AbstractsMedical & Health Science

Development of methodology for the characterisation and modelling of soft tissues for real-time simulation. Application to the modelling of the viscoelastic mechanical response of brain tissue

by EJ (Emilio Sanchez-Tapia




Institution: TDX
Department:
Year: 2016
Keywords: Modelado matemático.; Cizalla simple.; Mechanical characterisation.; Brain tissue.; Soft tissues.; Surgery simulation.
Posted: 02/05/2017
Record ID: 2063688
Full text PDF: http://hdl.handle.net/10171/39358


Abstract

The characterisation of the mechanical properties of biological soft tissues is of great interest for many applications in the bioengineering field: such as for the detection of tumours and diseases, for the development of medical assistive and surgical technologies. These technologies include surgery simulation, which based on computational methods, reproduces surgical procedures in order to develop the skills of the surgeon, to plan operations or to provide technical support to surgeon during the operation. However, modelling the physical behaviour of human organs and tissues remains a challenge. This is due to the difficulty in characterising the physical properties of biological soft tissues. Besides, the challenge lies on the computation time requirements for real-time simulations. Surgical real-time simulation should employ a sufficiently precise and simple model in order to provide a realistic tactile and visual feedback. To address these difficulties, this thesis presents a methodology for the characterisation and modelling of the mechanical properties of soft tissues, for its integration into real-time surgical simulators. The characterisation is performed in the laboratory using a parallel plate rheometer. The methodology has been applied to synthetic materials such as agar gel, as well as to biological tissues such as porcine brain tissue. By performing this characterisation, different mathematical models have been analysed and developed for the modelling of the selected tissues. These models have been studied in order to select the most appropriate one, depending on the specific requirements of the simulator.