ArticleFrontiers in physiology2017
Novel Computational Analysis of Left Atrial Anatomy Improves Prediction of Atrial Fibrillation Recurrence after Ablation.
Article in Frontiers in physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing.Computer methods in applied mechanics and engineering · 2026Article
- Three-Dimensional Left Atrial Geometry in Atrial Fibrillation: Imaging Biomarkers, Substrate Phenotyping, and Ablation Outcome Prediction.Diagnostics (Basel, Switzerland) · 2026Review
- Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation.Royal Society open science · 2025Article
- Automated three-dimensional left atrial analysis on computed tomography angiography: reproducibility and workflow efficiency of eight clinically relevant metrics using a deep learning pipeline.Frontiers in bioengineering and biotechnology · 2025Article
- Semi-supervised segmentation of cardiac chambers from LGE-CMR using feature consistency awareness.BMC cardiovascular disorders · 2024Article
- Differentiating Left Ventricular Remodeling in Aortic Stenosis From Systemic Hypertension.Circulation. Cardiovascular imaging · 2024Article
- Leveraging 3D Atrial Geometry for the Evaluation of Atrial Fibrillation: A Comprehensive Review.Journal of clinical medicine · 2024Review
- Left Atrial Roof Enlargement Is a Distinct Feature of Heart Failure With Preserved Ejection Fraction.Circulation. Cardiovascular imaging · 2024Article
- DeepSSM: A blueprint for image-to-shape deep learning models.Medical image analysis · 2024Article
- Value of Imaging in the Non-Invasive Prediction of Recurrence after Catheter Ablation in Patients with Atrial Fibrillation: An Up-to-Date Review.Reviews in cardiovascular medicine · 2023Review
- Use of left atrial automated functional myocardial imaging to identify patients with paroxysmal atrial fibrillation at high risk of stroke.Quantitative imaging in medicine and surgery · 2023Article
- Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta.Journal of cardiovascular translational research · 2023Article
- Left ventricular anatomy in obstructive hypertrophic cardiomyopathy: beyond basal septal hypertrophy.European heart journal. Cardiovascular Imaging · 2023Article
- An Artificial Intelligence-Enabled ECG Algorithm for Predicting the Risk of Recurrence in Patients with Paroxysmal Atrial Fibrillation after Catheter Ablation.Journal of clinical medicine · 2023Article
- Exploring interpretability in deep learning prediction of successful ablation therapy for atrial fibrillation.Frontiers in physiology · 2023Article
- Progressive and Simultaneous Right and Left Atrial Remodeling Uncovered by a Comprehensive Magnetic Resonance Assessment in Atrial Fibrillation.Journal of the American Heart Association · 2022Article
- Understanding and Improving Risk Assessment After Myocardial Infarction Using Automated Left Ventricular Shape Analysis.JACC. Cardiovascular imaging · 2022Article
- Le Cœur en Sabot: shape associations with adverse events in repaired tetralogy of Fallot.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2022Article
- Cardiac and placental imaging (CARP) in pregnancy to assess aetiology of preeclampsia.Placenta · 2022Article
- Big Data in electrophysiology.Herzschrittmachertherapie & Elektrophysiologie · 2022Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The left atrium (LA) can change in size and shape due to atrial fibrillation (AF)-induced remodeling. These alterations can be linked to poorer outcomes of AF ablation. In this study, we propose a novel comprehensive computational analysis of LA anatomy to identify what features of LA shape can optimally predict post-ablation AF recurrence. To this end, we construct smooth 3D geometrical models from the segmentation of the LA blood pool captured in pre-procedural MR images. We first apply this methodology to characterize the LA anatomy of 144 AF patients and build a statistical shape model that includes the most salient variations in shape across this cohort. We then perform a discriminant analysis to optimally distinguish between recurrent and non-recurrent patients. From this analysis, we propose a new shape metric called vertical asymmetry, which measures the imbalance of size along the anterior to posterior direction between the superior and inferior left atrial hemispheres. Vertical asymmetry was found, in combination with LA sphericity, to be the best predictor of post-ablation recurrence at both 12 and 24 months (area under the ROC curve: 0.71 and 0.68, respectively) outperforming other shape markers and any of their combinations. We also found that model-derived shape metrics, such as the anterior-posterior radius, were better predictors than equivalent metrics taken directly from MRI or echocardiography, suggesting that the proposed approach leads to a reduction of the impact of data artifacts and noise. This novel methodology contributes to an improved characterization of LA organ remodeling and the reported findings have the potential to improve patient selection and risk stratification for catheter ablations in AF.
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