Cardiovascular and lung mesh generation based on centerlines

Marchandise, Émilie; Geuzaine, Christophe; Remacle, Jean‐François

doi:10.1002/cnm.2549

Cited by 22 publications

(24 citation statements)

References 32 publications

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“…More formally, it is expressed as: Labbé et al [36] showed that the proposed method converges and yields adapted meshes with low non-conformity coefficient values. Note that this coefficient is similar to the quality measure used by Marchandise et al [19].…”

Section: Adaptation Stepmentioning

confidence: 60%

Patient‐specific anisotropic model of human trunk based on MR data

Courchesne

Guibault

Parent

et al. 2015

Numer Methods Biomed Eng

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SUMMARYThere are many ways to generate geometrical models for numerical simulation and most of them start with a segmentation step to extract the boundaries of the regions of interest. This paper presents an algorithm to generate a patient specific 3D geometric model, based on a tetrahedral mesh, without an initial extraction of contours from the volumetric data. Using the information directly available in the data, such as grey levels, a metric is built to drive a mesh adaptation process. The metric is used to specify the size and orientation of the tetrahedral elements everywhere in the mesh. Our method, which produces anisotropic meshes, gives good results with synthetic and real MRI data. The resulting model quality has been evaluated qualitatively and quantitatively by comparing it with an analytical solution and with a segmentation made by an expert. Results show that our method gives, in 90% of the cases, as good or better meshes as a similar isotropic method, based on the accuracy of the volume reconstruction for a given mesh size. Moreover, a comparison of Hausdorff distances between adapted meshes of both methods and ground-truth volumes shows that our method decreases reconstruction errors faster.

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Section: Adaptation Stepmentioning

confidence: 60%

Patient‐specific anisotropic model of human trunk based on MR data

Courchesne

Guibault

Parent

et al. 2015

Numer Methods Biomed Eng

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“…This tool generates a script containing the geometric description (points, lines and planes, and directed line loops) of the segmentation. Subsequently, the script was meshed using GMSH 9. Conductivity for the homogeneous VCM (model 1) was specified at 0.2 Siemens per meter (S/m) 10.…”

Section: Methodsmentioning

confidence: 99%

Feasibility and Accuracy of Cardiac Magnetic Resonance Imaging–Based Whole‐Heart Inverse Potential Mapping of Sinus Rhythm and Idiopathic Ventricular Foci

Bhagirath

Graaf

Dongen

et al. 2015

JAHA

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BackgroundInverse potential mapping (IPM) noninvasively reconstructs cardiac surface potentials using body surface potentials. This requires a volume conductor model (VCM), usually constructed from computed tomography; however, computed tomography exposes the patient to harmful radiation and lacks information about tissue structure. Magnetic resonance imaging (MRI) is not associated with this limitation and might have advantages for mapping purposes. This feasibility study investigated a magnetic resonance imaging–based IPM approach. In addition, the impact of incorporating the lungs and their particular resistivity values was explored.Methods and ResultsThree volunteers and 8 patients with premature ventricular contractions scheduled for ablation underwent 65‐electrode body surface potential mapping. A VCM was created using magnetic resonance imaging. Cardiac surface potentials were estimated from body surface potentials and used to determine the origin of electrical activation. The IPM‐defined origin of sinus rhythm corresponded well with the anatomic position of the sinus node, as described in the literature. In patients, the IPM‐derived premature ventricular contraction focus was 3‐dimensionally located within 8.3±2.7 mm of the invasively determined focus using electroanatomic mapping. The impact of lungs on the IPM was investigated using homogeneous and inhomogeneous VCMs. The inhomogeneous VCM, incorporating lung‐specific conductivity, provided more accurate results compared with the homogeneous VCM (8.3±2.7 and 10.3±3.1 mm, respectively; P=0.043). The interobserver agreement was high for homogeneous (intraclass correlation coefficient 0.862, P=0.003) and inhomogeneous (intraclass correlation coefficient 0.812, P=0.004) VCMs.ConclusionMagnetic resonance imaging–based whole‐heart IPM enables accurate spatial localization of sinus rhythm and premature ventricular contractions comparable to electroanatomic mapping. An inhomogeneous VCM improved IPM accuracy.

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“…For instance, tubular structures appears in many industrial and medical applications. In references [81,82] two different strategies for this kind of geometries are presented.…”

Section: Other Methodsmentioning

confidence: 99%

Unstructured and Semi-Structured Hexahedral Mesh Generation Methods

Ramos¹,

Ruiz‐Gironés²,

Navarro³

2014

Comp. Tech. Rev.

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Discretization techniques such the finite element method, the finite volume method or the discontinuous Galerkin method are the most used simulation techniques in applied sciences and technology. These methods rely on a spatial discretization adapted to the geometry and to the prescribed distribution of element size. Several fast and robust algorithms have been developed to generate triangular and tetrahedral meshes. In these methods local connectivity modifications are a crucial step. Nevertheless, in hexahedral meshes the connectivity modifications propagate through the mesh. In this sense, hexahedral meshes are more constrained and therefore, more difficult to generate. However, in many applications such as boundary layers in computational fluid dynamics or composite material in structural analysis hexahedral meshes are preferred. In this work we present a survey of developed methods for generating structured and unstructured hexahedral meshes.

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Cardiovascular and lung mesh generation based on centerlines

Cited by 22 publications

References 32 publications

Patient‐specific anisotropic model of human trunk based on MR data

Patient‐specific anisotropic model of human trunk based on MR data

Feasibility and Accuracy of Cardiac Magnetic Resonance Imaging–Based Whole‐Heart Inverse Potential Mapping of Sinus Rhythm and Idiopathic Ventricular Foci

Unstructured and Semi-Structured Hexahedral Mesh Generation Methods

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