SBIR Phase I: Use of Automated Multiparametric Strain Analysis Technology (MPS) as a Diagnostic Test for Heart Disease
National Science Foundation
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Small Business Information
535 W Research Center Blvd, Suite 135, M/S 2300, Fayetteville, AR, 72701-6948
Socially and Economically Disadvantaged:
AbstractThis Small Business Innovation Research (SBIR) Phase I project proposes to develop in-clinic proof of concept for fully automated cardiac multiparametric strain analysis (MPS) technology capable of identifying left ventricular (LV) contractile injury. The innovation in this technology is centered not in MRI tissue tagging (which has been clinically available for decades), but rather in the post-processing cardiac MRI files. Post-processing analysis of cardiac MRI tissue-tagging displacement information is based upon the comparison of three systolic strain components to the normal average and standard deviation established in our normal human strain database. The strain values are "normalized" and combined into novel and powerful multiparametric strain indices. Because cardiac MRI can capture transmural and not just wall contractility over the course of a cardiac cycle, MPS post processing can identify the erratically functioning loci through the ventricular wall. The broader impact/commercial potential of this project is the development and commercialization of a reliable metric that provides insight into accurate timing of surgery. Many heart failure programs have adopted a very low threshold for early highly invasive intervention. The associated yearly cost of caring for heart patients has risen above $300 billion. Heart failure is currently the most rapidly increasing clinical manifestation of cardiac disease in the United States. A better understanding and the ability to monitor contractile injury distribution over time could lead to more precise surgical referral. This would represent a major improvement in diagnostic and therapeutic heart failure care and have the potential to profoundly impact U.S. health care.
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