ArticleJACC. Advances2024
AI-Enabled CT Cardiac Chamber Volumetry Predicts Atrial Fibrillation and Stroke Comparable to MRI.
Article in JACC. Advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Comparing incidence of heart failure in individuals with enlarged cardiac chambers versus diabetes.American journal of preventive cardiology · 2026Article
- Serum asprosin levels as a subclinical atherosclerosis marker in patients with primary hypertension.BMC cardiovascular disorders · 2026Article
- AI-CVD-HF: A heart failure risk prediction model based on coronary artery calcium scans compared with PREVENT-HF.American journal of preventive cardiology · 2026Article
- Article
- Aortic and Cardiac Structure From Routine CT Predict Cardiovascular Risk Beyond PREVENT and Coronary Calcium.JACC. Cardiovascular imaging · 2026Article
- Interpretable machine learning models for stroke risk prediction in patients with newly diagnosed atrial fibrillation.NPJ digital medicine · 2026Article
- Artificial intelligence-enabled cardiac volumetry for opportunistic screening of cardiomegaly on chest CT: clinical validation with echocardiography.Radiology advances · 2026Article
- Artificial Intelligence-derived Measurements of Myosteatosis from Coronary Artery Calcium CT Scans to Predict COPD: The Multi-Ethnic Study of Atherosclerosis.Radiology. Cardiothoracic imaging · 2026Article
- Opportunistic AI-derived adiposity measures from coronary artery calcium scans predict new-onset type 2 diabetes in adults without obesity or hyperglycemia: insights from the AI-CVD study within MESA.Diabetology & metabolic syndrome · 2025Article
- Artificial intelligence in coronary artery calcification scoring: Current progress and future directions.Global cardiology science & practice · 2025Review
- AI-enabled opportunistic measurement of liver steatosis in coronary artery calcium scans predicts cardiovascular events and all-cause mortality: an AI-CVD study within the Multi-Ethnic Study of Atherosclerosis (MESA).BMJ open diabetes research & care · 2025Article
- Recurrence and non-improvement of European Heart Rhythm Association symptom scores after atrial fibrillation ablation: the role of left atrial fractal dimension.Quantitative imaging in medicine and surgery · 2025Article
- Fully Automated Assessment of Cardiac Chamber Volumes and Myocardial Mass on Non-Contrast Chest CT with a Deep Learning Model: Validation Against Cardiac MR.Diagnostics (Basel, Switzerland) · 2024Article
- New Frontiers for Predicting Atrial Fibrillation and Stroke: AI-Based Left Atrial Volumetry.JACC. Advances · 2024Article
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11 authors.
Funding
Abstract
Background: AI-CAC provides more actionable information than the Agatston coronary artery calcium (CAC) score. We have recently shown in the MESA (Multi-Ethnic Study of Atherosclerosis) that AI-CAC automated left atrial (LA) volumetry enabled prediction of atrial fibrillation (AF) as early as 1 year. Objectives: In this study, the authors evaluated the performance of AI-CAC LA volumetry versus LA measured by human experts using cardiac magnetic resonance imaging (CMRI) for predicting incident AF and stroke and compared them with Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF) risk score, Agatston score, and N-terminal pro b-type natriuretic peptide (NT-proBNP). Methods: We used 15-year outcomes data from 3,552 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) who underwent both CAC scans and CMRI in the MESA baseline examination. CMRI LA volume was previously measured by human experts. Data on NT-proBNP, CHARGE-AF risk score, and the Agatston score were obtained from MESA. Discrimination was assessed using the time-dependent area under the curve. Results: Over 15 years follow-up, 562 cases of AF and 140 cases of stroke accrued. The area under the curve for AI-CAC versus CMRI volumetry for AF (0.802 vs 0.798) and stroke (0.762 vs 0.751) were not significantly different. AI-CAC LA significantly improved the continuous net reclassification index for prediction of 5-year AF when added to CHARGE-AF risk score (0.23), NT-proBNP (0.37, 0.37), and Agatston score (0.44) ( Conclusions: AI-CAC automated LA volumetry and CMRI LA volume measured by human experts similarly predicted incident AF and stroke over 15 years. Further studies to investigate the clinical utility of AI-CAC for AF and stroke prediction are warranted.
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