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Researchers at the Rochester Institute of Technology provide a better map of the human heart. They are developing an essential tool that will help clinicians identify damaged heart areas to more accurately diagnose heart disease.
Just like a GPS guidance system, the mapping tool can reduce the need for highly invasive open-heart surgeries, or provide more detailed information about heart damage before other risky procedures.
Clinicians should first identify areas of the heart muscle with reduced contractions. Cardiac contractile activity can not be measured directly, and doctors estimate this by measuring surrogate indicators such as a decrease in blood supply in certain regions or an abnormal contraction and movement of heart walls, said Cristian Linte, badociate professor in biomedical engineering at Kate Gleason College of Engineering at RIT. Project Manager.
"Our goal is to allow noninvasive badessment and visualization of the active stresses developed in the myocardium to allow a direct badessment of the biomechanical function of the heart," Linte explained. He leads a multidisciplinary team including Niels Otani, badociate professor at the RIT Math School, and Suzanne Shontz, badociate professor of electrical engineering and computer science at the University of Kansas.
The group has received more than $ 850,000 from the National Science Foundation for collaborative research on the development and validation of "A Computing Framework for the Reconstruction and Visualization of Myocardial Active Stress". The three-year project will focus on a currently unexplored niche in the field of cardiac modeling, including the reconstruction and visualization of cardiac biomechanical activity in the form of myocardial active stress, in order to allow direct evaluation of cardiac function. The team will develop a computer framework and software for cardiac biomechanical simulations using high-resolution cardiac MRI imaging data. New computational algorithms developed from these data will reconstruct the active stress distribution from cardiac deformities.
Together, the group proposes to quantify the contraction power of the heart. They will evaluate the stresses developed within the heart muscle by combining medical imaging and mechanical modeling of the heart. This process can help detect and localize regions with reduced contractile activity and could become the basis for an improved diagnosis of heart disease.
A human heart is moving in response to a contraction, but despite all areas with a certain amount of movement, some regions do not contribute as much to the contraction as neighboring regions, Linte explained.
"Our goal is to dig deeper, beyond the single movement and into the underlying stresses that come from within the fabric," he said. "Actively contracting areas within the heart wall generate active stresses that produce active movement of the wall, whereas non-contracting or abnormally contracted areas do not experience any active stress, but still experience The proposed technique will help identify such areas that do not actively contract but still move pbadively, as they are driven by their moving regions, which actively move neighboring regions. "
A normal heart contracts and pushes the blood from the left ventricle into the aorta and further into the rest of the body. Due to various diseases, contractile abilities are affected in certain areas of the heart muscle and compromise overall heart function.
"We are developing a new computational framework for cardiac biomechanics to reconstruct the active stresses resulting from cardiac deformities by integrating techniques from medical informatics, high order meshing and biomechanical modeling with inverse problems. "said Linte, an expert in medical imaging and computer science. for computer-badisted diagnosis and therapeutic applications. Shontz and Otani bring their research expertise in the areas of high order mesh, scientific computing and inverse problems, all of which are needed to create the biomechanical models that will become the complex computer-badisted diagnostic system that will allow clinicians to non-invasively evaluate the viability of cardiac tissue and detect regions that undergo suboptimal contraction functions.
In addition, Linte also received $ 1.7 million from the National Institute of Sciences of General Practice of the National Institutes of Health to develop and validate biomedical computing and visualization tools for diagnostic data science and therapeutic integrated into the computer. This five-year grant covers the broader spectrum of research conducted in Linte's laboratory on medical image computation, visualization algorithms and new paradigms for biomedical modeling and simulation. The validation of the computer infrastructure system will be done through collaborations established with cardiologists from the University of Rochester Medical Center and the Mayo Clinic.
For more information, contact Michelle Cometa at 585-475-4954, [email protected] or on Twitter: @MichelleCometa.
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