Non-invasive Model-Based Assessment of Passive Left-Ventricular Myocardial Stiffness in Healthy Subjects and in Patients with Non-ischemic Dilated Cardiomyopathy

• Published in: Annals of biomedical engineering Vol. 45; no. 3; pp. 605 - 618
• Main Authors: Hadjicharalambous, Myrianthi, Asner, Liya, Chabiniok, Radomir, Sammut, Eva, Wong, James, Peressutti, Devis, Kerfoot, Eric, King, Andrew, Lee, Jack, Razavi, Reza, Smith, Nicolas, Carr-White, Gerald, Nordsletten, David
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2017; Springer Nature B.V; Springer Verlag
• Subjects: Accuracy; Adult; Biochemistry; Bioengineering; Biological and Medical Physics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Boundary conditions; Cardiology and cardiovascular system; Cardiomyopathy, Dilated - diagnostic imaging; Cardiomyopathy, Dilated - physiopathology; Classical Mechanics; Estimates; Female; Fibre; Heart Ventricles - diagnostic imaging; Heart Ventricles - physiopathology; Human health and pathology; Humans; Imaging; Life Sciences; Male; Mathematical models; Middle Aged; Models, Cardiovascular; Myocardium; Parameter estimation; Parameters; Patients; Pericardium - diagnostic imaging; Pericardium - physiopathology; Precision Medicine - methods; Stiffness; Myocardium; Stiffness; Patient-specific modelling; Parameter uniqueness; Model uncertainties
• ISSN: 0090-6964; 1573-9686
• DOI: 10.1007/s10439-016-1721-4

Patient-specific modelling has emerged as a tool for studying heart function, demonstrating the potential to provide non-invasive estimates of tissue passive stiffness. However, reliable use of model-derived stiffness requires sufficient model accuracy and unique estimation of model parameters. In this paper we present personalised models of cardiac mechanics, focusing on improving model accuracy, while ensuring unique parametrisation. The influence of principal model uncertainties on accuracy and parameter identifiability was systematically assessed in a group of patients with dilated cardiomyopathy ( n = 3 ) and healthy volunteers ( n = 5 ). For all cases, we examined three circumferentially symmetric fibre distributions and two epicardial boundary conditions. Our results demonstrated the ability of data-derived boundary conditions to improve model accuracy and highlighted the influence of the assumed fibre distribution on both model fidelity and stiffness estimates. The model personalisation pipeline—based strictly on non-invasive data—produced unique parameter estimates and satisfactory model errors for all cases, supporting the selected model assumptions. The thorough analysis performed enabled the comparison of passive parameters between volunteers and dilated cardiomyopathy patients, illustrating elevated stiffness in diseased hearts.