Direct creation of patient-specific Finite Element models from medical images and preoperative prosthetic implant simulation using h-adaptive Cartesian grids.

Abstract

In silico medicine is believed to be one of the most disruptive changes in the near future. A great effort has been carried out during the last decade to develop predicting computational models to increase the diagnostic capabilities of medical doctors and the effectiveness of therapies. One of the key points of this revolution, will be personalisation, which means in most of the cases creating patient specific computational models, also called digital twins. This practice is currently widespread in research and there are quite a few software products in the market to obtain models from images. Nevertheless, in order to be usable in the clinical practice, these methods have to drastically reduce the time and human intervention required for the creation of the numerical models. First of all, I would like to thank my supervisors Prof. Juan José Ródenas and Dr. Manuel Tur for their exceptional support, trust and comprehension during these years. They actually offered me more dedication and guidance than I would have ever expected to receive. My special thanks go to Prof. Stéphane Bordas and Dr. Pierre Kerfriden for letting me be part of the Advanced Materials and Computational Mechanics research group and to the wonderful people I had the pleasure to meet during my stay at Cardiff University. I am also extremely grateful to Prof. Waldir Roque and Prof. Jessica Zhang for their hospitality and the insightful time dedicated. I would also like to extend my gratitude to all the members of the Departamento de Ingeniería Mechánica y Materiales at the Universitat Politècnica de València who never hesitated to offer me their experience, knowledge and help. In particular I would like to thank Prof.

Improvement in 3D topology optimization with h‐adaptive refinement using the Cartesian grid Finite Element Method

“…Additionally, some of the FDM implementations have been successfully adapted to problems where the object to be analyzed is described by an image, including medical images. The finite cell method 29‐31 and the cgFEM 33,34 have demonstrated their capabilities to deal with these problems 38,39 …”

“…The finite cell method [29][30][31] and the cgFEM 33,34 have demonstrated their capabilities to deal with these problems. 38,39 The basic idea of FDM is to extend the structural analysis problem to an easy-to-mesh fictitious domain that encloses the physical domain with its complex boundaries. The attractive advantages of this kind of methods, like the simplification of the meshing process and the possibility to define a data structure to reuse calculations, come together with some issues that must be considered.…”

“…As indicated in the Introduction, cgFEM can be used to run patient‐specific simulations considering bone‐implant frictional contact conditions. A detailed description of the methodologies involved, out of the scope of this article, can be found in References 36‐38,45, and 72. Hence, in this example, we used this simulation techniques to test the behavior of the methodologies proposed in this article in implant optimization.…”