AIMC Topic: Pulmonary Veins
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Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.
Nature communications
Mar 6, 2025
Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditional methods rely on Computed Tomography Pulmonary Angiography (CTPA), which requires contrast agents with potential health risks. Non-contrast CT, a s...
Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial.
Nature medicine
Feb 14, 2025
Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fibrillation (AF), the optimal ablation procedure for persistent and long-standing persistent AF remains elusive. Targeting spatio-temporal electrogram d...
Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach.
JMIR cardio
Feb 11, 2025
BACKGROUND: Atrial fibrillation (AF) is a prevalent arrhythmia associated with significant morbidity and mortality. Despite advancements in ablation techniques, predicting recurrence of AF remains a challenge, necessitating reliable models to identif...
Left Atrial Wall Thickness Measured by a Machine Learning Method Predicts AF Recurrence After Pulmonary Vein Isolation.
Journal of cardiovascular electrophysiology
Nov 29, 2024
BACKGROUND: Left atrial (LA) remodeling plays a significant role in the progression of atrial fibrillation (AF). Although LA wall thickness (LAWT) has emerged as an indicator of structural remodeling, its impact on AF outcomes remains unclear. We aim...
Catheter Ablation
Recurrence
Atrial Function, Left
Pulmonary Veins
Atrial Fibrillation
Heart Atria
Heart Rate
Atrial Remodeling
Middle Aged
Risk Assessment
Time Factors
Treatment Outcome
Action Potentials
Predictive Value of Tests
Registries
Fibrosis
Female
Risk Factors
Aged
Male
Humans
Machine Learning
Retrospective Studies
Neural network reconstruction of the left atrium using sparse catheter paths.
International journal of computer assisted radiology and surgery
Sep 16, 2024
PURPOSE: Catheter-based radiofrequency ablation for pulmonary vein isolation has become the first line of treatment for atrial fibrillation in recent years. This requires a rather accurate map of the left atrial sub-endocardial surface including the ...
Clinical value of artificial intelligence 3D echocardiography in evaluating left atrial volume and pulmonary vein structure in patients with atrial fibrillation.
Clinics (Sao Paulo, Brazil)
Sep 15, 2024
OBJECTIVE: To explore the clinical value of 3D Echocardiography (3DE) in evaluating the changes of left atrial volume and pulmonary vein structure in patients with Atrial Fibrillation (AF).
DECNet: Left Atrial Pulmonary Vein Class Imbalance Classification Network.
Journal of imaging informatics in medicine
Aug 20, 2024
In clinical practice, the anatomical classification of pulmonary veins plays a crucial role in the preoperative assessment of atrial fibrillation radiofrequency ablation surgery. Accurate classification of pulmonary vein anatomy assists physicians in...
Robot-assisted thoracic surgery is effective for right upper lobectomy in cases with a rare variation pattern of the pulmonary veins.
BMJ case reports
Apr 1, 2022
A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image.
International journal of computer assisted radiology and surgery
Mar 31, 2021
PURPOSE: In this study, we try to consider the most common type of total anomalous pulmonary venous connection and established a machine learning-based prediction model for postoperative pulmonary venous obstruction by using clinical data and CT imag...
A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT.
BMC medical imaging
Mar 9, 2021
OBJECTIVE: To investigate left atrial shape differences on CT scans of atrial fibrillation (AF) patients with (AF+) versus without (AF-) post-ablation recurrence and whether these shape differences predict AF recurrence.
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