Computational models of the human heart can be very useful in studying not just the basic mechanisms of heart function, but also to analyze the heart in a diseased state, and come up with methods for diagnosis and therapy.
Dr. Natalia Trayanova's Computational Cardiology Lab at the Johns Hopkins University is doing just thather group uses mathematical models to look at cardiac function and dysfunction, examining the mechanisms behind disorders such as cardiac arrhythmias and pump dysfunction.
In a plenary lecture at the SIAM Conference on Computational Science and Engineering in February, Dr. Trayanova described how her lab uses imaging data from clinics, such as MRIs and CT scans, to create heart models. Using detailed information from such images, the team geometrically constructs 3-D computer models by incorporating information about chemical and protein interactions as well as cardiac fiber orientation.
A normal heart beats at a steady, even rhythm usually between 60 and 100 times a minute. "Cardiac arrhythmia" is a condition caused by a disruption of the normal rhythm of the heart.
Analyzing drug interactions:
Sodium channels are membrane proteins located in cardiac cells, which play a central role in the proper conduction of electrical impulses within the heart, and are hence important for normal cardiac electrical activity. Altered sodium channel function is associated with various arrhythmias, including potentially lethal arrhythmias that result from sodium channel disease.
Given their importance, clinically, drugs for arrhythmia usually target sodium channels. Many drugs used to treat arrhythmia tend to exhibit pro-arrythmic effects while they may cure one component, they can induce another. Hence, clinical trials for arrhythmia drugs have often resulted in more people dying from them than from placebos, says Trayanova. Previously, there has never been a platform to evaluate drug interac
|Contact: Karthika Muthukumaraswamy|
Society for Industrial and Applied Mathematics