The Computational Biomechanics Research Group at the University of Glasgow is a part of Glasgow Computational Engineering Centre (GCEC) and is led by Dr. Ankush Aggarwal.

Our aim is to generate new scientific knowledge and methods using innovative ideas in numerical methods and biomechanics that contribute towards improved cardiovascular healthcare. Our work can be divided into four categories: cardiovascular modeling, cell mechanics, image-based mechanics, and advanced numerics. Scroll down for more information on these topics.

Strain estimation from 4D images

We have developed methods to estimate strains in cardiovascular tissues directly from image registrations.

Marfan syndrome

Marfan syndrome is a genetic disorder, which puts patients at a higher risk of aneurysm. We are using biomechanical modeling to identify the patients at highest risk so that they can be offered surgery.

Aortic vessels

We have quantified the calcification present in aortic vessels from CT images and developed models for the effect of wall elasticity on haemodynamics.

Aorta-stent interaction

We are developing models to understand the interaction between aorta and stent device.

Lung resection

Lung resection is a surgery to treat lung cancer, but it can lead to cardiovascular issues. We are using computational modeling to understand and predict these changes.

Image-based analysis

We are developing machine learning techniques to analyze clinical images such as ultrasound.

Cardiac tissue

We have developed reaction-diffusion models for cardiac tissue with higher accuracy and faster convergence.

Parameter estimation and inverse models

We have developed new methods for biomechanical parameter estimation of cardiovascular tissues.

Nonlinear solvers

We have developed novel solvers for nonlinear equations with significantly faster convergence and wider domain of convergence.

Statistical framework

We are combining the statistical framework-based techniques with deterministic computational mechanics.

Spline-based strain estimation

To estimate the functional and residual strains in semilunar heart valves, we have developed and used a spline-based technique

Cell mechanobiology

We are developing models to understand the mechanosensitive ion channels.

Cell motility

To understand how cells move, we have complemented experiments with simplified stochastic models.

Cell proliferation and calcification

To understand how cells proliferate and calcify under different biochemical and micromechanical environment, we have combined in-vitro experiments with in-silico models.

Aortic valve

We have developed shell-based models for aortic valves with patient- and population-based fiber architecture.