Computational Cardiac Bioengineering (CCB) Lab at NSU performs multiprofessional research
in the field of advanced computer modeling of bioelectric systems such as the cardiovascular system.
The research in the lab is focused on multiscale modeling of biomedical systems,
image-based 3D geometry reconstruction, disease mechanisms and predictive modeling.
The principle investigator is
Dr. Makarand Deo ,
an Assistant Professor in the Department of Engineering.
Cellular mechanisms of inherited heart disorders
It has been observed that the roots of many inherited or acquired heart disorders
—electrical abnormalities, called arrhyhmia— lie
in electrophysiological mutations in heart cells. These mutations in various cardiac
ion channels alter the electrical activity of the heart. Therefore it is imperative to
study the arrhythmia mechanisms at single cell level using detailed biophysical models.
This project aims to study the functional effects of a lethal inherited cardiac disease
known as Catecholaminergic polymorphic ventricular tachycardia (CPVT) using single cell
computer models. Ryanodine receptor mutations resulting into spontaneous calcium leaks
inside the cells, as commonly observed in CPVT patients, are implemented in single cell
models to study their effect on arrhythmia initiation and maintenance.
This project is funded by American Heart Association (AHA).
3D modeling of cardiac electrical activity
The electrical activity in the heart can be modeled by applying basic electrical
circuit laws to the equivalent lumped circuit representation of the cardiac tissue.
It models both the intra and the extracellular potential fields linked through
the semi-permeable cell membrane which results into a set of bidomain equations.
These equations are then solved on the 3D computational mesh derived from the MRI-based
reconstruction of the patient’s heart geometry. Thus, we can simulate the electrical
functioning of healthy heart as well as reproduce the complex arrhythmia scenarios in
the 3D computer models. The 3D simulations are performed to study the role of heart’s
specialized conduction system, the His-Purkinje system, which is responsible for rapid
and uniform electrical activation of the ventricles, in deadly arrhythmias.
Other 3D simulation projects include modeling of fibrosis and structural arrhythmia.
Image-based 3D reconstruction
Cardiac MRI is the most popular method for diagnosis of structural
heart diseases due to its ability to differentiate between healthy
and pathological tissue based on inhomogeneity in gray level intensities.
However, manual interpretation of MRI scans is time-consuming, tedious and prone
to human errors. The goal of this project is to develop fully-automated computer
algorithms to reconstruct three dimensional geometry of patient's heart tagged
with precise areas of abnormal tissue. These patient-specific computer models
could be used as assistive tools by the cardiologists during surgeries and
clinical decision making process. Direct visualization of patient's heart
anatomy through interactive modeling during complex heart surgeries
enables accurate deployment of ablation lesions, thereby greatly reducing
the time required for the surgery and the patient’s discomfort.
Virtual reality and interactive simulations
Visualization plays a key role in biomedical applications in conveying
salient information about various measurements and enabling the detection
and validation of both expected and unexpected results. For example, various
forms of visualization have been applied to biomedical systems in understanding
neural connectivity within the brain, interpreting isoelectric currents within
the heart, and characterizing white-matter tracts by diffusion tensor imaging.
In this project, we aim to investigate an interactive, user-feedback-oriented
visualization system aimed at guiding the users (e.g. surgeons) to inspect the
cardiac tissues and abnormalities and to track special features of interests.
In particular, dynamic visualization approaches that can enable interactive,
real-time rendering of the 3D heart model and effectively show changes in data
will be investigated. Use of virtual reality techniques, graphics processors (GPUs)
and parallel programming strategies will be investigated.
Ringenberg J, Deo M, Filgueiras-Rama D, Pizarro G, Ibañez B, Peinado R, Trayanova N, Miller M, Merino JL, Berenfeld O, Devabhaktuni V. Effects of fibrosis morphology on reentrant ventricular tachycardia inducibility and simulation fidelity in patient-derived models., Clin Med Insights Cardiol. 2014 Sep 25;8(Suppl 1):1-13
Deo M, Ruan Y, Pandit SV, Shah K, Berenfeld O, Napolitano C, Jalife J, Priori S. Impaired inward rectification in a novel KCNJ2 mutation in short QT syndrome 3 results in atrial fibrillation and ventricular pro-arrhythmia, Proceedings of the National Academy of Sciences of USA (PNAS). 2013; 110(11):4291-6.
Ringenberg J, Deo M, Devabhaktuni V, Filgueiras-Rama D, Pizzaro G, Berenfeld O, Boyers P, , Gold J. Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI. Measurement Science and Technology (Special Issue). 2012; 23(12): 125405:1-13.
Vaidyanathan R*, O’Connell RP*, Deo M*, Milstein ML, Furspan P, Herron TJ, Pandit SV, Musa H, Berenfeld O, Jalife J, Anumonwo JMB. The ionic bases of the action potential in isolated mouse cardiac Purkinje cell. Heart Rhythm. 2013; 10(1):80-7. (*equal contribution)
Deo M, Sato PY, Musa H, Lin X, Pandit SV, Delmar M, Berenfeld O. Relative contribution of changes in sodium current vs intercellular coupling on reentry initiation in two dimensional preparations of Plakophilin-2-deficient cardiac cells. Heart Rhythm. 2011; 8(11):1740-8.
Hou L*, Deo M*, Furspan P, Pandit SV, Mironov S, Auerbach DS, Gong Q, Zhou Z, Berenfeld O, Jalife J. A major role for hERG in determining frequency of reentry in neonatal rat ventricular myocyte monolayer. Circ Res. 2010; 107(12):1503-11. (*equal contribution)