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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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Computed Tomography01:10

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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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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Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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Related Experiment Video

Updated: Jan 5, 2026

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
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Published on: February 21, 2025

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Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications.

Frederic Commandeur1, Markus Goeller1,2, Damini Dey1

  • 1Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, S. Mark Taper Building, California, Los Angeles 90048, USA.

Current Cardiovascular Imaging Reports
|October 29, 2019
PubMed
Summary

Recent advances in multidetector row computed tomography (CT) enhance cardiovascular imaging. Improved CT hardware, software, and machine learning applications offer better noninvasive heart and coronary artery assessment.

Keywords:
Coronary CT angiographyCoronary calcium scoringCoronary plaqueDetectorsEpicardial adipose tissueMachine learningNoninvasive fractional flow reserve

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Area of Science:

  • Cardiovascular Imaging
  • Medical Technology
  • Artificial Intelligence in Medicine

Background:

  • Multidetector row computed tomography (CT) provides noninvasive visualization of cardiac structures and coronary arteries.
  • Technological progress in CT imaging is crucial for advancing cardiovascular diagnostics.

Purpose of the Study:

  • To review recent technological advancements in CT hardware and software.
  • To summarize the application of machine learning in cardiovascular CT imaging.

Main Methods:

  • Review of recent literature on CT hardware and software innovations.
  • Analysis of machine learning algorithms applied to cardiovascular CT data.

Main Results:

  • Enhanced CT hardware offers faster gantry rotation, improved temporal and spatial resolution, and wider patient coverage.
  • Software advancements enable noninvasive fractional flow reserve (FFR) measurement, coronary plaque characterization, and cardiac adipose tissue analysis.
  • Machine learning in cardiac CT improves risk prediction and identification of lesion-specific ischemia.

Conclusions:

  • Current CT technology has significantly broadened its clinical use in cardiovascular imaging.
  • Future developments in CT hardware, software, and machine learning are expected to further integrate into routine clinical practice for improved patient outcomes.