Project ID BE-MI2023_12


Co Supervisor 1A School of Biomedical Engineering & Imaging SciencesWebsite

Co Supervisor 1B StatisticsWebsite

Additional Supervisor Sanjay Prasad

Predicting optimal therapies for Left Ventricular Outflow Tract Obstruction (LVOTO) for Hypertrophic Cardiomyopathy (HCM) patients.

Hypertrophic cardiomyopathy (HCM) is a poorly understood, heritable cardiac disease affecting > 1 in 500 persons. HCM is characterised by progressive enlargement of the primary pumping chamber of the heart, the left ventricle, wherein the heart muscle is abnormally thick. Patients with HCM can develop left ventricular outflow tract obstruction (LVOTO), a blockage of the path by which blood is pumped out of the heart. Drug-refractory patients with HCM LVOTO can be treated by a septal myectomy (SM), where parts of the heart are surgically removed, alcohol septal ablation (ASA), where alcohol is injected in the heart to kill unwanted tissue, or potentially through Mavacamten a novel sarcomere modulator, however which treatment is best in each patient is not known.

Physics based patient specific models of the heart have been used to optimise therapies for rhythm disorders. In this study we will create patient specific models of HCM patients. We will:

Develop workflows to rapidly create patient specific biomechanical models from routine clinical images in HCM patients.

Test if inferred myocardial properties (shape, stiffness, contraction, pre-load or after-load) correlate with known genetic causes of HCM.

Create models to simulate the effect of Mavacamten, SM and ASA on cardiac contraction.

Test if simulations of each therapy based on pre-procedural data predicts post procedural measurements in patients undergoing each procedure.

Representative Publications

Strocchi M, Gsell MAF, Augustin CM, Razeghi O, Roney CH, Prassl AJ, Vigmond EJ, Behar JM, Gould JS, Rinaldi CA, Bishop MJ, Plank G, Niederer SA. Simulating ventricular systolic motion in a four-chamber heart model with spatially varying robin boundary conditions to model the effect of the pericardium. J Biomech. 2020 Mar 5;101:109645. doi: 10.1016/j.jbiomech.2020.109645. Epub 2020 Jan 21. PMID: 32014305; PMCID: PMC7677892.

Lei CL, Ghosh S, Whittaker DG, Aboelkassem Y, Beattie KA, Cantwell CD, Delhaas T, Houston C, Novaes GM, Panfilov AV, Pathmanathan P, Riabiz M, Dos Santos RW, Walmsley J, Worden K, Mirams GR, Wilkinson RD. Considering discrepancy when calibrating a mechanistic electrophysiology model. Philos Trans A Math Phys Eng Sci. 2020 Jun 12;378(2173):20190349. doi: 10.1098/rsta.2019.0349. Epub 2020 May 25. PMID: 32448065; PMCID: PMC7287333.