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Related Concept Videos

Atherosclerosis I: Introduction01:30

Atherosclerosis I: Introduction

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Atherosclerosis is a progressive disorder characterized by the buildup of plaques on the arterial inner wall, causing them to narrow and harden over time. These plaques comprise lipids, calcium, blood components, carbohydrates, and fibrous tissue. The process primarily affects the intima of large and medium-sized arteries, reducing blood flow in any artery.Etiology and risk factorsThe cause of atherosclerosis is multifactorial, involving a complex interplay among endothelial injury, lipid...
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Atherosclerosis III: Management01:26

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Management of atherosclerosis involves an integrated strategy encompassing pharmacological treatment, surgical interventions, lifestyle changes, and nutrition therapy to address the multifactorial nature of the disease.Pharmacological TherapyA cornerstone of atherosclerosis management is the use of pharmacological agents. Statins, such as atorvastatin, are pivotal in inhibiting HMG-CoA reductase, an enzyme that catalyzes an initial step in cholesterol synthesis in the liver. This reduction in...
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Atherosclerosis II: Clinical Manifestations and Diagnostic Tests01:27

Atherosclerosis II: Clinical Manifestations and Diagnostic Tests

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Atherosclerosis is a progressive disorder that leads to the thickening and narrowing of arterial walls due to plaque buildup. This condition can cause various symptoms depending on the arteries affected:Coronary Artery Disease (CAD): This condition affects the coronary arteries and may lead to chest pain (angina), shortness of breath (dyspnea), heart attacks, and other heart disease symptoms.Cerebrovascular Disease: This affects blood flow to the brain, causing transient ischemic attacks (TIAs)...
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Related Experiment Video

Updated: Apr 29, 2026

Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
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A multiscale approach for modeling atherosclerosis progression.

Konstantinos P Exarchos, Clara Carpegianni, Georgios Rigas

    IEEE Journal of Biomedical and Health Informatics
    |May 20, 2014
    PubMed
    Summary
    This summary is machine-generated.

    This study models coronary atherosclerosis (ATS) progression using patient data. Diabetes, cholesterol, and CD11b marker are key predictors of disease advancement.

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    Area of Science:

    • Cardiovascular research
    • Biomedical data analysis
    • Medical imaging analysis

    Background:

    • Atherosclerosis (ATS) progression, driven by arterial fatty deposits, causes significant cardiovascular complications.
    • Accurate modeling of ATS progression is crucial for effective patient management and intervention.
    • Heterogeneous patient data, including medical records and biochemical markers, offer potential for improved ATS modeling.

    Purpose of the Study:

    • To develop and evaluate models for predicting coronary atherosclerosis (ATS) progression.
    • To analyze the influence of various patient data types on ATS development.
    • To identify key clinical and molecular markers associated with coronary plaque progression.

    Main Methods:

    • Utilized a dataset of 39 patients with serial coronary computed tomography angiographies.
    • Employed a twofold approach: baseline analysis for future state prediction and temporal analysis using dynamic Bayesian networks.
    • Incorporated patient medical records, biochemical analytes, monocyte information, adhesion molecules, and therapy data.

    Main Results:

    • Achieved 93.3% accuracy in predicting ATS progression using baseline analysis.
    • Attained 83% overall accuracy in modeling ATS evolvement with temporal analysis.
    • Identified diabetes, cholesterol, and cholesterol/HDL ratio as prominent risk factors. The CD11b marker was associated with coronary plaque progression.

    Conclusions:

    • The developed models demonstrate high accuracy in predicting and modeling coronary atherosclerosis (ATS) progression.
    • Baseline and temporal analyses provide valuable insights into the dynamics of ATS.
    • Key factors like diabetes, cholesterol levels, and the CD11b marker are critical for understanding and managing ATS progression.