Contractile dyssynchrony diminishes systolic function and is a major independent risk factor for worsening heart failure. Cardiac resynchronization therapy (CRT) is a new treatment that involves electrical pre-excitation of the ventricles to recoordinate contraction. Clear identification of patients with ventricular and electrical dyssynchrony is central to targeting patients who are most likely to benefit from CRT. In current practice, widening of the QRS duration is primarily used to identify patients with dyssynchrony who would be candidates for CRT. While non-invasive and convenient, QRS duration and even direct measures of intraventricular electrical delay are only weakly correlated with acute CRT response, and have had little to no predictive value for chronic CRT efficacy. In light of the complexity and health care cost to implement CRT, a noninvasive method to predict responders is highly desirable. We hypothesize that direct image based measurements of mechanical dyssynchrony using magnetic resonance imaging (MRI), regional strain analysis and complete electrical mapping data will allow for the study of the complex relationship between electrical conduction delay and mechanical activation and improve the selection process for CRT candidates. In this project, we use a unique 4D electromechanical imaging and mapping system to address several unanswered and untested mechanistic and practical questions in CRT therapy.
In Aim 1 of this project we will test how patho-physiological properties of the failing heart, such as chamber remodeling, cardio-depression, right-heart/septal loading, and myocardial conduction velocity, influence the relationship between conduction delay and mechanical dyssynchrony.
In Aim 2 we seek to understand how we can optimize CRT efficacy by factors such as site selection and field versus point stimulation.
In Aim 3 we will develop a multivariate prognostic model to identify the extent of mechanical dyssynchrony and responsiveness to resynchronization. This will be derived from magnetic resonance data but focusing on measures that can be derived using other non-invasive methods (echo-Doppler) as well. These studies should provide important elucidation of the mechanisms by which electrical conduction delay alters mechanical dyssynchrony, facilitate the design of optimal pacing algorithms and treatment delivery, and enhance the accuracy of identifying likely responders to CRT therapy.
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