In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3)

Abstract: 1.8 million ECGs derived from multiscale simulations of cardiac electrophysiology of ventricular extrasystoles. 1000 anatomical variants of a bi-ventricular mesh x 600 excitation origins x 3 heart posiitions in the torso. TechnicalRemarks: This dataset contains about 1.8 million body surface potentials (BSPs) simulated using 1000 heart models generated using a statistical shape model. It has been used in [1,1a]. Here, only the noise-free BSPs are provided.

Due to its size, this is a multi-part dataset. Part 1: https://doi.org/10.5445/IR/1000156139 Part 2: https://doi.org/10.5445/IR/1000156554 Part 3: https://doi.org/10.5445/IR/1000156555 Part 4: https://doi.org/10.5445/IR/1000156556 Part 5: https://doi.org/10.5445/IR/1000156557

Each archive XXXX-YYYY.tar contains 20 heart models and corresponding signals. Each subdirectory within the archive contains:

  • heart.vtp: A triangle mesh of the heart including the point data:
  • ab, rt, rtCos, rtSin, tm, tv: Consistent biventricular coordinates [2].
  • class: Boundary regions used as input for the computation of fiber orientations [3].
  • trigger: 1-based indices of the ca. 600 foci (-1000 if not a focus).

  • heart_transform_matrices.mat: A 1 x 3 cell array containing 4 x 4 transformation matrices that describe the pose of the heart within the torso. Apply the matrix from heart_transform_matrices.mat to the nodes in heart.vtp.

  • actTimes.mat: A numNodes x numFoci matrix of activation times computed using the fast iterative method [4,5] (conduction velocity in fiber direction: 1 m/s, perpendicular to fiber direction: 1/2.7 m/s).

  • bsp.mat:

  • bsp: A numElectrodes x numTimeSamples x numHeartPoses x numFoci matrix of BSPs computed by aligning a transmembrane voltage template with scaled activation times (see actTimeScalings.mat below) and solving the second bidomain equation using the boundary element method [6].
  • bspEnd: Time index of the end of depolarization (largest scaled activation time).

The archive general.tar contains heart-model-independent data and parameters used to generate the individual heart models:

  • torso.vtp: A triangle mesh of the torso including the point data:
  • electrodes: 1-based indices of the 200 electrodes (-1000 if not an electrode).

  • heart_meanshape.vtp: A triangle mesh of the mean shape of the statistical shape model [7,8].

  • heart_shapemodel.mat:

  • pc: A 3*numNodes x numModes matrix of principal components (numModes = 100).
  • var: A numModes x 1 vector of variances.
  • weights: A numModes x numModels matrix of weights used to generate the 1000 heart models.

  • heart_alignment_matrix.mat: A 4 x 4 transformation matrix describing the alignment of the mean shape with the torso-specific heart. Only to be appleid to node coordinates in within general.tar (already contained in heart_transform_matrices.mat).

  • heart_transform_params.mat: A struct containing roll, pitch, yaw angles and x, y, z translations used to generate the heart_transform_matrices.mat (see above).

  • fiber_angles.mat:

  • alphaEndo: numModels x 1 vector of endocardial fiber angles used to generate fiber orientations.
  • alphaEpi: numModels x 1 vector of epicardial fiber angles used to generate fiber orientations.

  • actTimeScalings.mat:

  • A numModels x numFoci matrix of factors used to scale the activation times.

  • tmv_template.mat: The transmembrane voltage time course used to compute BSPs.

  • heart_classes.vtp: A coarse triangle mesh of the mean shape used for fuzzy classification.

  • heart_classes_subdiv.vtp: A subdivided version of the coarse triangle mesh of the mean shape used to convert between Cobiveco and barycentric coordinates.

[1] https://doi.org/10.48550/arXiv.2209.08095 [1a]https://doi.org/10.1016/j.artmed.2023.102619 [2] https://doi.org/10.1016/j.media.2021.102247 [3] https://github.com/KIT-IBT/LDRB_Fibers [4] https://github.com/KIT-IBT/FIM_Eikonal [5] https://doi.org/10.1137/120881956 [6] https://doi.org/10.1016/j.cmpb.2007.09.004 [7] https://doi.org/10.5281/zenodo.4506463 [8] https://doi.org/10.1016/j.media.2015.08.009

Cite this as

Pilia, Nicolas, Schuler, Steffen, Rees, Maike, Moik, Gerald, Potyagaylo, Danila, Dössel, Olaf, Loewe, Axel (2023). Dataset: In silico electrocardiograms of 1.8 million ventricular extrasystoles and corresponding activation maps (part 3). https://doi.org/10.35097/1534

DOI retrieved: 2023

Additional Info

Field Value
Imported on August 4, 2023
Last update August 4, 2023
License CC BY-NC-SA 4.0 Attribution-NonCommercial-ShareAlike
Source https://doi.org/10.35097/1534
Author Pilia, Nicolas
More Authors
Schuler, Steffen
Rees, Maike
Moik, Gerald
Potyagaylo, Danila
Dössel, Olaf
Loewe, Axel
Source Creation 2023
Publishers
Karlsruhe Institute of Technology
Production Year 2023
Publication Year 2023
Subject Areas
Name: Engineering