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Related Concept Videos

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 V: CT01:28

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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 I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

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Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...
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Imaging Studies for Cardiovascular System IV: CMRI01:21

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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 II:Types of Echocardiography01:20

Imaging Studies for Cardiovascular System II:Types of Echocardiography

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Echocardiography plays a role in assessing cardiac health and detecting heart conditions, with various types providing critical insights for diagnosis and treatment.
Types of Echocardiography
Transthoracic Echocardiography (TTE)
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Imaging Studies for Cardiovascular System III: X-Ray01:20

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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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Updated: Sep 9, 2025

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PRIME 2.0: Proposed Requirements for Cardiovascular Imaging-Related Multimodal-AI Evaluation: An Updated Checklist.

Nobuyuki Kagiyama1, Márton Tokodi2, Quincy A Hathaway3

  • 1Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan; AI Incubation Farm, Juntendo University Faculty of Medicine, Tokyo, Japan.

JACC. Cardiovascular Imaging
|September 2, 2025
PubMed
Summary
This summary is machine-generated.

The PRIME 2.0 checklist offers updated guidance for developing and reporting artificial intelligence (AI) in cardiovascular imaging. This framework addresses new AI technologies like deep learning and large language models for better research transparency.

Keywords:
PRIME 2.0 checklistartificial intelligencecardiovascular imagingclinical validationdeep learninglarge language modelsmodel developmentmultimodal generative artificial intelligencetransparency and reproducibility

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Area of Science:

  • Cardiovascular Imaging
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Rapid advancements in artificial intelligence (AI), including deep learning and large language models, necessitate updated reporting standards for AI applications in cardiovascular imaging.
  • Existing general AI reporting guidelines lack the specificity required for complex cardiovascular imaging research.
  • The original PRIME checklist provided a foundational framework, but requires enhancement to address current AI technologies and domain-specific challenges.

Purpose of the Study:

  • To present the updated PRIME 2.0 checklist, a domain-specific framework for standardizing the development, evaluation, and reporting of AI in cardiovascular imaging.
  • To incorporate recent AI advancements, such as deep learning and generative AI, into reporting guidelines.
  • To provide practical recommendations tailored to the unique complexities of cardiovascular imaging, including motion, artifacts, and variability.

Main Methods:

  • Development of the PRIME 2.0 checklist involved a modified Delphi process.
  • An international panel of clinical and technical experts contributed to the checklist's refinement.
  • The framework builds upon the original seven-domain structure, integrating cardiovascular imaging-specific considerations.

Main Results:

  • The PRIME 2.0 checklist offers detailed, practical recommendations for AI research in cardiovascular imaging.
  • It addresses critical aspects of AI development, evaluation, and reporting, moving beyond general guidelines.
  • The checklist incorporates specific challenges like cardiac motion, imaging artifacts, and inter-observer variability.

Conclusions:

  • PRIME 2.0 enhances transparency and rigor in AI research within cardiovascular imaging.
  • It serves as a vital resource for researchers, clinicians, peer reviewers, and editors.
  • Adoption of PRIME 2.0 can improve the quality and reliability of AI applications in the field.