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Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function.

Bishop MJ, Plank G, Burton RA, Schneider JE, Gavaghan DJ, Grau V, Kohl P - Am. J. Physiol. Heart Circ. Physiol. (2009)

Bottom Line: Simulation results were compared with those from a simplified model built from the same images but excluding finer anatomical features (vessels/endocardial structures).Postshock, these differences resulted in the genesis of new excitation wavefronts that were not observed in more simplified models.In conclusion, structurally simplified models are well suited for a large range of cardiac modeling applications.

View Article: PubMed Central - PubMed

Affiliation: University of Oxford Computing Laboratory, Parks Road, Oxford OX1 3QD, UK. martin.bishop@comlab.ox.ac.uk

ABSTRACT
Recent advances in magnetic resonance (MR) imaging technology have unveiled a wealth of information regarding cardiac histoanatomical complexity. However, methods to faithfully translate this level of fine-scale structural detail into computational whole ventricular models are still in their infancy, and, thus, the relevance of this additional complexity for simulations of cardiac function has yet to be elucidated. Here, we describe the development of a highly detailed finite-element computational model (resolution: approximately 125 microm) of rabbit ventricles constructed from high-resolution MR data (raw data resolution: 43 x 43 x 36 microm), including the processes of segmentation (using a combination of level-set approaches), identification of relevant anatomical features, mesh generation, and myocyte orientation representation (using a rule-based approach). Full access is provided to the completed model and MR data. Simulation results were compared with those from a simplified model built from the same images but excluding finer anatomical features (vessels/endocardial structures). Initial simulations showed that the presence of trabeculations can provide shortcut paths for excitation, causing regional differences in activation after pacing between models. Endocardial structures gave rise to small-scale virtual electrodes upon the application of external field stimulation, which appeared to protect parts of the endocardium in the complex model from strong polarizations, whereas intramural virtual electrodes caused by blood vessels and extracellular cleft spaces appeared to reduce polarization of the epicardium. Postshock, these differences resulted in the genesis of new excitation wavefronts that were not observed in more simplified models. Furthermore, global differences in the stimulus recovery rates of apex/base regions were observed, causing differences in the ensuing arrhythmogenic episodes. In conclusion, structurally simplified models are well suited for a large range of cardiac modeling applications. However, important differences are seen when behavior at microscales is relevant, particularly when examining the effects of external electrical stimulation on tissue electrophysiology and arrhythmia induction. This highlights the utility of histoanatomically detailed models for investigations of cardiac function, in particular for future patient-specific modeling.

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Identification of discrete surfaces. A: whole cardiac mesh [including atrial tissue] produced from Tetgen showing the tagged tetrahedral elements: myocardium (green), LV/right atrial (RA) cavities (red), and RV/RA cavities (blue). B: schematic diagram showing the identification of different surfaces based on the tags of bordering elements. The example shown is of an LV endocardial face triangle. C: visualization of the tagged surface nodes in the final ventricular finite-element mesh, representing the epicardium (red), LV endocardium (white), and RV endocardium (yellow).
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Figure 9: Identification of discrete surfaces. A: whole cardiac mesh [including atrial tissue] produced from Tetgen showing the tagged tetrahedral elements: myocardium (green), LV/right atrial (RA) cavities (red), and RV/RA cavities (blue). B: schematic diagram showing the identification of different surfaces based on the tags of bordering elements. The example shown is of an LV endocardial face triangle. C: visualization of the tagged surface nodes in the final ventricular finite-element mesh, representing the epicardium (red), LV endocardium (white), and RV endocardium (yellow).

Mentions: Meshing of the resulting segmented dataset produced elements with three separate numerical tags representing the myocardial tissue volume, the LV cavity, and the RV cavity, as shown in Fig. 9A. Note that in this case the ventricular cavities were directly connected to the atrial cavities as well. Examination of the numerical tags of each pair of elements bordering each bounding triangle face allowed discrimination between the three individual surfaces to be made. For example, a triangle that is part of the LV (or RV) endocardium also forms part of two tetrahedral elements: one in the myocardium (green) and one in the LV cavity (red) [or RV cavity (blue)]. A triangle that is part of the epicardium only forms part of one tetrahedral element. A schematic diagram demonstrating this identification process is shown in Fig. 9B.


Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function.

