Cardiac Mri Correlation
Cardiac Mri Correlation - Related Videos
01:25
Correlation between ECG and Cardiac Cycle
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2025
The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle. A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
08:41
Assessment of Cardiac Function and Myocardial Morphology Using Small Animal Look-locker Inversion Recovery (SALLI) MRI in Rats
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Cited by 2 •
2013
Contrast enhanced cardiac magnetic resonance (CMR) imaging allows comprehensive in vivo assessment of the heart in small animal models of cardiovascular disease. Here we detail the procedures to perform CMR imaging, reconstruction and analysis using Small Animal Lock-Locker Inversion Recovery (SALLI) in rats.
11:55
Physiological Correlates of Emotion Recognition
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2023
Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel—University of Southern California The autonomic nervous system (ANS) controls the activity of the body's internal organs and regulates changes in their activity depending on the current environment. The vagus nerve, which innervates many of the internal organs, is an important part of the system. When our brain senses danger, vagal tone is inhibited, leading to a set of changes in the body designed to make us more prepared to fight or...
02:20
Correlations
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2020
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
11:37
Cardiac Magnetic Resonance Imaging
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2023
Source: Frederick W. Damen and Craig J. Goergen, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana In this video, high field, small-bore magnetic resonance imaging (MRI) with physiological monitoring is demonstrated to acquire gated cine loops of the murine cardiovascular system. This procedure provides a basis for assessing left-ventricular function, visualizing vascular networks, and quantifying motion of organs due to respiration. Comparable small animal...
FAQs
Cine MRI captures changing cardiac structure and motion, while tissue characterization adds information about myocardial properties. Linking these outputs with ventricular volume, wall motion, strain, or pressure allows models to test whether imaging-derived features track measurable cardiac performance. This relationship can reveal which biomarkers best represent mechanics for bioengineering analyses.
Image segmentation separates relevant cardiac structures so measurements can be assigned to specific regions or chambers. Quantitative feature extraction then converts the images into variables such as volume, wall motion, or strain. These standardized measurements make it possible to compare imaging results with physiological, clinical, or bioengineering data through formal analyses.
Statistical and computational models evaluate relationships between MRI-derived measurements and external cardiac data. They help determine whether observed imaging features correspond to pressure, motion, strain, or other indicators of performance. In bioengineering, these analyses support validation of imaging biomarkers and provide quantitative evidence for interpreting cardiac mechanics and remodeling.
Pressure measurements provide a physiological reference that complements image-based observations. Comparing pressure with ventricular volume, wall motion, or strain can show how visible structural or functional changes relate to cardiac performance. This combined view helps connect noninvasive imaging measurements with measurable tissue behavior rather than interpreting MRI features in isolation.
A typical workflow begins by obtaining cine MRI and tissue-characterization measurements, followed by image segmentation and quantitative feature extraction. The resulting variables are paired with physiological, clinical, or bioengineering data, such as ventricular volume, strain, wall motion, or pressure. Statistical or computational models then evaluate the relationships and their relevance to cardiac performance.
This approach can validate imaging biomarkers, assess cardiac mechanics, and characterize disease-related remodeling. It also supports research that connects observed heart structure and function with measurable tissue behavior. These applications are relevant to diagnosis, treatment planning, and the development of predictive cardiovascular models, particularly when noninvasive measurements need physiological or engineering context.
Correlated MRI measurements provide quantitative information about an individual heart’s structure and function. Incorporating ventricular volume, wall motion, strain, tissue characterization, or pressure relationships can improve patient-specific simulations by grounding them in measured cardiac behavior. The same evidence can inform bioengineering evaluations of device designs intended to interact with or support the heart.