Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

286
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...
286
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

466
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...
466
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

399
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...
399

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Premature stopping of LEIA-HF: protecting trial participants while preserving clinical knowledge.

ESC heart failure·2026
Same author

Letter to the editor: acute heart failure diagnosis and vasodilator use in a nationwide registry study.

European heart journal. Acute cardiovascular care·2026
Same author

Glucocorticoids for Patients With Acute Decompensated Heart Failure: A Protocol for a Systematic Review With Meta-Analysis and Trial Sequential Analysis.

Acta anaesthesiologica Scandinavica·2026
Same author

Restrictive versus liberal oxygenation targets in patients with acute heart failure and pulmonary congestion-A protocol for a Randomized Controlled Trial (The REDOX-AHF trial).

PloS one·2026
Same author

Artificial intelligence for detecting acute heart failure on chest CT: prospective clinical proof-of-concept validation.

European radiology experimental·2026
Same author

Secondary Mitral and Tricuspid Regurgitation in Early HFrEF: The Impact of Contemporary Medical Therapy.

European journal of heart failure·2026
Same journal

A Stepped Care, Peer-Delivered Intervention to Improve Substance Use and HIV Medication Adherence in Primary Care in South Africa (Project <i>Khanya</i>): Protocol for a Hybrid Type 2 Effectiveness-Implementation Randomized Controlled Trial.

JMIR research protocols·2026
Same journal

Optimizing Engagement with Digital Mental Health Resources Among Sexual and Gender Minority Users: Protocol for a Series of Microrandomized Trials.

JMIR research protocols·2026
Same journal

Correction: HealthData@MAD-R&I: Protocol for Design and Development of a Regional Health Data Infrastructure to Enable Secondary Use of Health Data in Research and Innovation.

JMIR research protocols·2026
Same journal

A Clinician-Supported Mobile App to Reduce Mental Health Symptoms Among World Trade Center Responders in Florida: Protocol for a Randomized Controlled Trial.

JMIR research protocols·2026
Same journal

Emergency Department-Initiated Hospice and Palliative Care Consultation Among Older Adults: Protocol for a Systematic Review and Meta-Analysis.

JMIR research protocols·2026
Same journal

The South Texas Oral Health Network Study of Practitioners' Approaches to Oral Appliance Therapy Titration for Obstructive Sleep Apnea and Their Impact on Patient Outcomes (PAOSA): Protocol for a Prospective Observational Study.

JMIR research protocols·2026
See all related articles

Related Experiment Video

Updated: Jan 17, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.7K

AI-Based Algorithm to Detect Heart and Lung Disease From Acute Chest Computed Tomography Scans: Protocol for an

Anne Sophie Overgaard Olesen1, Kristina Miger1, Silas Nyboe Ørting2

  • 1Department of Cardiology, Bispebjerg Hospital, Copenhagen, Denmark.

JMIR Research Protocols
|September 19, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) algorithms are being developed to analyze chest CT scans for conditions like cardiac decompensation. This aims to speed up diagnosis for patients experiencing shortness of breath (dyspnea).

Keywords:
AIacute careartificial intelligencecardiac decompensationcomputed tomographydiagnostic imagingdyspneamachine learning

More Related Videos

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

1.1K
Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
04:40

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Published on: August 28, 2018

15.9K

Related Experiment Videos

Last Updated: Jan 17, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.7K
Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

1.1K
Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
04:40

Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans

Published on: August 28, 2018

15.9K

Area of Science:

  • Medical Imaging Analysis
  • Artificial Intelligence in Healthcare
  • Diagnostic Tools

Background:

  • Dyspnea is a common hospitalization reason in older adults, often challenging to diagnose.
  • Chest computed tomography (CT) offers better accuracy than radiographs but faces radiologist shortages.
  • AI can potentially automate CT scan analysis to aid diagnosis.

Purpose of the Study:

  • To develop and validate AI algorithms for automatic analysis of acute chest CT scans.
  • To provide immediate feedback on the likelihood of pneumonia, pulmonary embolism, and cardiac decompensation.
  • Focus on developing AI for cardiac decompensation detection.

Main Methods:

  • Retrospective study using 4672 acute chest CT scans (2016-2021).
  • Random split into training (2/3) and internal validation (1/3) sets.
  • AI development involves cross-validation; validation uses radiological reports as ground truth.

Main Results:

  • CT data extraction completed; algorithm development ongoing.
  • AI algorithm development for pulmonary congestion is complete.
  • Internal and external validation planned, with results expected in 2026.

Conclusions:

  • AI-driven insights from CT scans are expected to improve clinical decision-making.
  • Immediate feedback will benefit clinicians and patients with dyspnea.
  • Potential to address diagnostic challenges in older adults with multiple conditions.