Heart failure is a major cause of morbidity and mortality, contributing significantly to global health expenditure. Heart failure patients often exhibit contractile dyssynchrony, which diminishes cardiac systolic function. Cardiac resynchronization therapy (CRT) employs bi-ventricular pacing to re-coordinate the contraction of the heart. CRT has been shown to improve heart failure symptoms and reduce hospitalization, yet approximately 30% of patients fail to respond to the therapy. There is an urgent need for new robust diagnostic approaches that improve the efficacy of the therapy. The long-tem objective of this project is to develop, test, and validate a new methodology for the guidance of the clinical procedure of CRT. As a first step in this direction, the objective of this Phase I project by CardioSolv, LLC is to explore the feasibility of the development of an automated high-throughput pipeline for patient-specific electromechanical heart model generation. The pipeline will combine sophisticated image-processing of patient magnetic resonance images pre-CRT, as well as computational-anatomy and mesh-generation tools. Accordingly, the project proposes to 1) Develop fully and customize all software tools needed for MRI-based cardiac electromechanical models assembly. 2) Assess the technical feasibility of assembling an automated pipeline for rapid patient-specific cardiac electromechanical model construction that integrates all elements developed and customized under Specific Aim #1. In stages of the project beyond Phase I, validated multiscale cardiac electromechanics simulation approaches will be developed based on this pipeline, to evaluate the optimal patient-specific locations for bi-ventricular endo- or epicardial pacing and thus to increase the efficacy in the delivery of CRT therapy. Successful execution of the proposed studies will constitute a major step towards optimizing CRT as well as towards the integration of computational modeling in the diagnosis and treatment of cardiac disease, and in patient care in general. This is the second SBIR project by CardioSolv LLC, a new biotech start-up company specializing in predictive cardiac modeling and simulation. CardioSolv's goal is to be the world leader in software development for cardiac electrophysiological and electromechanical applications for biomedical technology companies, for clinical cardiology, and for the academic research community.

Public Health Relevance

Cardiac resynchronization therapy (CRT) employs bi-ventricular pacing to re-coordinate the contraction of the heart, yet approximately 30% of patients fail to respond to the therapy. In the current environment which emphasizes reducing health care costs and optimizing therapy, robust diagnostic approaches to optimize CRT would have a dramatic personal, medical and economic impact. The proposed project offers to build an automated pipeline for patient-specific MRI-based generation of an electromechnical model of the heart that can be used to non-invasively predict the optimal CRT therapy for the patient.

National Institute of Health (NIH)
National Center for Advancing Translational Sciences (NCATS)
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
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Special Emphasis Panel (ZRG1-CVRS-B (10))
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Sawczuk, Andrea
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Cardiosolv, LLC
United States
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