Electrophysiology Model for a Human Heart with Ischemic Scar and Realistic Purkinje Network

Lassila, Toni; Lange, Matthias; Perez, Antonio R. Porras; Lekadir, Karim; Albí, Xènia; Piella, Gemma; Frangi, Alejandro F.

doi:10.1007/978-3-319-28712-6_10

Cited by 6 publications

(10 citation statements)

References 15 publications

(22 reference statements)

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“…In the past, different models for the PN have been suggested and reviewed by Ten Tusscher and Panfilov in 2008 . More recent work can be found in the literature . In such simulations, 2 main types of models have been used: the simpler eikonal model and the monodomain model.…”

Section: Introductionmentioning

confidence: 99%

“…For this model certain observations have been made in conjunction with the PN. Most importantly, it has been shown that coarse networks are not able to reproduce physiological activations . A further indication that the PN needs a certain density comes from a single PMJ might fail to conduct the AP from the PN to the MC.…”

Section: Introductionmentioning

confidence: 99%

“…12 More recent work can be found in the literature. 7,[13][14][15][16] In such simulations, 2 main types of models have been used: the simpler eikonal model and the monodomain model.…”

Section: Introductionmentioning

confidence: 99%

“…Most importantly, it has been shown that coarse networks are not able to reproduce physiological activations. 6,14,16,18 A further indication that the PN needs a certain density comes from a single PMJ might fail to conduct the AP from the PN to the MC. However, if a large enough density is given, other PMJs will take over.…”

Section: Introductionmentioning

confidence: 99%

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Improved hybrid/GPU algorithm for solving cardiac electrophysiology problems on Purkinje networks

Lange

Palamara

Lassila

et al. 2016

Numer Methods Biomed Eng

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SUMMARYCardiac Purkinje fibres provide an important pathway to the coordinated contraction of the heart. We present a numerical algorithm for the solution of electrophysiology problems across the Purkinje network that is efficient enough to be used in in-silico studies on realistic Purkinje networks with physiologically detailed models of ion exchange at the cell membrane. The algorithm is based on operator splitting and is provided with three different implementations: pure CPU, hybrid CPU/GPU, and pure GPU. Compared to our previous work, we modify the explicit gap junction term at network bifurcations in order to improve its mathematical consistency. Due to this improved consistency of the model, we are able to perform an empirical convergence study against analytical solutions. The study verified that all three implementations produce equivalent convergence rates, which shows that the algorithm produces equivalent result across different hardware platforms. Finally, we compare the efficiency of all three implementations on Purkinje networks of increasing spatial resolution using membrane models of increasing complexity. Both hybrid and pure-GPU implementations outperform the pure-CPU implementation, but their relative performance difference depends on the size of the Purkinje network and the complexity of the membrane model used.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…12 More recent work can be found in the literature. 7,[13][14][15][16] In such simulations, 2 main types of models have been used: the simpler eikonal model and the monodomain model.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Improved hybrid/GPU algorithm for solving cardiac electrophysiology problems on Purkinje networks

Lange

Palamara

Lassila

et al. 2016

Numer Methods Biomed Eng

View full text Add to dashboard Cite

show abstract

“…In addition to the features mentioned above, the flexibility of this "minimal model" is such that it can also be fitted to reproduce the reported AP shape changes in pathological conduction scenarios, such as ischemia [153]. It has also been used to fit experimental data of thermo-electrical coupling and bifurcation phenomena and to simulate tissue size effects [84,86].…”

Section: Electrophysiology Of the Heartmentioning

confidence: 99%