Towards regional elastography of intracranial aneurysms.
Weak spots in the aneurysm could be identified estimating the regional stiffness of the wall. Our approach consists in defining a parametric biomechanical model of the vessel which, given the patient's vascular morphology and the blood in- and outflow obtained from non-invasive imaging as well as parameters describing the local elasticity of the wall, enables the computation of the theoretical deformed wall position. The distance between this latter and the one obtained from the aneurysm pulsation is iteratively minimized in order to estimate the optimal set of stiffness parameters. In order to reduce the number of variables to estimate, the aneurysm morphology is clustered into a limited number of regions with uniform stiffness. A random noise perturbation (< 5mm) is applied to the reference deformations and strains, showing that the robustness of the clustering decreases to 75% and errors of the stiffness estimates remain below 10% of the reference values.
Balocco
Simone
S
Center for Computational Imaging & Simulation Technologies in Biomedicine, Universitat Pompeu Fabra, Barcelona, Spain.
Camara
Oscar
O
Frangi
Alejandro F
AF
D003198:Computer Simulation; D004548:Elasticity; D054459:Elasticity Imaging Techniques / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D002532:Intracranial Aneurysm / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D008959:Models, Neurological; D013314:Stress, Mechanical; D014057:Tomography, X-Ray Computed / Q000379:methods*