title: Feasibility of estimating regional mechanical properties of cerebral aneurysms in vivo.
abstract: OBJECTIVE
  In this article, the authors studied the feasibility of estimating regional mechanical properties in cerebral aneurysms, integrating information extracted from imaging and physiological data with generic computational models of the arterial wall behavior.
  
  
  METHODS
  A data assimilation framework was developed to incorporate patient-specific geometries into a given biomechanical model, whereas wall motion estimates were obtained from applying registration techniques to a pair of simulated MR images and guided the mechanical parameter estimation. A simple incompressible linear and isotropic Hookean model coupled with computational fluid-dynamics was employed as a first approximation for computational purposes. Additionally, an automatic clustering technique was developed to reduce the number of parameters to assimilate at the optimization stage and it considerably accelerated the convergence of the simulations. Several in silico experiments were designed to assess the influence of aneurysm geometrical characteristics and the accuracy of wall motion estimates on the mechanical property estimates. Hence, the proposed methodology was applied to six real cerebral aneurysms and tested against a varying number of regions with different elasticity, different mesh discretization, imaging resolution, and registration configurations.
  
  
  RESULTS
  Several in silico experiments were conducted to investigate the feasibility of the proposed workflow, results found suggesting that the estimation of the mechanical properties was mainly influenced by the image spatial resolution and the chosen registration configuration. According to the in silico experiments, the minimal spatial resolution needed to extract wall pulsation measurements with enough accuracy to guide the proposed data assimilation framework was of 0.1 mm.
  
  
  CONCLUSIONS
  Current routine imaging modalities do not have such a high spatial resolution and therefore the proposed data assimilation framework cannot currently be used on in vivo data to reliably estimate regional properties in cerebral aneurysms. Besides, it was observed that the incorporation of fluid-structure interaction in a biomechanical model with linear and isotropic material properties did not have a substantial influence in the final results.
authors.affiliation: Department of Information and Communication Technologies, Centre for Computational Imaging and Simulation Technologies in Biomedicine, Universitat Pompeu Fabra, E08018 Barcelona, Spain. balocco.simone@gmail.com
authors.forename: Simone
authors.initials: S
authors.lastname: Balocco
authors.forename: Oscar
authors.initials: O
authors.lastname: Camara
authors.forename: Elio
authors.initials: E
authors.lastname: Vivas
authors.forename: Teresa
authors.initials: T
authors.lastname: Sola
authors.forename: Leopoldo
authors.initials: L
authors.lastname: Guimaraens
authors.forename: Hugo A F
authors.initials: HA
authors.lastname: Gratama van Andel
authors.forename: Charles B
authors.initials: CB
authors.lastname: Majoie
authors.forename: José María
authors.initials: JM
authors.lastname: Pozo
authors.forename: Bart H
authors.initials: BH
authors.lastname: Bijnens
authors.forename: Alejandro F
authors.initials: AF
authors.lastname: Frangi
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004548:Elasticity; D020342:Finite Element Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D002532:Intracranial Aneurysm / Q000378:metabolism / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement; D012984:Software; D013314:Stress, Mechanical