Semi-Automated Patient Specific Hexahedral Mesh Generation of Articular Cartilage

Articular cartilage is a critical component in the movement of one bone against another. It possesses unique chemical properties allowing it to serve as a bearing surface, capable of transferring loads from one bone to another while simultaneously allowing the load bearing surfaces to articulate with low friction. Patient-specific finite element (FE) models incorporating articular cartilage provide insight into articular joint mechanics [1, 2]. To date, the methods/tools available to create accurate FE mesh definitions of the articular cartilage are limited. Semi-automated morphing methods have been developed, but many intermediate steps have to be performed to get the final cartilage mesh definition [3]. Commercially available software [4] is capable of generating tetrahedral/shell/pyramid element based meshes of the cartilage from the underlying bony surface, but hexahedral meshes are preferred over tetrahedral meshes [5]. IA-FEMesh currently provides the ability to project a pre-defined set of elements a uniform distance [6]. This technique has been adopted in several models [1, 2]. Cartilage does not necessarily exist as such; rather the thickness of the cartilage is non-uniform and varies over the surface. Consequently an accurate representation of the articular cartilage is crucial for an accurate contact FE analysis. The goal of this study was to develop an algorithm that will aid in the generation of anatomically accurate cartilage FE mesh definitions in a reliable manner based on patient-specific image data.

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Accuracy of Cartilage Geometry Reconstruction From Volumetric CT Data: A Phantom Study

ASME 2007 Summer Bioengineering Conference ◽

10.1115/sbc2007-174936 ◽

2007 ◽

Author(s):

Andrew E. Anderson ◽

Benjamin J. Ellis ◽

Christopher L. Peters ◽

Jeffrey A. Weiss

Keyword(s):

Articular Cartilage ◽

Contrast Agent ◽

Computational Models ◽

Image Data ◽

Cartilage Thickness ◽

Patient Specific ◽

Joint Spacing ◽

Ct Arthrography ◽

Diarthrodial Joints ◽

Joint Contact

Segmentation of medical image data is often used for the construction of computational models to study the mechanics of diarthrodial joints such as the hip and knee. The analyst must demonstrate that the reconstructed geometry is an accurate representation of the true continuum to ensure model validity. This becomes especially important for computational modeling of joint contact, which requires accurate reconstruction of articular cartilage. Although volumetric computed tomography (CT) is often used to image diarthrodial joints, the lower bounds for detecting articular cartilage thickness and the influence of imaging parameters on the ability to image cartilage have not been reported. The use of contrast agent (CT arthrography) is necessary to visualize the surface of articular cartilage in live patients. Thus, it is of primary interest to quantify the accuracy of CT arthrography to demonstrate the feasibility of patient-specific modeling. The objectives of this study were to assess the accuracy and detection limits of CT for measuring simulated cartilage thickness using a phantom and to quantify changes in accuracy due to alterations in contrast agent concentration, imaging plane direction, spatial resolution and joint spacing.

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Automated hexahedral mesh generation from biomedical image data: applications in limb prosthetics

IEEE Transactions on Rehabilitation Engineering ◽

10.1109/86.506406 ◽

1996 ◽

Vol 4 (2) ◽

pp. 91-102 ◽

Cited By ~ 22

Author(s):

S.G. Zachariah ◽

J.E. Sanders ◽

G.M. Turkiyyah

Keyword(s):

Mesh Generation ◽

Image Data ◽

Hexahedral Mesh ◽

Biomedical Image ◽

Hexahedral Mesh Generation

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Automatic Regular Hexahedral Mesh Generation by Regular Volume Decomposition

Volume 5: 17th Computers in Engineering Conference ◽

10.1115/detc97/cie-4497 ◽

1997 ◽

Author(s):

Bih-Yaw Shih ◽

Hiroshi Sakurai

Keyword(s):

Mesh Generation ◽

Complex Shape ◽

Solid Model ◽

Hexahedral Mesh ◽

Solid Models ◽

Hexahedral Mesh Generation ◽

Volume Decomposition ◽

Hexahedral Meshes ◽

The Way

Abstract A method has been developed to generate regular hexahedral meshes automatically from arbitrary solid models by volume decomposition. This method first decomposes a solid model having a complex shape into volumes having simple shapes. Then, shape-specific meshing methods like mapping are applied to generate regular hexahedral meshes from these volumes. Finally, all regular hexahedral meshes of these volumes are combined into a regular hexahedral mesh of the original solid model. Thus the method generates regular hexahedral meshes automatically in a way similar to the way a human does interactively. This is in contrast to the previous methods of automatic hexahedral mesh generation, which try to generate hexahedral meshes from solid models directly.

