Cerebral aneurysms: A patient-specic and image-based management pipeline

M.C. VILLA-URIOL; I. LARRABIDE; J. M. POZO; M. KIM; M. DE CRAENE; O. CAMARA; C. ZHANG; A. J. GEERS; H. BOGUNOVIC; H. MORALES; A. F. FRANGI

Computational vision and medical image processing - recent trends

Springer

Lugar: Munich; Año: 2011; p. 327 - 349

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 are expected to bring an insight into the processes behind aneurysm genesis, growth and rupture. On the other one,the inclusion of virtual devices allows the in silico personalized evaluation of alternative treatment scenarios before intervention and constitutes a valuable tool for the industrial design of more effective devices. Before the clinical take-up of the proposed pipeline, validation is of an outmost importance. Our results provide a first approximation by testing several of its components in terms of robustness and accuracy. The next step should comprehensively evaluate the complete pipeline, also proving its clinical value.