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Related Experiment Video

Updated: Jun 22, 2026

Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography

Morphological and Functional Assessment of the Right Ventricle Using 3D Echocardiography

Published on: October 28, 2020

Serial assessment of ventricular morphology and function.

Frank Grothues¹, Ruediger Braun-Dullaeus

¹Department of Cardiology, Otto-von-Guericke-University, Magdeburg, Germany. frank.grothues@med.ovgu.de

Heart Failure Clinics

|July 1, 2009

Summary

Cardiovascular magnetic resonance (CMR) provides accurate measurements of heart function and mass. This imaging technique is crucial for assessing heart failure, guiding treatment decisions, and evaluating patient prognosis and cardiac remodeling.

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Last Updated: Jun 22, 2026

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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

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Published on: July 20, 2022

Area of Science:

Cardiology
Medical Imaging
Biomedical Engineering

Background:

Cardiovascular magnetic resonance (CMR) is a validated imaging technique.
Accurate measurement of cardiac function is essential for patient management.

Purpose of the Study:

To highlight the utility of CMR in assessing cardiac function and guiding heart failure management.
To emphasize CMR's role in prognosis estimation and remodeling research.

Main Methods:

Utilizes cardiovascular magnetic resonance (CMR) for imaging.
Measures left and right ventricular volumes, function, and mass.

Main Results:

CMR offers accurate and reproducible measurements of cardiac parameters.
Ventricular ejection fraction measurements guide therapeutic decisions.
CMR parameters correlate with morbidity and mortality, aiding prognosis.

Conclusions:

CMR is ideal for initial assessment and longitudinal follow-up in heart failure.
CMR enables confident therapeutic decisions based on ejection fraction.
CMR is a leading imaging technique for remodeling research due to its accuracy and ability to assess changes with small sample sizes.