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Cerebral Aneurysms: A Patient-Specific and Image-Based Management Pipeline

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Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 19))

Abstract

This work presents an image- and biomechanics-based data processing pipeline able to build patient-specific models of cerebral aneurysms. The pipeline also contemplates the virtual modeling and release of endovascular devices such as stents and coils. As a result of the morphological, morphodynamic, hemodynamic and structural analyses, a set of complex descriptors relevant for aneurysm’s diagnosis and prognosis is derived. On the one hand these will bring an insight into the processes behind aneurysm genesis, growth and rupture. On the other one, the inclusion of virtual devices enables the in silicopersonalized evaluation of alternative treatment scenarios before intervention and constitutes a valuable tool for the industrial design of more effective devices. Several of its components have been evaluated in terms of robustness and accuracy. The next step should comprehensively assess the complete pipeline, also proving its clinical value. This pipeline illustrates some of the ideas behind the Virtual Physiological Human (VPH) and the integration of complex data for a better understanding of human physiology in health, disease and its treatment.

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Acknowledgements

This work was partially supported by the @neurIST Integrated Project (co-financed by the European Commission through the contract no. IST-027703), the CDTI CENIT-CDTEAM grant funded by the Spanish Ministry of Science and Innovation (MICINN-CDTI) and Philips Healthcare (Best, The Netherlands). The authors would also like to thank the support provided by ANSYS Inc.(Canonsburg, PA, USA).

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Villa-Uriol, M.C. et al. (2011). Cerebral Aneurysms: A Patient-Specific and Image-Based Management Pipeline. In: Tavares, J., Jorge, R. (eds) Computational Vision and Medical Image Processing. Computational Methods in Applied Sciences, vol 19. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0011-6_19

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