Changes and classification in myocardial contractile function in the left ventricle following acute myocardial infarction

• Published in: Journal of the Royal Society interface Vol. 14; no. 132; p. 20170203
• Main Authors: Gao, Hao, Aderhold, Andrej, Mangion, Kenneth, Luo, Xiaoyu, Husmeier, Dirk, Berry, Colin
• Format: Journal Article
• Language: English
• Published: England The Royal Society 01.07.2017; The Royal Society Publishing
• Subjects: Active control; Adult; Aged; Biomarkers; Biomechanics; Blood pressure; Cardiac Modelling; Case-Control Studies; Computer applications; Contractility; Demand analysis; Electrocardiography; Female; Heart attacks; Heart diseases; Heart Ventricles - pathology; Heart Ventricles - physiopathology; Humans; Immersed Boundary Method; Kinematics; Learning algorithms; Life Sciences–Mathematics interface; Machine Learning; Male; Mathematical models; Middle Aged; Muscle contraction; Myocardial Contraction - physiology; Myocardial Infarction; Myocardial Infarction - pathology; Myocardial Infarction - physiopathology; Myocardium; Patients; Statistical analysis; Statistical Inference; Statistics; Ventricle; Ventricular Function; immersed boundary method; statistical inference; machine learning; contractility; cardiac modelling; myocardial infarction
• ISSN: 1742-5689; 1742-5662; 1742-5662
• DOI: 10.1098/rsif.2017.0203

In this research, we hypothesized that novel biomechanical parameters are discriminative in patients following acute ST-segment elevation myocardial infarction (STEMI). To identify these biomechanical biomarkers and bring computational biomechanics ‘closer to the clinic’, we applied state-of-the-art multiphysics cardiac modelling combined with advanced machine learning and multivariate statistical inference to a clinical database of myocardial infarction. We obtained data from 11 STEMI patients (ClinicalTrials.gov NCT01717573) and 27 healthy volunteers, and developed personalized mathematical models for the left ventricle (LV) using an immersed boundary method. Subject-specific constitutive parameters were achieved by matching to clinical measurements. We have shown, for the first time, that compared with healthy controls, patients with STEMI exhibited increased LV wall active tension when normalized by systolic blood pressure, which suggests an increased demand on the contractile reserve of remote functional myocardium. The statistical analysis reveals that the required patient-specific contractility, normalized active tension and the systolic myofilament kinematics have the strongest explanatory power for identifying the myocardial function changes post-MI. We further observed a strong correlation between two biomarkers and the changes in LV ejection fraction at six months from baseline (the required contractility (r = − 0.79, p < 0.01) and the systolic myofilament kinematics (r = 0.70, p = 0.02)). The clinical and prognostic significance of these biomechanical parameters merits further scrutinization.