DOI: 10.5061/dryad.kkwh70sg0
title: Predicting arrhythmia recurrence post-ablation in atrial fibrillation using explainable machine learning: Atrial meshes

description: This repository contains computational meshes of human left atria
 segmented from late gadolinium enhanced cardiac magnetic resonance imaging
 (LGE-MRI) for patients receiving a catheter ablation for atrial
 fibrillation. There are two models per patient (pre-ablation with patterns
 of fibrotic remodeling, post-ablation with scar created by the procedure)
 for 82 individuals. These meshes support the replication of our findings
 while protecting confidential patient information.
description: This study retrospectively included patients from University of
 Washington (UW) Medical Center with documented persistent atrial
 fibrillation (AFib) or paroxysmal AFib who had already received both pre-
 and post-procedural LGE-MRI scans and underwent either cryoballoon or
 radiofrequency (RF) ablation. Cardiac late gadolinium enhanced magnetic
 resonance images (LGE-MRI) were obtained using previously described
 protocols for all participants within 90 days prior to their ablation
 procedure and again 3-6 months post-ablation to quantify the extent of LA
 fibrosis and scar, respectively. Exclusion criteria for AFib patients
 included those who had a prior catheter ablation, patients with cardiac
 implantable electronic devices, severe claustrophobia, renal dysfunction,
 and contraindications to MRI or gadolinium-based contrast. Scans were
 performed on the Philips Ingenia system, 15–25 min after contrast
 injection, using a three-dimensional inversion-recovery,
 respiration-navigated, ECG-gated, gradient echo pulse sequence.
 Acquisition parameters included transverse imaging volume with a voxel
 size of 1.25 × 1.25 × 2.5 mm (reconstructed to 0.625 × 0.625 × 1.25 mm).
 Scan time was 5–10 minutes dependent on respiration and heart
 rate. Patients had clinical assessment and catheter
 ablation in the UW AFib program. All patients underwent pulmonary vein
 isolation (PVI), and some had additional substrate modification at the
 operator’s discretion. <strong> </strong>
 Geometric models were reconstructed from both pre- and post-
 ablation LGE-MRI scans by Merisight Inc. (Salt Lake City, UT) to assess LA
 volume and surface area. Geometric models were reconstructed from
 pre-ablation scans and the relative extent of fibrosis in the LA was
 quantified via an adaptive histogram thresholding algorithm to determine
 pre-ablation LGE-MRI derived fibrosis. For post-ablation models, ablation
 scar was quantified on post-ablation LGE-MRI using previously established
 methods. Non-rigid registration was used to map LGE-derived post-ablation
 scar patterns onto existing LA pre-ablation fibrotic models.
 Hyper-enhancement on post-ablation scans was assumed to be
 ablation-induced scar; this accounts for the fact that hyperenhancement
 from ablation scar is at a higher absolute level than that of native
 fibrosis. Consequently, regions labeled as fibrotic pre-ablation fall
 below the hyperenhancement threshold in post-procedure scans.
description: # Predicting arrhythmia recurrence post-ablation in atrial fibrillation
 using explainable machine learning: Atrial meshes Dataset DOI:
 [10.5061/dryad.kkwh70sg0](10.5061/dryad.kkwh70sg0) These meshes are linked
 to an accepted paper which will be published around mid-August 2025. Once
 the paper is published and the embargo period has ended, a link will be
 added to this repository. If you use these models, please cite this
 repository our paper. ## Description of the data and file structure This
 repository contains computational meshes of human left atria segmented
 from late gadolinium enhanced cardiac magnetic resonance imaging (LGE-MRI)
 for patients receiving a catheter ablation for atrial fibrillation. There
 are two models per patient (pre-ablation with patterns of fibrotic
 remodeling, post-ablation with scar created by the procedure) for 82
 individuals. These meshes support the replication of our findings while
 protecting confidential patient information. ### Files and variables
 Computational meshes are provided in VTK format. The same deidentified
 numbers used in the publication to identify the holdout patients
 correspond to the meshes for ID numbers 1-15 in this dataset. Patients in
 the original cohort were assigned ID numbers 21-87. We used this format
 (`vtk_bin`) in the interest of reproducibility. To reduce the total size
 of the repository, meshes have been downsampled to an average edge length
 of 0.5 mm; before running simulations using these meshes, please consider
 resampling to an appropriate resolution (e.g., ~0.2 mm for
 reaction-diffuction simulations of electrophysiology). These files can be
 converted to a machine- and human-readable text format compatible with the
 `openCARP` simulation framework using the free software `meshtool`
 (available [here](https://bitbucket.org/aneic/meshtool/src)), e.g.: `$
 /path/to/meshtool convert -imsh ID001_PostAbl -ifmt vtk_bin -omsh
 ID001_PostAbl -ofmt carp_txt` Once each mesh is converted from `carp_bin`
 to `carp_txt` format, the resulting files (`.pts`, `.elem`, `.lon`) can be
 opened in a text editor and the explicit values of Cartesian coordinates,
 element specifications, and fiber orientation vectors can be seen.
 Attached files are structured as follows. * holdout_cohort.tgz *
 ID001_PreAbl_rev1.vtk * ID001_PostAbl_rev1.vtk * ... *
 ID015_PreAbl_rev1.vtk * ID015_PostAbl_rev1.vtk * training_cohort.tgz *
 ID021_PreAbl_rev1.vtk * ID021_PostAbl_rev1.vtk * ... *
 ID087_PreAbl_rev1.vtk * ID087_PostAbl_rev1.vtk ## Code/software We used
 openCARP ([https://opencarp.org/](https://opencarp.org/)) [1] to run
 simulations. openCARP is open software licensed under the Academic Public
 License. Please read and abide by the relevant licenses if you choose to
 use these tools. More information about the licenses for both of these
 tools is available at this stable
 link: [https://opencarp.org/download/license](https://opencarp.org/download/license). A good option for visualizing these models is [NumeriCor Studio for Academia](https://numericor.at/rlb/wordpress/resources/), which is freely available and has binary installers for Linux, Mac, and Windows. .vtk files can also be used with the free/open source Paraview software: https://www.paraview.org/.  ## References 1. Plank, G. et al. The openCARP simulation environment for cardiac electrophysiology. *Comput Methods Programs Biomed* **208**, 106223 (2021). [https://doi.org/10.1016/j.cmpb.2021.106223](https://doi.org/10.1016/j.cmpb.2021.106223) ## Human subjects data This repository contains computational meshes of human left atria segmented from late gadolinium enhanced cardiac magnetic resonance imaging. These meshes support the replication of our findings while protecting confidential patient information. This study was approved by the University of Washington Institutional Review Board. All participants provided written informed consent.