Personalized computational modeling of left atrial geometry and transmural myofiber architecture

Fastl, Thomas; Tobon-Gómez, Catalina; Crozier, Andrew; Whitaker, John; Rajani, Ronak; McCarthy, Karen; Sánchez‐Quintana, Damián; Ho, Siew Yen; O’Neill, Mark; Plank, Gernot; Bishop, Martin J.; Niederer, Steven

doi:10.1016/j.media.2018.04.001

Cited by 56 publications

(87 citation statements)

References 57 publications

(111 reference statements)

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“…Our results from Protocol 1 suggest that variation in myocyte orientations had a minimal influence on excitation-propagation at normal pacing rates, in agreement with previous human atrial simulations ( 39 ). The maximal mean absolute difference in local activation times between myocyte orientation scenarios was 2.68 ms at a pacing rate of 5 Hz but could be as low as 0.85 ms ( Table 2 ).…”

Section: Discussionsupporting

confidence: 91%

Investigation of the Role of Myocyte Orientations in Cardiac Arrhythmia Using Image-Based Models

Whittaker

Benson

Teh

et al. 2019

Biophysical Journal

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Cardiac electrical excitation-propagation is influenced by myocyte orientations (cellular organization). Quantitatively understanding this relationship presents a significant research challenge, especially during arrhythmias in which excitation patterns become complex. Tissue-scale simulations of cardiac electrophysiology, incorporating both dynamic action potential behavior and image-based myocardial architecture, provide an approach to investigate three-dimensional (3D) propagation of excitation waves in the heart. In this study, we aimed to assess the importance of natural variation in myocyte orientations on cardiac arrhythmogenesis using 3D tissue electrophysiology simulations. Three anatomical models (i.e., describing myocyte orientations) of healthy rat ventricles—obtained using diffusion tensor imaging at 100 μ m resolution—were registered to a single biventricular geometry (i.e., a single cardiac shape), in which the myocyte orientations could be represented by each of the diffusion tensor imaging data sets or by an idealized rule-based description. The Fenton-Karma cellular excitation model was modified to reproduce rat ventricular action potential duration restitution to create reaction-diffusion cardiac electrophysiology models. Over 250 3D simulations were performed to investigate the effects of myocyte orientations on the following: 1) ventricular activation, 2) location-dependent arrhythmia induction via rapid pacing, and 3) dynamics of re-entry averaged over multiple episodes. It was shown that 1) myocyte orientation differences manifested themselves in local activation times, but the influence on total activation time was small; 2) differences in myocyte orientations could critically affect the inducibility and persistence of arrhythmias for specific stimulus-location/cycle-length combinations; and 3) myocyte orientations alone could be an important determinant of scroll wave break, although no significant differences were observed in averaged arrhythmia dynamics between the four myocyte orientation scenarios considered. Our results show that myocyte orientations are an important determinant of arrhythmia inducibility, persistence, and scroll wave break. These findings suggest that where specificity is desired (for example, when predicting location-dependent, patient-specific arrhythmia inducibility), subject-specific myocyte orientations may be important.

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Section: Discussionsupporting

confidence: 91%

Investigation of the Role of Myocyte Orientations in Cardiac Arrhythmia Using Image-Based Models

Whittaker

Benson

Teh

et al. 2019

Biophysical Journal

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“…Atrial fibers are more challenging to embed in three-dimensional geometries compared to ventricular fibres, due to complex atrial anatomy and scarcity of data about fibre orientation in atrial myocardium. It is however possible for the user to define atrial fibres using a rule-based method [103,104] or by mapping a pre-existing fibre field using the universal atrial coordinated (UACs) [105][106][107].…”

Section: Limitationsmentioning

confidence: 99%

A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations

et al. 2020

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Computational models of the heart are increasingly being used in the development of devices, patient diagnosis and therapy guidance. While software techniques have been developed for simulating single hearts, there remain significant challenges in simulating cohorts of virtual hearts from multiple patients. To facilitate the development of new simulation and model analysis techniques by groups without direct access to medical data, image analysis techniques and meshing tools, we have created the first publicly available virtual cohort of twenty-four four-chamber hearts. Our cohort was built from heart failure patients, age 67±14 years. We segmented four-chamber heart geometries from end-diastolic (ED) CT images and generated linear tetrahedral meshes with an average edge length of 1.1 ±0.2mm. Ventricular fibres were added in the ventricles with a rule-based method with an orientation of-60˚and 80˚at the epicardium and endocardium, respectively. We additionally refined the meshes to an average edge length of 0.39±0.10mm to show that all given meshes can be resampled to achieve an arbitrary desired resolution. We ran simulations for ventricular electrical activation and free mechanical contraction on all 1.1mm-resolution meshes to ensure that our meshes are suitable for electro-mechanical simulations. Simulations for electrical activation resulted in a total activation time of 149±16ms. Free mechanical contractions gave an average left ventricular (LV) and right ventricular (RV) ejection fraction (EF) of 35±1% and 30±2%, respectively, and a LV and RV stroke volume (SV) of 95±28mL and 65±11mL, respectively. By making the cohort publicly available, we hope to facilitate large cohort computational studies and to promote the development of cardiac computational electro-mechanics for clinical applications.

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“…However, fibre orientation was not incorporated in this study due to the absence of patience-specific data in this regard. Future studies will aim to incorporate information about fibre orientation into patient-specific atrial models based on recently proposed rule-based approaches [52]. The modelling approach presented in the current study is entirely based on patient imaging-derived data available in the clinic.…”

Section: Limitationsmentioning

confidence: 99%

Identifying locations of re-entrant drivers from patient-specific distribution of fibrosis in the left atrium

et al. 2020

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Clinical evidence suggests a link between fibrosis in the left atrium (LA) and atrial fibrillation (AF), the most common sustained arrhythmia. Image-derived fibrosis is increasingly used for patient stratification and therapy guidance. However, locations of re-entrant drivers (RDs) sustaining AF are unknown and therapy success rates remain suboptimal. This study used image-derived LA models to explore the dynamics of RD stabilization in fibrotic regions and generate maps of RD locations. LA models with patient-specific geometry and fibrosis distribution were derived from late gadolinium enhanced magnetic resonance imaging of 6 AF patients. In each model, RDs were initiated at multiple locations, and their trajectories were tracked and overlaid on the LA fibrosis distributions to identify the most likely regions where the RDs stabilized. The simulations showed that the RD dynamics were strongly influenced by the amount and spatial distribution of fibrosis. In patients with fibrosis burden greater than 25%, RDs anchored to specific locations near large fibrotic patches. In patients with fibrosis burden below 25%, RDs either moved near small fibrotic patches or anchored to anatomical features. The patient-specific maps of RD locations showed that areas that harboured the RDs were much smaller than the entire fibrotic areas, indicating potential targets for ablation therapy. Ablating the predicted locations and connecting them to the existing pulmonary vein ablation lesions was the most effective in-silico ablation strategy.

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Personalized computational modeling of left atrial geometry and transmural myofiber architecture

Cited by 56 publications

References 57 publications

Investigation of the Role of Myocyte Orientations in Cardiac Arrhythmia Using Image-Based Models

Investigation of the Role of Myocyte Orientations in Cardiac Arrhythmia Using Image-Based Models

A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations

Identifying locations of re-entrant drivers from patient-specific distribution of fibrosis in the left atrium

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