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Related Concept Videos

Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

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Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
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Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

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Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
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Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

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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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Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

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The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
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Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
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Artificial Intelligence in Intracoronary Imaging.

Russell Fedewa1, Rishi Puri2, Eitan Fleischman3

  • 1Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH, 44195, USA.

Current Cardiology Reports
|May 31, 2020
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances intracoronary imaging for better diagnosis and prediction of cardiac events. Further development requires large datasets to advance AI in treating coronary heart disease.

Keywords:
Artificial intelligenceDeep learningIVUSImagingMachine learningOCT

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Digitized medical imaging and data analytics enable AI applications in healthcare.
  • AI integration into intracoronary imaging aims to improve patient outcomes and reduce costs.

Purpose of the Study:

  • To investigate current applications of artificial intelligence (AI) in intracoronary imaging.
  • To explore the future potential of AI in enhancing the diagnosis and treatment of coronary heart disease.

Main Methods:

  • Review of AI applications in intravascular ultrasound (IVUS) and intravascular optical coherence tomography (IVOCT).
  • Analysis of machine learning algorithms for image segmentation, plaque analysis, and stent evaluation.
  • Assessment of AI's role in predicting future coronary events using diverse patient data.

Main Results:

  • AI applications in IVUS and IVOСT show improvements in image segmentation, plaque analysis, and stent evaluation.
  • Machine learning algorithms demonstrate potential in predicting cardiac events using imaging, clinical, and demographic data.
  • AI has shown early success in improving the prediction of cardiac events.

Conclusions:

  • AI in intracoronary imaging offers significant promise for understanding and treating coronary heart disease.
  • AI can enhance diagnostic accuracy and treatment strategies for cardiovascular conditions.
  • Development of large, curated datasets is crucial for advancing AI in this field.