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Pulmonary Veins

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Pulmonary Artery-Vein Classification in CT Images Using Deep Learning.

IEEE transactions on medical imaging 29993996
Recent studies show that pulmonary vascular diseases may specifically affect arteries or veins through different physiologic mechanisms. To detect changes in the two vascular trees, physicians manually analyze the chest computed tomography (CT) image...
Algorithms Deep Learning Humans Image Processing, Computer-Assisted Pulmonary Artery Pulmonary Disease, Chronic Obstructive Pulmonary Veins Tomography, X-Ray Computed
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Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Heart and vessels 30140958
Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndrome) are factors commonly related to AF recurrence. This study aims to assess the predictive value o...
Algorithms Atrial Fibrillation Cryosurgery Electrocardiography, Ambulatory Female Follow-Up Studies Heart Conduction System Humans Machine Learning Male Middle Aged Prognosis Pulmonary Veins Recurrence Retrospective Studies Time Factors
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Comparisons of efficacy, safety, and recurrence risk factors of paroxysmal and persistent atrial fibrillation catheter ablation using robotic magnetic navigation system.

Clinical cardiology 30652336
BACKGROUND: No data exist on comparisons of efficacy, safety, and recurrence risk factors of paroxysmal and persistent atrial fibrillation (AF) ablation using robotic magnetic navigation system (MNS), respectively.
Adolescent Adult Aged Atrial Fibrillation Catheter Ablation Echocardiography Equipment Design Female Follow-Up Studies Heart Atria Heart Conduction System Heart Rate Humans Male Middle Aged Prospective Studies Pulmonary Veins Recurrence Risk Factors Robotics Surgery, Computer-Assisted Tomography, X-Ray Computed Treatment Outcome Young Adult
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Deep residual network for off-resonance artifact correction with application to pediatric body MRA with 3D cones.

Magnetic resonance in medicine 31115936
PURPOSE: To enable rapid imaging with a scan time-efficient 3D cones trajectory with a deep-learning off-resonance artifact correction technique.
Artifacts Child Child, Preschool Deep Learning Female Humans Imaging, Three-Dimensional Magnetic Resonance Angiography Male Phantoms, Imaging Pulmonary Veins
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Atrial scar quantification via multi-scale CNN in the graph-cuts framework.

Medical image analysis 31811981
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the quantification and analysis of atrial scars can be challenging due to...
Atrial Fibrillation Catheter Ablation Cicatrix Contrast Media Heart Atria Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Pulmonary Veins
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Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Circulation. Arrhythmia and electrophysiology 32536204
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Action Potentials Aged Atrial Fibrillation Catheter Ablation Contrast Media Diagnosis, Computer-Assisted Female Heart Rate Humans Machine Learning Magnetic Resonance Imaging Male Meglumine Middle Aged Models, Cardiovascular Organometallic Compounds Patient-Specific Modeling Predictive Value of Tests Proof of Concept Study Pulmonary Veins Recurrence Reproducibility of Results Retrospective Studies Risk Assessment Risk Factors Treatment Outcome
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The Clinical Application of the Deep Learning Technique for Predicting Trigger Origins in Patients With Paroxysmal Atrial Fibrillation With Catheter Ablation.

Circulation. Arrhythmia and electrophysiology 33021404
BACKGROUND: Non-pulmonary vein (NPV) trigger has been reported as an important predictor of recurrence post-atrial fibrillation ablation. Elimination of NPV triggers can reduce the recurrence of postablation atrial fibrillation. Deep learning was app...
Action Potentials Adult Aged Atrial Fibrillation Catheter Ablation Computed Tomography Angiography Deep Learning Female Heart Rate Humans Male Middle Aged Phlebography Predictive Value of Tests Pulmonary Veins Radiographic Image Interpretation, Computer-Assisted Recurrence Reproducibility of Results Retrospective Studies Risk Assessment Risk Factors Time Factors Treatment Outcome
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Machine Learning-Derived Fractal Features of Shape and Texture of the Left Atrium and Pulmonary Veins From Cardiac Computed Tomography Scans Are Associated With Risk of Recurrence of Atrial Fibrillation Postablation.

Circulation. Arrhythmia and electrophysiology 33576688
[Figure: see text].
Action Potentials Atrial Fibrillation Atrial Function, Left Catheter Ablation Female Fractals Heart Atria Heart Rate Humans Machine Learning Male Middle Aged Predictive Value of Tests Pulmonary Veins Radiographic Image Interpretation, Computer-Assisted Recurrence Retrospective Studies Risk Assessment Risk Factors Tomography, X-Ray Computed Treatment Outcome
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A machine learning-based pulmonary venous obstruction prediction model using clinical data and CT image.

International journal of computer assisted radiology and surgery 33791921
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...
Area Under Curve Humans Logistic Models Lung Machine Learning Neural Networks, Computer Predictive Value of Tests Pulmonary Veins ROC Curve Tomography, X-Ray Computed Vascular Diseases
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A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT.

BMC medical imaging 33750343
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.
Aged Atrial Appendage Atrial Fibrillation Catheter Ablation Female Heart Atria Humans Machine Learning Male Middle Aged Prognosis Pulmonary Veins Recurrence Retrospective Studies ROC Curve
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