The incidence of cerebral aneurysms in the general population has been estimated as high as 6%. When a cerebral aneurysm ruptures, blood is forced out of the cerebrovascular system and into the brain, causing lethal damage in most cases. Accordingly, it is critically important for cerebral aneurysms to be treated prior to rupture, which has become increasingly possible as advances in medical imaging have led to dramatically elevated early detection rates. Surgical clipping is the long-standing convention for cerebral aneurysm treatment, but less invasive endovascular therapies (e.g., stenting and/or coil embolization) have emerged over the past decade as a more effective option. Nevertheless, endovascular therapies are successful only 50%-80% of the time, depending on the type of therapy and aneurysm being treated.
The wide range of endovascular therapy success rates results, in part, from the diverse and expanding array of devices that are available for treatment, and from the even more diverse population of aneurysms that the devices are used to treat. Determining (with any certainty) the best treatment match between a patient-specific aneurysm and the hundreds if not thousands of endovascular therapy options is simply not feasible in the current clinical setting. However, the emergence of simulation-based interventional planning is helping to advance clinical practice toward a new paradigm. If the deployment of endovascular devices and subsequent fluid dynamics can be simulated well, then optimal treatments can be identified and even designed on a patient-specific basis. Unfortunately, current technology for simulating endovascular device deployment is still relatively limited, particularly in the context of embolic coils, which are generally most effective among the available devices.
In this talk, we present the first fluid dynamic simulations of coiled cerebral aneurysms that consider the structure and deployment mechanics of embolic coils. The results elucidate the influence of coil packing density, design, and configuration on post-treatment cerebral aneurysm fluid dynamics. Comparisons to experimental results and other endovascular devices will also be made, and an overview of the near-term prospects for interventional planning of endovascular therapies in the clinic will be provided.
David H. Frakes received the B.S. and M.S. degrees in electrical engineering, the M.S. degree in mechanical engineering, and the Ph.D. degree in bioengineering, all from the Georgia Institute of Technology. In April 2008, he joined the faculty at Arizona State University (ASU) where he currently serves as a jointly appointed assistant professor in the School of Biological and Health Systems Engineering (SBHSE) and the School of Electrical, Computer, and Energy Engineering. Professor Frakes was the ASU Centennial Professor of the Year in 2009, received the IEEE Outstanding University Faculty Award in 2011, and was awarded the National Science Foundation CAREER Award and SBHSE Professor of the Year Award in 2012. He manages the Image Processing Applications Laboratory at ASU, which focuses on problems in image and video processing, fluid dynamics, and machine vision.
Friday, October 4th, 2013
132 Fluor Daniel Building
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