Evaluation of an Open-Source Pipeline to Create Patient-Specific Left Atrial Models: A Reproducibility Study
Jose Alonso Solis-Lemus, Tiffany Baptiste, Rosie Barrows, Charles, Sillett, Ali Gharaviri, Giulia Raffaele, Orod Razeghi, Marina Strocchi, Iain, Sim, Irum Kotadia, Neil Bodagh, Daniel O'Hare, Mark O'Neill, Steven E, Williams, Caroline Roney, Steven Niederer

TL;DR
This study introduces an open-source pipeline for creating patient-specific left atrial models with fiber and fibrosis data, demonstrating high reproducibility and efficiency across multiple operators for electrophysiology simulations.
Contribution
The paper presents a semi-automatic, reproducible pipeline for generating detailed LA models from CMR data, including fiber and fibrosis mapping, with validation of inter/intra-operator variability.
Findings
High fibrosis and fiber orientation agreement (ICC > 0.9) among operators.
Reproducible LAT and PS maps with low activation time differences.
Model creation time averaged around 17 seconds per case.
Abstract
We present an open-source software pipeline to create patient-specific left atrial (LA) models with fibre orientations and a fibrosis map, suitable for electrophysiology simulations. The semi-automatic pipeline takes as input a contrast enhanced magnetic resonance angiogram, and a late gadolinium enhanced (LGE) contrast magnetic resonance (CMR). Five operators were allocated 20 cases each from a set of 50 CMR datasets to create a total of 100 models to evaluate inter/intra-operator variability. Each output model consisted of (1) a labelled surface mesh open at the pulmonary veins (PV) and mitral valve (MV), (2) fibre orientations mapped from a diffusion tensor MRI human atlas, (3) fibrosis map from the LGE-CMR scan, and (4) simulation of local activation time (LAT) and phase singularity (PS) mapping. We evaluated reproducibility in our pipeline by comparing agreement in shape of the…
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Taxonomy
TopicsAdvanced MRI Techniques and Applications · Cardiovascular Function and Risk Factors · Advanced Neuroimaging Techniques and Applications
