Data for generating patient-specific computational models with point cloud data from human atrial electrophysiology studies
Data files
Mar 10, 2026 version files 1.41 GB
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Fibrosis_Region_Coordinates_Samples.zip
5.12 MB
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Patient_Electrode_Sites.zip
47.28 KB
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Patient_Meshes_(Unrefined).zip
3.59 MB
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README.md
5.38 KB
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Refined_Coordinate_Points_and_Fiber_Orientations.zip
34.69 MB
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Simulation_Results_Sample_(Refined).zip
1.37 GB
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Useful_MATLAB_Functions.zip
18.32 KB
Abstract
This dataset contains anonymized patient-specific atrial electrophysiology simulation data, geometric models, and computational simulation outputs used in the study of building point cloud data computational models. The dataset includes patient-specific electrode site coordinates and patient-specific LAPW meshes created using the surface points. Additional data describe fibrosis region samples mapped onto the atrial geometries, refined mesh point clouds with associated fiber orientations, and results from electrophysiological wave propagation simulations performed on the refined meshes. MATLAB scripts used for data preprocessing and analysis are provided to facilitate transparency and reproducibility. All patient data have been anonymized prior to sharing, and no personally identifiable information is included. These data are intended to support reproducible research in cardiac electrophysiology modeling and to enable further investigation into patient-specific conduction properties and arrhythmia mechanisms.
Dataset DOI: 10.5061/dryad.c866t1gn7
Description of the data and file structure
This dataset was generated to support the development and validation of patient-specific computational models of human atrial electrophysiology, with a focus on the left atrial posterior wall. The data include anonymized simulated electrograms recordings, electrode locations, geometric point clouds, and finite element meshes derived from clinical electrophysiology studies conducted using the CARTO 3 system.
The dataset also includes derived spatial data such as fibrosis region samples, atlas-mapped fiber orientations, and outputs from electrophysiology simulations performed on refined patient-specific meshes using monodomain models. Together, these data enable the reconstruction of patient-specific atrial geometries, the calculation of extracellular electrograms, and the investigation of relationships between tissue substrate, conduction properties, and electrogram morphology.
Files and variables
File: Fibrosis_Region_Coordinates_Samples.zip
Description:
This archive contains CSV files with spatial coordinate samples representing regions where fibrosis can be modeled on patient-specific left atrial geometries. Each CSV file corresponds to a patient and consists of rows of 3D points (x,y,z) derived from refined atrial meshes. These coordinates are intended for mapping fibrosis distributions onto computational meshes used in electrophysiology simulations.
File: Patient_Electrode_Sites.zip
Description:
This archive contains CSV files specifying electrode site locations for each patient. Each file includes rows of spatial coordinates (x, y, z) corresponding to electrode positions at which extracellular electrograms were recorded and simulated. These coordinates align with the patient-specific geometries provided in this dataset.
File: Patient_Meshes_(Unrefined).zip
Description:
This archive contains patient-specific finite element meshes of the left atrial posterior wall in unrefined form (Exodus II format). These meshes were generated from point cloud data and represent the initial geometric discretization. Additional mesh refinement is required before use in electrophysiology simulations or fiber orientation mapping.
File: Useful_MATLAB_Functions.zip
Description:
This archive contains MATLAB scripts and functions used for data preprocessing, analysis, and post-processing. Included are tools for anatomical region extraction from point clouds, electrogram feature computation, signal classification, and generation of fibrosis patterns using a Perlin noise approach. The scripts are provided to support transparency and reproducibility and are not intended as a standalone software package.
File: Refined_Coordinate_Points_and_Fiber_Orientations.zip
Description:
This archive contains CSV files with refined mesh node coordinates and corresponding fiber, sheet, and normal orientation vectors for patient-specific atrial models. Each row represents a mesh node, with columns x, y, z for spatial coordinates and fiberx, fibery, fiberz, sheathx, sheathy, sheathz, normalx, normaly, normalz for orientation components. Fiber orientations were mapped using atlas-based methods.
File: Simulation_Results_Sample_(Refined).zip
Description:
This archive contains sample outputs from electrophysiology simulations performed on refined patient-specific meshes. Files are provided in VTK format and represent transmembrane potential propagation over time. These results are intended for qualitative visualization and validation using software such as ParaView.
Code/software
The data can be viewed and processed using the following free or commonly used scientific software:
- MATLAB (custom scripts and functions included in the dataset)
- ParaView (for visualization of VTK simulation outputs)
- Coreform Cubit (mesh generation and refinement)
- Blender (geometry inspection and preprocessing)
- libMesh (finite element framework used in electrophysiology simulations)
Included MATLAB scripts were used for data preprocessing, electrogram characterization, mesh manipulation, and fibrosis pattern generation. These include functions for extracting atrial subregions, classifying electrogram morphologies, calculating electrogram features, and generating spatial fibrosis patterns using a Perlin noise approach.
The workflow involves extracting atrial geometries from point clouds, refining meshes, mapping fiber orientations, running monodomain electrophysiology simulations on refined meshes, and computing extracellular electrograms at specified electrode locations.
Access information
The dataset to do preliminary processing for simulations came from clinical data (not included in this repository) previously published in:
Gaeta, S. et al., Heart Rhythm, 2020, doi:10.1016/j.hrthm.2019.12.010.
Fiber orientation mapping methods used atlas-based approaches described in:
Rossi, S. et al., Frontiers in Physiology, 2022, doi:10.3389/fphys.2022.912947.
All data in this repository are shared under a Creative Commons Zero (CC0 1.0) license.