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A Computational Desk for Surgeons

  • Victoria Hilford
  • Yusuf Yildiz
  • Marc Garbey
Chapter

Abstract

According to the American Heart Association, cardiovascular disease is an underlying cause of death that accounted for 37.3% of all deaths, or one of every 2.7 deaths in the United States in 2003. Many of these deaths corresponding to vascular disease are due to the rupture of an aneurism or the rupture of a vulnerable plaque usually located near the narrowing of blood vessels, also called stenosis [1, 2]. The interested reader can refer to the chapters of Mark Davies et al. and Scott Berceli et al. in this volume for an overview of low extremity vessels diseases.

Endovascular surgery is a relatively new procedure to treat such problems that may develop in blood vessels. In recent years, we have seen the development of intravascular balloons, stents, and coils that can be put in place through arteries with minimum invasive procedures. Endovascular surgery is performed by radiologists, neurosurgeons, cardiologists, and vascular surgeons. This surgery is essentially guided by imaging such as X-ray techniques. The interested reader can refer to the chapter of Mark Davies et al. for a review of the state of the art, and the chapter of Berceli et al. that emphasize the system biology approach of the problem.

Typically, workflow involved in the planning of endovascular surgery includes the acquisition of the patient’s medical image in DICOM (Digital Imaging and Communications in Medicine) format, the image visualization such as zooming, rotating, 2D and 3D rendering that allows the surgeon to identify a region of interest (ROI), the image processing that allows segmentation of the original medical image based on the chosen ROI, creating a model by using the geometry extraction on the ROI, extracting patient-specific boundary condition parameters for flow simulation, running the simulation, and visualization of the results. The surgeon will repeat these steps easily as many times as needed to come up with a decision. The surgeon will also be able to virtually modify the geometry of artery lumen, in order to anticipate the outcome of a surgical procedure.

Keywords

Domain Decomposition Penalty Method Image Visualization Endovascular Surgery Magnetic Resonance Imaging Slice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.University of HoustonHoustonUSA

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