Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 306765, 24 pages
http://dx.doi.org/10.1155/2012/306765
Research Article

A Workflow for Patient-Individualized Virtual Angiogram Generation Based on CFD Simulation

Jürgen Endres,1 Markus Kowarschik,2 Thomas Redel,2 Puneet Sharma,3 Viorel Mihalef,3 Joachim Hornegger,1,4 and Arnd Dörfler5

1Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, Martensstrasse 3, 91058 Erlangen, Germany
2Angiography & Interventional X-Ray Systems, Healthcare Sector, Siemens AG, Siemensstrasse 1, 91301 Forchheim, Germany
3Corporate Research and Technology, Siemens Corporation, 755 College Road East, Princeton, NJ 08540, USA
4Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University of Erlangen-Nuremberg, 91052 Erlangen, Germany
5Department of Neuroradiology, Friedrich-Alexander University of Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany

Received 1 June 2012; Revised 14 August 2012; Accepted 31 August 2012

Academic Editor: Huafeng Liu

Copyright © 2012 Jürgen Endres et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Increasing interest is drawn on hemodynamic parameters for classifying the risk of rupture as well as treatment planning of cerebral aneurysms. A proposed method to obtain quantities such as wall shear stress, pressure, and blood flow velocity is to numerically simulate the blood flow using computational fluid dynamics (CFD) methods. For the validation of those calculated quantities, virtually generated angiograms, based on the CFD results, are increasingly used for a subsequent comparison with real, acquired angiograms. For the generation of virtual angiograms, several patient-specific parameters have to be incorporated to obtain virtual angiograms which match the acquired angiograms as best as possible. For this purpose, a workflow is presented and demonstrated involving multiple phantom and patient cases.