Non-invasive Model-Based Assessment of Passive Left-Ventricular Myocardial Stiffness in Healthy Subjects and in Patients with Non-ischemic Dilated Cardiomyopathy.
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 ([Formula: see text]) and healthy volunteers ([Formula: see text]). 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.
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK. myrianthi.hadjicharalambous@kcl.ac.uk.
Myrianthi
0000-0003-1212-5882
M
Hadjicharalambous
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Liya
L
Asner
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.|Inria and Paris-Saclay University, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, 91120, Palaiseau, France.
Radomir
R
Chabiniok
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Eva
E
Sammut
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
James
J
Wong
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Devis
D
Peressutti
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Eric
E
Kerfoot
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Andrew
A
King
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Jack
J
Lee
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Reza
R
Razavi
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.|Department of Engineering Science, University of Auckland, 20 Symonds St, Auckland, 1010, New Zealand.
Nicolas
N
Smith
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
Gerald
G
Carr-White
Division of Imaging Sciences and Biomedical Engineering, King's College London, St. Thomas' Hospital, London, SE1 7EH, UK.
David
D
Nordsletten
D000328:Adult; D002311:Cardiomyopathy, Dilated / Q000000981:diagnostic imaging / Q000503:physiopathology; D005260:Female; D006352:Heart Ventricles / Q000000981:diagnostic imaging / Q000503:physiopathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D009206:Myocardium; D010496:Pericardium / Q000000981:diagnostic imaging / Q000503:physiopathology; D057285:Precision Medicine / Q000379:methods
Model uncertainties; Myocardium; Parameter uniqueness; Patient-specific modelling; Stiffness