Myocardial Stiffness Estimation: A Novel Cost Function for Unique Parameter Identification

Myocardial stiffness is a clinical biomarker used to diagnose and stratify diseases such as heart failure. This biomechanical property can be inferred from the personalisation of computational cardiac models to clinical measures. Nevertheless, previous attempts have been unable to determine a unique set of material constitutive parameters. In this study we address this shortcoming by proposing a new cost function that allows us to uncouple key parameters and uniquely describe passive material properties in patients from available clinical data.

[1]  Kevin F. Augenstein,et al.  Method and apparatus for soft tissue material parameter estimation using tissue tagged Magnetic Resonance Imaging. , 2005, Journal of biomechanical engineering.

[2]  T. Schaeffter,et al.  Towards a fast and efficient approach for modelling the patient-specific ventricular haemodynamics. , 2014, Progress in biophysics and molecular biology.

[3]  D N Firmin,et al.  A comparison of left ventricular myocardial velocity in diastole measured by magnetic resonance and left ventricular filling measured by Doppler echocardiography. , 1996, European heart journal.

[4]  Andrew D. McCulloch,et al.  Effect of Laminar Orthotropic Myofiber Architecture on Regional Stress and Strain in the Canine Left Ventricle , 2000 .

[5]  Martin J Bishop,et al.  Soft Tissue Modelling of Cardiac Fibres for Use in Coupled Mechano-Electric Simulations , 2007, Bulletin of mathematical biology.

[6]  Daniel Rueckert,et al.  Understanding the need of ventricular pressure for the estimation of diastolic biomarkers , 2013, Biomechanics and Modeling in Mechanobiology.

[7]  Wolfgang Hoffmann,et al.  Role of Left Ventricular Stiffness in Heart Failure With Normal Ejection Fraction , 2008, Circulation.

[8]  N P Smith,et al.  Coupling multi-physics models to cardiac mechanics. , 2011, Progress in biophysics and molecular biology.

[9]  Sébastien Ourselin,et al.  The estimation of patient-specific cardiac diastolic functions from clinical measurements , 2012, Medical Image Anal..

[10]  David Barber,et al.  An automatic service for the personalization of ventricular cardiac meshes , 2014, Journal of The Royal Society Interface.

[11]  Pablo Lamata,et al.  Estimation of Diastolic Biomarkers: Sensitiviy to Fibre Orientation , 2014, STACOM.

[12]  Alistair A. Young,et al.  Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function , 2009, Medical Image Anal..

[13]  Gerhard A Holzapfel,et al.  Constitutive modelling of passive myocardium: a structurally based framework for material characterization , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[14]  O. C. Zienkiewicz,et al.  The Finite Element Method: Its Basis and Fundamentals , 2005 .

[15]  D. Brutsaert,et al.  New concepts in diastolic dysfunction and diastolic heart failure: Part I: diagnosis, prognosis, and measurements of diastolic function. , 2002, Circulation.

[16]  A. McCulloch,et al.  Passive material properties of intact ventricular myocardium determined from a cylindrical model. , 1991, Journal of biomechanical engineering.

[17]  Myrianthi Hadjicharalambous,et al.  Analysis of passive cardiac constitutive laws for parameter estimation using 3D tagged MRI , 2014, Biomechanics and modeling in mechanobiology.

[18]  Pablo Lamata,et al.  An accurate, fast and robust method to generate patient-specific cubic Hermite meshes , 2011, Medical Image Anal..

[19]  Daniel Rodríguez-Pérez,et al.  Diastolic chamber properties of the left ventricle assessed by global fitting of pressure-volume data: improving the gold standard of diastolic function. , 2013, Journal of applied physiology.

[20]  N. Sharpe,et al.  Left ventricular remodeling after myocardial infarction: pathophysiology and therapy. , 2000, Circulation.

[21]  Pablo Lamata,et al.  Quality Metrics for High Order Meshes: Analysis of the Mechanical Simulation of the Heart Beat , 2013, IEEE Transactions on Medical Imaging.

[22]  Pablo Lamata,et al.  A computational pipeline for quantification of mouse myocardial stiffness parameters , 2014, Comput. Biol. Medicine.

[23]  Daniel Rueckert,et al.  Temporal sparse free-form deformations , 2013, Medical Image Anal..