Computational Heart Modeling
Computational Heart Modeling - Related Videos
12:09
Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
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Cited by 14 •
2013
A methodology to estimate ventricular fiber orientations from in vivo images of patient heart geometries for personalized modeling is described. Validation of the methodology performed using normal and failing canine hearts demonstrate that that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.
07:59
The Inverted Heart Model for Interstitial Transudate Collection from the Isolated Rat Heart
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2017
This protocol describes a method to collect cardiac interstitial fluid from the isolated, perfused rat heart. To physically separate interstitial transudate from coronary venous effluent perfusate, the Langendorff perfused heart is inverted, and the transudate (interstitial fluid) formed on the cardiac surface is collected using a soft latex cap.
09:45
An Isolated Working Heart System for Large Animal Models
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Cited by 22 •
2014
Most studies involving the Langendorff apparatus use small animal models due to the increased complexity of systems for larger mammals. We describe a Langendorff system for large animal models that allows for use across a range of species, including humans, and relatively easy data acquisition.
06:08
Apical Resection Mouse Model to Study Early Mammalian Heart Regeneration
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Cited by 12 •
2016
A step-by-step video protocol of apical resection is demonstrated in this study. Apical resection is a recently highlighted surgical approach in mammalian heart regeneration research. This study may promote the application of apical resection as a standard methodology in research into the mechanism underlying heart regeneration.
06:52
A Standardized Pig to Macaque Heterotopic Heart Xenotransplantation Model
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Cited by 1 •
2025
This study presents a pre-clinical heterotopic abdominal heart xenotransplantation model using α-Gal knockout (GTKO) pigs and macaques. The model incorporates optimized recipient selection, vascular anastomosis techniques, and perioperative management strategies. It is suitable for evaluating novel immunosuppressive agents and provides a convenient platform for advancing heart xenotransplantation.
FAQs
Computational heart modeling can represent electrical activity, mechanical contraction, and blood flow within a common simulation framework. By tracking how these processes change over time, the model shows how altered tissue behavior may influence cardiac function and circulation. This integrated view helps investigators examine arrhythmias and other functional changes without isolating each process from the others.
Anatomical information, cardiac imaging, and pressure or flow measurements provide the measurable inputs needed to construct a more relevant representation of an individual heart. Combining these sources with physiological principles connects patient features to predicted cardiovascular outcomes. That connection supports individualized analysis when researchers evaluate interventions or examine how disease-related changes may affect cardiac function.
Numerical methods allow computational representations to predict how heart tissue and blood respond as time progresses. They make it possible to examine electrical activity, contraction, and flow under selected conditions rather than relying only on static measurements. The resulting time-dependent predictions help investigators study changing cardiac behavior and compare possible outcomes across scenarios.
These models provide a way to investigate cardiac function, arrhythmias, and disease progression through simulations while reducing reliance on experimental testing alone. Researchers can explore predicted responses under different conditions before interpreting or pursuing further experimental work. This complementary role is valuable when direct testing cannot capture every combination of patient features, disease states, or intervention conditions.
A study begins by combining physiological principles with information such as cardiac anatomy, imaging, and pressure or flow measurements. Researchers then use numerical methods to represent activity, contraction, or circulation and predict responses over time. Comparing simulations across different conditions can reveal possible changes in function, disease progression, or cardiovascular outcomes.
Bioengineers can use these simulations to examine how a medical device may relate to cardiac function and blood flow under selected conditions. Modeling offers a way to connect device evaluation with predicted cardiovascular outcomes before relying exclusively on experimental testing. The approach also supports therapy development by showing how measurable features may relate to responses.
Patient-specific anatomy, imaging, and pressure or flow measurements can be linked with physiological principles to generate predictions tailored to measurable features. Those predictions may help guide personalized interventions by indicating how cardiovascular behavior could change under different conditions. In bioengineering research, this connection also supports development of therapies aimed at cardiac function, arrhythmias, or disease progression.