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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
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Acute Coronary Syndrome (ACS) encompasses a spectrum of heart conditions caused by sudden obstruction of coronary arteries, typically resulting from the rupture of an atherosclerotic plaque and subsequent thrombus (blood clot) formation. This obstruction can lead to partial or complete blockage of blood flow, causing varying degrees of myocardial ischemia or infarction.ACS includes the following clinical entities:Unstable Angina (UA)Non-ST-Elevation Myocardial Infarction (NSTEMI)ST-Elevation...
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Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...
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Patient-Specific Myocardial Infarction Risk Thresholds From AI-Enabled Coronary Plaque Analysis.

Robert J H Miller1,2, Nipun Manral1, Andrew Lin1,3,4

  • 1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA (R.J.J.M., N.M., A.L., A.S., C.P., A.K., P.M., A.R., K.G., A.C.K., D.H., K.K., G.F.T., J.G., H.G., S.C., D.S.B., P.J.S., D.D.).

Circulation. Cardiovascular Imaging
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Summary
This summary is machine-generated.

Deep learning accurately quantifies coronary plaque from CT angiography. High plaque volumes, especially in older men, significantly predict myocardial infarction risk, highlighting its clinical utility.

Keywords:
cardiac imaging techniquescoronary artery diseasedeep learningmyocardial infarctionplaque, atherosclerotic

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Area of Science:

  • Cardiovascular Imaging
  • Artificial Intelligence in Medicine
  • Radiomics

Background:

  • Coronary computed tomography angiography (CCTA) enables plaque quantification for cardiovascular risk prediction.
  • Deep learning (DL) offers automated plaque quantification from CCTA.
  • This study establishes age- and sex-specific DL-based plaque distributions and evaluates their predictive power for myocardial infarction.

Purpose of the Study:

  • To determine age- and sex-specific distributions of DL-quantified coronary plaque volumes.
  • To assess the predictive value of these DL-based plaque measurements for myocardial infarction (MI) risk.

Main Methods:

  • A validated DL system quantified coronary plaque from CCTA in 2803 patients.
  • Age- and sex-specific plaque volume distributions were derived from 956 patients with stable coronary artery disease.
  • External multicenter cohorts (n=1847) were used to correlate plaque percentiles with MI incidence.

Main Results:

  • Coronary plaque volumes quantified by DL increased with age and were higher in males.
  • Patients in the ≥75th percentile of total plaque volume faced significantly higher MI risk (unadjusted HR 2.65).
  • These associations remained significant in multivariable analyses, even after adjusting for clinical factors and stenosis.

Conclusions:

  • DL-based coronary plaque volume distributions, stratified by age and sex, are strong predictors of myocardial infarction.
  • Patients with high coronary plaque burden (≥75th percentile) exhibit the greatest risk for MI.