Personalized Computer Simulation of Diastolic Function in Heart Failure
- Author:
Amr ALI
1
;
Kayvanpour ELHAM
;
Sedaghat-Hamedani FARBOD
;
Passerini TIZIANO
;
Mihalef VIOREL
;
Lai Alan E
;
Neumann Dominik F
;
Georgescu Bogdan G
;
Buss SEBASTIAN
;
Mereles DERLIZ
;
Zitron Edgar H
;
Posch E ANDREAS
;
Rstle Wu MAXIMILIAN
;
Mansi TOMMASO
;
Katus A HUGO
;
Meder BENJAMIN
Author Information
1. Institute for Cardiomyopathies
- Keywords:
Dilated cardiomyopathy;
Tau;
Myocardial stiffness;
Computer-based 3D model;
Personalized medicine;
Diastolic function
- From:
Genomics, Proteomics & Bioinformatics
2016;14(4):244-252
- CountryChina
- Language:Chinese
-
Abstract:
The search for a parameter representing left ventricular relaxation from non-invasive and invasive diagnostic tools has been extensive, since heart failure (HF) with preserved ejection fraction (HF-pEF) is a global health problem. We explore here the feasibility using patient-specific cardiac computer modeling to capture diastolic parameters in patients suffering from different degrees of systolic HF. Fifty eight patients with idiopathic dilated cardiomyopathy have undergone thorough clinical evaluation, including cardiac magnetic resonance imaging (MRI), heart catheterization, echocardiography, and cardiac biomarker assessment. A previously-introduced framework for creating multi-scale patient-specific cardiac models has been applied on all these patients. Novel parameters, such as global stiffness factor and maximum left ventricular active stress, representing cardiac active and passive tissue properties have been computed for all patients. Invasive pressure measurements from heart catheterization were then used to evaluate ventricular relaxation using the time constant of isovolumic relaxation Tau (s). Parameters from heart catheterization and the multi-scale model have been evaluated and compared to patient clinical presentation. The model parameter global stiffness factor, representing diastolic passive tissue properties, is correlated signif-icantly across the patient population with s. This study shows that multi-modal cardiac models can successfully capture diastolic (dys) function, a prerequisite for future clinical trials on HF-pEF.
