Suran
Galappaththige

A patient-specific model (PSM) is a computational model personalized to represent a particular patient. In silico clinical trials (ISCTs) use virtual patient cohorts to assess medical device performance. This project evaluates current PSM and ISCT methods for cardiovascular regulatory applications, with potential to reduce the size of real clinical trials.

Using 3D atria and bi-ventricular mesh models with CHASTE cardiac solver (finite element analysis) to simulate electrical wave propagation throughout the full heart. The goal is a computational model with known arrhythmia mechanisms to rigorously evaluate diagnostic device accuracy.

Cardiac EP models are increasingly used in clinical and regulatory contexts. This project assesses uncertainty in model predictions to ensure the reliability of clinical decisions. Contribution includes running simulations and analyzing outputs for parameter estimation.

Cardiac contractility modulation (CCM) delivers nonexcitatory electrical stimulations during the cardiac absolute refractory period. Contribution: developing automated image analysis code to measure cardiomyocyte contractility from large image datasets.

Cardiac tissue modeled as a 2D bidomain with coupled PDEs describing extracellular and intracellular electrical properties. Active properties described by ion currents, solved numerically using Fortran to study tissue behavior under stimulation.

Examined the degradation of articular cartilage using micro-MRI: setting up experiments, acquiring and analyzing images, and analyzing T1, T2 and T1ρ relaxation times in different zones of the cartilage.

The physical properties of a polymer gel — its elasticity, permeability, dangling ends, and the diffusion of connected strands and foreign particles — produce density fluctuations measurable by Dynamic Light Scattering (DLS), a noninvasive technique for resolving the gel's different relaxation modes.