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Personalized Computational Models of the Heart for Cardiac Resynchronization Therapy

Abstract : Cardiovascular diseases (CVD) are the major cause of morbidity and mortality in the western world. Within CVD, the increasing prevalence of congestive heart failure (CHF) is mainly caused by the steadily increasing number of heart attack survivors. They suffer an important scar burden on their cardiac function due to the infarction. Moreover, CHF has a terrible prognosis with 50% mortality in the first 3 years after diagnosis. Of all CHF patients, those with an additional dyssynchronous contraction have the worst prognosis. Cardiac resynchronization therapy (CRT) involves placing a pacemaker to improve the synchronicity of cardiac contraction. It has recently been shown to be an effective method of treating patients with dyssynchronous CHF, inducing significant reductions in morbidity and mortality in large clinical trials. However, clinical trials have also demonstrated that up to 30% of patients may be classified as nonresponders. There remains major controversy surrounding patient selection and optimization of this expensive treatment (e.g., lead positioning, pacemaker setting). For instance, recent studies showed that patients with heart failure and narrow QRS intervals do not currently benefit from CRT (RethinQ, [3]) and that no single echocardiographic measure of dyssynchrony may be recommended to improve patient selection (PROSPECT, [10]). Therefore, new approaches are needed in order to provide a better diagnosis and characterization of patients while achieving a better planning and delivery of the therapy.
Mots-clés : Life Sciences
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Submitted on : Friday, August 19, 2011 - 7:25:00 PM
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Maxime Sermesant, Reza Razavi. Personalized Computational Models of the Heart for Cardiac Resynchronization Therapy. Kerckhoffs, Roy C.P. Patient-Specific Modeling of the Cardiovascular System, Springer New York, pp.167-182, 2010, 978-1-4419-6691-9. ⟨10.1007/978-1-4419-6691-9_10⟩. ⟨inria-00616112⟩



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