully evaluated against responses directly simulating two independently measured typical real-world rotational profiles. The computational cost to estimate element-wise whole-brain or regional εp was 6 sec and <0.01 sec, respectively, vs. ~50 min directly simulating a 40 ms impulse. These findings suggest the pcBRA could substantially increase the throughput in impact simulation without significant loss of accuracy from the estimation itself and, thus, its potential to accelerate the exploration of the mechanisms of sports concussion in general. If successful, the pcBRA may also become a diagnostic adjunct in conjunction with sensors that measure head impact kinematics on the field to objectively monitor and identify tissue-level brain trauma in real-time for “return-to-play” decision-making on the sideline.

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“…While simulations with tetrahedral elements may lead to numerical issues, such as volumetric locking [1], hexahedral elements suffer less from volumetric locking and yield an equivalent or higher accuracy per degree of freedom. However, hexahedral meshes can hardly be adapted to complex surfaces [7]. Thus, it is advantageous to either extend the partial differential equation (PDE) outside the actual domain in order to use a domain-independent mesh, which is known as the Finite Cell Method [14], or to work with partially filled elements.…”

Section: Introductionmentioning

confidence: 99%

An Immersed Boundary Method for Detail-Preserving Soft Tissue Simulation from Medical Images

Paulus

Maier

Peterseim

et al. 2018

Computational Biomechanics for Medicine

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Simulating the deformation of the human anatomy is a central element of Medical Image Computing and Computer Assisted Interventions. Such simulations play a key role in non-rigid registration, augmented reality, and several other applications. Although the Finite Element Method is widely used as a numerical approach in this area, it is often hindered by the need for an optimal meshing of the domain of interest. The derivation of meshes from imaging modalities such as CT or MRI can be cumbersome and time-consuming. In this paper we use the Immersed Boundary Method (IBM) to bridge the gap between these imaging modalities and the fast simulation of soft tissue deformation on complex shapes represented by a surface mesh directly retrieved from binary images. A high resolution surface, that can be obtained from binary images using a marching cubes approach, is embedded into a hexahedral simulation grid. The details of the surface mesh are properly taken into account in the hexahedral mesh by adapting the Mirtich integration method. In addition to not requiring a dedicated meshing approach, our method results in higher accuracy for less degrees of freedom when compared to other element types.Examples on brain deformation demonstrate the potential of our method.

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Automated subject-specific, hexahedral mesh generation via image registration

Cited by 38 publications

References 26 publications

Group-Wise Evaluation and Comparison of White Matter Fiber Strain and Maximum Principal Strain in Sports-Related Concussion

Group-Wise Evaluation and Comparison of White Matter Fiber Strain and Maximum Principal Strain in Sports-Related Concussion

A Pre-computed Brain Response Atlas for Instantaneous Strain Estimation in Contact Sports

An Immersed Boundary Method for Detail-Preserving Soft Tissue Simulation from Medical Images

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