Bishop MJ, Plank G, Burton RA, Schneider JE, Gavaghan DJ, Grau V, Kohl P - Am. J. Physiol. Heart Circ. Physiol. (2009)

Identification of discrete surfaces. A: whole cardiac mesh [including atrial tissue] produced from Tetgen showing the tagged tetrahedral elements: myocardium (green), LV/right atrial (RA) cavities (red), and RV/RA cavities (blue). B: schematic diagram showing the identification of different surfaces based on the tags of bordering elements. The example shown is of an LV endocardial face triangle. C: visualization of the tagged surface nodes in the final ventricular finite-element mesh, representing the epicardium (red), LV endocardium (white), and RV endocardium (yellow).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2822578&req=5

Figure 9: Identification of discrete surfaces. A: whole cardiac mesh [including atrial tissue] produced from Tetgen showing the tagged tetrahedral elements: myocardium (green), LV/right atrial (RA) cavities (red), and RV/RA cavities (blue). B: schematic diagram showing the identification of different surfaces based on the tags of bordering elements. The example shown is of an LV endocardial face triangle. C: visualization of the tagged surface nodes in the final ventricular finite-element mesh, representing the epicardium (red), LV endocardium (white), and RV endocardium (yellow).
Mentions: Meshing of the resulting segmented dataset produced elements with three separate numerical tags representing the myocardial tissue volume, the LV cavity, and the RV cavity, as shown in Fig. 9A. Note that in this case the ventricular cavities were directly connected to the atrial cavities as well. Examination of the numerical tags of each pair of elements bordering each bounding triangle face allowed discrimination between the three individual surfaces to be made. For example, a triangle that is part of the LV (or RV) endocardium also forms part of two tetrahedral elements: one in the myocardium (green) and one in the LV cavity (red) [or RV cavity (blue)]. A triangle that is part of the epicardium only forms part of one tetrahedral element. A schematic diagram demonstrating this identification process is shown in Fig. 9B.

Bottom Line: Simulation results were compared with those from a simplified model built from the same images but excluding finer anatomical features (vessels/endocardial structures).Postshock, these differences resulted in the genesis of new excitation wavefronts that were not observed in more simplified models.In conclusion, structurally simplified models are well suited for a large range of cardiac modeling applications.

View Article: PubMed Central - PubMed

Affiliation: University of Oxford Computing Laboratory, Parks Road, Oxford OX1 3QD, UK. martin.bishop@comlab.ox.ac.uk

ABSTRACT
Recent advances in magnetic resonance (MR) imaging technology have unveiled a wealth of information regarding cardiac histoanatomical complexity. However, methods to faithfully translate this level of fine-scale structural detail into computational whole ventricular models are still in their infancy, and, thus, the relevance of this additional complexity for simulations of cardiac function has yet to be elucidated. Here, we describe the development of a highly detailed finite-element computational model (resolution: approximately 125 microm) of rabbit ventricles constructed from high-resolution MR data (raw data resolution: 43 x 43 x 36 microm), including the processes of segmentation (using a combination of level-set approaches), identification of relevant anatomical features, mesh generation, and myocyte orientation representation (using a rule-based approach). Full access is provided to the completed model and MR data. Simulation results were compared with those from a simplified model built from the same images but excluding finer anatomical features (vessels/endocardial structures). Initial simulations showed that the presence of trabeculations can provide shortcut paths for excitation, causing regional differences in activation after pacing between models. Endocardial structures gave rise to small-scale virtual electrodes upon the application of external field stimulation, which appeared to protect parts of the endocardium in the complex model from strong polarizations, whereas intramural virtual electrodes caused by blood vessels and extracellular cleft spaces appeared to reduce polarization of the epicardium. Postshock, these differences resulted in the genesis of new excitation wavefronts that were not observed in more simplified models. Furthermore, global differences in the stimulus recovery rates of apex/base regions were observed, causing differences in the ensuing arrhythmogenic episodes. In conclusion, structurally simplified models are well suited for a large range of cardiac modeling applications. However, important differences are seen when behavior at microscales is relevant, particularly when examining the effects of external electrical stimulation on tissue electrophysiology and arrhythmia induction. This highlights the utility of histoanatomically detailed models for investigations of cardiac function, in particular for future patient-specific modeling.

Show MeSH
Related in: MedlinePlus