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

206
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...
206
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

310
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...
310
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

426
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...
426

You might also read

Related Articles

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

Sort by
Same author

Many excellent and one bad news regarding the European Journal of Translational Myology and the 2027 Padua Days on Muscle and Mobility Medicine.

European journal of translational myology·2026
Same author

Association of trabecular texture and paraspinal muscle characteristics with prevalent vertebral fractures - QCT results from a subcohort of the AGES population.

BMC musculoskeletal disorders·2026
Same author

Changes in DNA methylation-based aging predicts brain damage and dementia and reflects life-course cardiovascular risk.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Plasma GDF15 affects long-term dementia risk and alters neuroimmune signaling.

Science advances·2026
Same author

Analyzing Gait Pattern Associated With Neuropsychiatric Symptoms in Parkinson's Disease by a Comprehensive Approach.

IEEE journal of translational engineering in health and medicine·2026
Same author

Identification and characterization of a Fibrillin-1 derived matrikine for cardiac regeneration and repair.

Biomaterials·2026

Related Experiment Video

Updated: Dec 28, 2025

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection
06:57

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection

Published on: September 22, 2023

1.4K

Assessing cardiovascular risks from a mid-thigh CT image: a tree-based machine learning approach using

Carlo Ricciardi1,2, Kyle J Edmunds1, Marco Recenti1

  • 1Institute for Biomedical and Neural Engineering, Reykjavík University, Reykjavík, Iceland.

Scientific Reports
|February 20, 2020
PubMed
Summary

This study introduces a new method using CT scans to predict heart disease in older adults. The nonlinear trimodal regression analysis (NTRA) effectively identified cardiovascular disease and chronic heart failure with high accuracy.

More Related Videos

Author Spotlight: Enhanced Quantification of Cardiovascular Calcification Progression for Longitudinal Micro PET/CT Studies in Small Research Animals
08:02

Author Spotlight: Enhanced Quantification of Cardiovascular Calcification Progression for Longitudinal Micro PET/CT Studies in Small Research Animals

Published on: November 15, 2024

900
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.3K

Related Experiment Videos

Last Updated: Dec 28, 2025

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection
06:57

Author Spotlight: Advancing Cardiovascular Imaging - Introducing the Spatially Weighted Calcium Score for Early Disease Detection

Published on: September 22, 2023

1.4K
Author Spotlight: Enhanced Quantification of Cardiovascular Calcification Progression for Longitudinal Micro PET/CT Studies in Small Research Animals
08:02

Author Spotlight: Enhanced Quantification of Cardiovascular Calcification Progression for Longitudinal Micro PET/CT Studies in Small Research Animals

Published on: November 15, 2024

900
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

43.3K

Area of Science:

  • Radiology and Medical Imaging
  • Cardiovascular Health
  • Biostatistics and Machine Learning

Background:

  • Nonlinear trimodal regression analysis (NTRA) was previously used for lower extremity function and nutrition in aging. Its application in cardiovascular health prediction remained unexplored.
  • Accurate, non-invasive methods are needed to assess cardiovascular health in aging populations.

Purpose of the Study:

  • To evaluate NTRA parameters for classifying elderly individuals with coronary heart disease (CHD), cardiovascular disease (CVD), and chronic heart failure (CHF).
  • To develop predictive models for cardiovascular health outcomes using machine learning algorithms.

Main Methods:

  • Employed NTRA parameters derived from radiodensitometric CT distributions.
  • Utilized multivariate logistic regression and three tree-based machine learning algorithms (including random forests) for classification.
  • Assessed predictive utility using CHF incidence data and analyzed classification by tissue type, feature importance, and age.

Main Results:

  • Random forests algorithm demonstrated the highest classification performance across all analyses.
  • Achieved excellent overall classification scores: CHD (AUCROC: 0.936), CVD (AUCROC: 0.914), and CHF (AUCROC: 0.994).
  • Longitudinal modeling for CHF incidence prediction was robust (AUCROC: 0.993).

Conclusions:

  • NTRA parameters, analyzed with machine learning, provide a powerful tool for non-invasive cardiovascular health assessment in the elderly.
  • This approach effectively links changes in adipose, loose connective, and lean tissues to cardiovascular outcomes.
  • Introduces a standardized method for predicting heart disease risk and outcomes in aging individuals.