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Related Concept Videos

Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

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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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.
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High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
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Calculation of Ejection Fraction Using Cardiac Computed Tomography: Clinical Evolution, Reliability, and

Simone Steffani1, Mariagrazia Piscione2, Dario Gaudio3

  • 1Diagnostic Imaging Department, University of Rome Tor Vergata, 00133 Rome, Italy.

Medicina (Kaunas, Lithuania)
|June 26, 2026
PubMed
Summary

Cardiac computed tomography (CCT) now accurately calculates ejection fraction (EF), offering a comprehensive 3D assessment. This advanced imaging provides valuable functional data, complementing anatomical information for cardiovascular disease management.

Keywords:
artificial intelligencecardiac computed tomographycardiac magnetic resonanceejection fractionpre-procedural planningtrans-thoracic echocardiography

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Area of Science:

  • Cardiovascular Imaging
  • Medical Technology Assessment
  • Artificial Intelligence in Medicine

Background:

  • Ejection Fraction (EF) is crucial for cardiovascular disease classification and management.
  • Trans-thoracic echocardiography (TTE) is first-line, and cardiac magnetic resonance (CMR) is the gold standard for EF assessment.
  • Cardiac computed tomography (CCT) has evolved with wide-detector scanners and AI, enabling morpho-functional analysis.

Purpose of the Study:

  • To review the literature on calculating biventricular function and EF using CCT.
  • To summarize CCT's current clinical applications, technological advancements, and diagnostic reliability compared to TTE and CMR.
  • To evaluate the role of AI in CCT-based EF determination.

Main Methods:

  • Narrative literature review across Scopus, MEDLINE, and Web of Science.
  • Focus on studies calculating biventricular function and EF using CCT.
  • Comparative analysis of CCT against TTE and CMR for diagnostic accuracy.

Main Results:

  • CCT enables simultaneous acquisition of anatomical and functional data (EDV, ESV, SV, EF) in a 'one-stop-shop' approach.
  • CCT's 3D nature overcomes TTE's geometric assumptions and artifacts, showing high volumetric concordance with CMR.
  • Limitations include radiation exposure, contrast toxicity, heart rhythm dependence, and lower temporal resolution than CMR.

Conclusions:

  • EF determination by CCT is technically mature and clinically validated.
  • CCT offers synergistic functional data when integrated with anatomical indications, complementing TTE and CMR.
  • AI integration can automate CCT workflows, potentially enabling opportunistic screening for subclinical cardiac dysfunction.