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High-Resolution Imaging of the Passive Heart and Cardiac Valves for the Next Generation Cardiac Models

EMSL Project ID


Parallel to PNNL?s successful efforts to fund a virtual lung project, we seek preliminary data in pursuit of a large-scale computational effort directed at the heart. Software tools for image segmentation, grid generation and computational physics have been applied to the lung, and refinements are currently underway for accommodating the unique mechanics of the heart. However, we require a high-resolution dataset for the heart that is capable of representing some of the finer features of cardiac anatomy that have eluded previous efforts. Necessary geometric inputs to such models are tissue boundaries and both myofiber and collagen fiber orientations. Gross geometries have, in the past, been characterized by both MRI and CT-scanning, and myofiber angles have been successfully characterized with diffusion tensor methods. Despite their intimate relationship to cardiac flows in health and disease, however, the cardiac valves have never been successfully incorporated into such models due to imaging difficulties. This is largely because the valves are poorly perfused, thin (< 250 &#61549;m) and, in the case of the atrioventricular valves, tethered to the ventricle via a complex architecture of branching chordae. Specifically, we would like to obtain a high-resolution dataset on a fixed, excised porcine heart, including the four cardiac valves and a section of the aorta. The pig heart is closest to the human heart and is considered the gold standard in heart mechanics. This effort will require some exploration of contrasting agents to highlight the valvular apparatus.

Such a dataset will help lead the way to a funded computational model of the heart with applications ranging from the planning of surgical interventions to the design of prostheses to the understanding of fatal arrhythmias and congestive heart failure.

Project Details

Project type
Capability Research
Start Date
End Date


Principal Investigator

Daniel Einstein
Pacific Northwest National Laboratory

Team Members

Kevin Minard
Pacific Northwest National Laboratory