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Complex wall modeling for hemodynamic simulations of intracranial aneurysms based on histologic images

International Journal of Computer Assisted Radiology and Surgery ◽

10.1007/s11548-021-02334-z ◽

2021 ◽

Vol 16 (4) ◽

pp. 597-607

Author(s):

Annika Niemann ◽

Samuel Voß ◽

Riikka Tulamo ◽

Simon Weigand ◽

Bernhard Preim ◽

...

Keyword(s):

Wall Thickness ◽

Vessel Wall ◽

Intracranial Aneurysms ◽

Geometric Model ◽

Image Data ◽

Outer Wall ◽

3D Models ◽

Patient Specific ◽

Intracranial Vessel ◽

Hemodynamic Simulations

Abstract Purpose For the evaluation and rupture risk assessment of intracranial aneurysms, clinical, morphological and hemodynamic parameters are analyzed. The reliability of intracranial hemodynamic simulations strongly depends on the underlying models. Due to the missing information about the intracranial vessel wall, the patient-specific wall thickness is often neglected as well as the specific physiological and pathological properties of the vessel wall. Methods In this work, we present a model for structural simulations with patient-specific wall thickness including different tissue types based on postmortem histologic image data. Images of histologic 2D slices from intracranial aneurysms were manually segmented in nine tissue classes. After virtual inflation, they were combined into 3D models. This approach yields multiple 3D models of the inner and outer wall and different tissue parts as a prerequisite for subsequent simulations. Result We presented a pipeline to generate 3D models of aneurysms with respect to the different tissue textures occurring in the wall. First experiments show that including the variance of the tissue in the structural simulation affect the simulation result. Especially at the interfaces between neighboring tissue classes, the larger influence of stiffer components on the stability equilibrium became obvious. Conclusion The presented approach enables the creation of a geometric model with differentiated wall tissue. This information can be used for different applications, like hemodynamic simulations, to increase the modeling accuracy.

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Towards Patient-Specific Computational Modelling of Articular Cartilage on the Basis of Advanced Multiparametric MRI Techniques

Scientific Reports ◽

10.1038/s41598-019-43389-y ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 5

Author(s):

Kevin Linka ◽

Amelie Schäfer ◽

Markus Hillgärtner ◽

Mikhail Itskov ◽

Matthias Knobe ◽

...

Keyword(s):

Articular Cartilage ◽

Computational Modelling ◽

Multiparametric Mri ◽

Patient Specific

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4D Mitral Valve Motion Analysis Using Multi-Plane Cine Cardiac MRI Reconstructions for Functional Classification of Patients With Mitral Regurgitation

Volume 3: Biomedical and Biotechnology Engineering ◽

10.1115/imece2014-39910 ◽

2014 ◽

Author(s):

Abhiram Rao ◽

Prahlad G. Menon

Keyword(s):

Mitral Valve ◽

Mitral Regurgitation ◽

Motion Analysis ◽

Ventricular Remodeling ◽

Systolic Dysfunction ◽

Survival Rates ◽

Image Data ◽

Anatomical Reconstruction ◽

Patient Specific ◽

Operative Planning

Mitral regurgitation (MR) is a common consequence of ventricular remodeling in heart failure (HF) patients with systolic dysfunction and is associated with diminished survival rates. Characterization of patient-specific anatomy and function of the regurgitant mitral valve (MV) can enhance surgical decision making in terms of medical device choice and deployment strategy for minimally invasive endovascular approaches for MV repair. As a first step toward pre-operative planning for MV repair, we examine the feasibility of using cardiac magnetic resonance (CMR) images acquired in multiple orientations to resolve leaflet function and timing. In this study, MV motion of a HF patient with ischemic heart disease exhibiting both adverse ventricular remodeling and MR was compared pre-operatively against a normal control from the Sunnybrook cardiac database, starting with manually segmented 2D MV contours from cine CMR images acquired in multiple orientations. We find that MV motion analysis from CMR imaging is feasible and anatomical reconstruction using oriented segmentations from a combination of imaging slices acquired in multiple orientations can help overcome inherent limitations of CMR image data in terms of resolving small anatomical features, owing to finite slice-thicknesses and partial volume effects.

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