Cell to Whole Organ Global Sensitivity Analysis on a Four-chamber Heart Electromechanics Model Using Gaussian Processes Emulators - Training Datasets

Strocchi M, Longobardi S, Augustin CM, Gsell MAF, Petras A, Rinaldi CA, et al. (2023) Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators. PLoS Comput Biol 19(6): e1011257. https://doi.org/10.1371/journal.pcbi.1011257

This database contains all training datasets for the Gaussian processes emulators (GPEs) trained in the study entitled "Cell to Whole Organ Global Sensitivity Analysis on a Four-chamber Electromechanics Model Using Gaussian Processes Emulators", submitted to PLOS Computational Biology.

Paper , Training dataset (Zenodo) , Code

Whole Torso Computational Models

Qian S, Monaci S, Mendonca-Costa C, Campos F, Gemmell P, Zaidi HA, Rajani R, Whitaker J, Rinaldi CA, Bishop MJ. Additional coils mitigate elevated defibrillation threshold in right-sided implantable cardioverter defibrillator generator placement: a simulation study. Europace. 2023 Jun;25(6):euad146.

Whole torso computational models generated from high-resolution CT data.

Paper , Meshes (Zenodo)

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models

Roney, Caroline H., Iain Sim, Jin Yu, Marianne Beach, Arihant Mehta, Jose Alonso Solis-Lemus, Irum Kotadia et al. Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models. Circulation: Arrhythmia and Electrophysiology (2021): CIRCEP-121.

We include surface meshes in vtk format, consisting of the nodes, triangular elements, the atrial coordinate fields defined on the nodes, and the endocardial and epicardial fibre fields defined on the elements.

Paper , Meshes (Zenodo) , Data governance

Virtual cohort of 1000 synthetic heart meshes from adult human healthy population

Rodero C, Strocchi M, Marciniak M, Longobardi S, Whitaker J, O’Neill MD, Gillette K, Augustin C, Plank G, Vigmond EJ, Lamata P. Linking statistical shape models and simulated function in the healthy adult human heart. PLoS computational biology. 2021 Apr 15;17(4):e1008851.

Paper , Meshes (Zenodo)

Virtual cohort of extreme and average four-chamber heart meshes from statistical shape model

Rodero C, Strocchi M, Marciniak M, Longobardi S, Whitaker J, O’Neill MD, Gillette K, Augustin C, Plank G, Vigmond EJ, Lamata P. Linking statistical shape models and simulated function in the healthy adult human heart. PLoS computational biology. 2021 Apr 15;17(4):e1008851.

Paper , Meshes (Zenodo)

Virtual cohort of adult healthy four-chamber heart meshes from CT images

Rodero C, Strocchi M, Marciniak M, Longobardi S, Whitaker J, O’Neill MD, Gillette K, Augustin C, Plank G, Vigmond EJ, Lamata P. Linking statistical shape models and simulated function in the healthy adult human heart. PLoS computational biology. 2021 Apr 15;17(4):e1008851.

Paper , Meshes (Zenodo)

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

Strocchi M, Augustin CM, Gsell MAF, Karabelas E, Neic A, et al. (2020) A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations. PLOS ONE 15(6): e0235145

Paper , Meshes (Zenodo)

The Impact of Wall Thickness and Curvature on Wall Stress in Patient-Specific Electromechanical Models of the Left Atrium

Augustin CM, Fastl TE, Neic A, et al. The impact of wall thickness and curvature on wall stress in patient-specific electromechanical models of the left atrium. Biomech Model Mechanobiol. 2020;19(3):1015‐1034. doi:10.1007/s10237-019-01268-5

Paper , Meshes (Zenodo)

Constructing a Human Atrial Fibre Atlas

Roney, C.H., Bendikas, R., Pashakhanloo, F. et al. Constructing a Human Atrial Fibre Atlas. Ann Biomed Eng 49, 233–250 (2021). https://doi.org/10.1007/s10439-020-02525-w

Paper , Meshes (Zenodo)

A Virtual Cohort of Twenty-four Left-ventricular Models of Ischemic Cardiomyopathy Patients

Mendonca Costa, Caroline, Neic, Aurel Medical University of Graz, and Kerfoot, Eric King’s College London. A Virtual Cohort of Twenty-four Left-ventricular Models of Ischemic Cardiomyopathy Patients (2020)

KCL Library Archive

Personalized computational finite element models for left atrial electromechanics

Fastl, Thomas E, Tobon-Gomez, Catalina King's College London, Crozier, Andrew Medical University of Graz, and McCarthy, Karen P Royal Brompton Hospital. Personalized Computational Finite Element Models for Left Atrial Electromechanics (2018).

KCL Library Archive

A model of cardiac contraction based on novel measurements of tension development in human cardiomyocytes.

S Land, SJ Park-Holohan, NP Smith, CG Dos Remedios, JC Kentish, SA Niederer. JMCC, 2017

A model of human cardiac contraction intended for multi-scale modelling applications. Download includes relevant experimental data, and C++ code is available on request.

Pubmed , Matlab

Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour

Land S, Gurev V, Arens S, Augustin CM, Baron L, Blake R, Bradley C, Castro S, Crozier A, Favino M, Fastl TE. Verification of cardiac mechanics software: benchmark problems and solutions for testing active and passive material behaviour. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2015 Dec 8;471(2184):20150641.

To aid in the verification of current and future cardiac mechanics solvers, this study provides three benchmark problems for cardiac mechanics. These benchmark problems test the ability to accurately simulate pressure-type forces that depend on the deformed objects geometry, anisotropic and spatially varying material properties similar to those seen in the left ventricle and active contractile forces.

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences , Bitbucket

A Spatially Detailed Model of Isometric Contraction Based on Competitive Binding of Troponin I Explains Cooperative Interactions between Tropomyosin and Crossbridges

Land S, Niederer SA. PLoS Computational Biology, 2015

A spatially detailed ODE model of contraction based on continuous flexible chain model of the thin filament. Includes explicit TnI kinetics and a biophysically detailed representation of RU-RU, RU-XB, and XB-XB cooperativity.

PLOS , Matlab

An analysis of deformation-dependent electromechanical coupling in the mouse heart

Land S, Niederer SA, Aronsen JM, Espe EK, Zhang L, Louch WE, Sjaastad I, Sejersted OM, Smith NP. J Physiol. 2012 15;590(Pt 18):4553-69. Epub 2012 May 21. PubMed ID: 22615436

A model of contraction fitted to mouse data at physiological temperature and frequency, including length and velocity dependent tension generation.

Journal of Physiology , cellML , Matlab

A mathematical model of the murine ventricular myocyte: a data-driven biophysically based approach applied to mice overexpressing the canine NCX isoform A Mathematical Model of the Slow Force Response to Stretch in Rat Ventricular Myocytes

L. Li , S. A. Niederer , W. Idigo , Y. H. Zhang , P. Swietach , B. Casadei , N. P. Smith, 2010 American Journal of Physiology, Voume 299 no. H1045-H1063

A mouse electrophysiology model fitted to mouse data at physiological temperatures and capable of pacing to physiological pacing rates.

American Journal of Physiology , cellML

A Quantitative Analysis of Cardiac Myocyte Relaxation: A Simulation Study

Steven Niederer, Peter Hunter, Nicholas Smith, 2006 Biophysical Journal, 90 1697-1722 PubMed ID: 16339881

A biophysical data driven model of length, velocity and calcium dependent tension development in rat cardiac muscle at room temperature.

Science Direct , cellML