Computational Model Predicts Performance of Drug-Eluting StentsComputational Model Predicts Performance of Drug-Eluting Stents
March 7, 2009
Since the first drug-eluting stent (DES) was approved for use in the United States in 2003, the device has been a point of contention owing to reports that it is more prone to clotting and adverse events such as heart attacks than its bare-metal counterparts. A mathematical model developed by researchers at the Massachusetts Institute of Technology (MIT; Cambridge, MA; http://hst.mit.edu) could quiet critics, however, by providing insight into the design of safer drug-eluting stents.
Employing a computational fluid dynamics and mass transfer model, Elazer Edelman, the Thomas D. and Virginia W. Cabot professor of health sciences and technology at MIT, and his fellow researchers Brinda Balakrishnan, Vijaya Kolachalama, and Abraham Tzafriri, discovered that the design of a DES and the flow environment have a significant impact on its performance. The MIT researchers were able to prove that the size and geometry of an endovascular DES ultimately affects blood flow and drug distribution in the body.
Essentially, a stent distorts the natural shape of the arterial wall in which it is placed, thus altering the flow of blood through the artery. In turn, the pattern in which blood flows over a stent can influence deposition and retention of the drug in the arterial wall, according to Edelman. Describing the role that design plays in the stent’s performance in the simplest of terms, he explains, “Stents alter [blood] flow, flow alters [drug] release, release changes what gets deposited, and then flow also changes what is retained. This cascade affects how the body responds to the presence of the stent.”
The MIT team also found that stent design and strut dimensions were key determinants in the size of drug pools that formed from blood flowing over the stent. Blood flow separation and recirculation caused by the presence of the device in the artery create these concentrated areas of the restenosis-reducing pharmaceutical agent, which are credited with contributing to clot formation. Taking these findings into consideration, stents that have very high local levels of drug would be predisposed to clotting, Edelman says.
Using the computational model to predict stent performance based on design and changes in arterial blood flow could assist with the development of safer drug-eluting devices. Edelman notes that it also provides engineers with a means to assess the potential consequences of a design modification while still in the early stages of development. “[The model] does for the first time allow people the opportunity to look at changes before having to test them, which means that high throughput testing for a large number of design changes can occur without the time, risk, and expense of human clinical trials or animal experiments,” he says.
The logical next phase of research would focus on examining diseased models in order to understand the role of the blood vessel wall, according to Edelman. He points out that this aspect of the project can be modeled using the same techniques incorporated in this study.
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