Biomechanical models and prediction of mobility after tongue cancer surgery

Research output: ThesisPhD Thesis - Research external, graduation UT

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Abstract

Due to the complex anatomy of the tongue, it is not possible to predict functional consequences after surgical treatment of tongue cancer based on reasoning and experience alone. The ambition of the 'Virtual Therapy' project is to develop a Digital Twin model based on actual physics and anatomy of the head and neck region. This model could theoretically assist in predicting functional loss, thereby assisting the physician and patient to better understand the effects of treatment on function. In this thesis various aspects in creating a biomechanical finite element (FE) models of the tongue have been researched. A method was created to enable virtual surgery on a biomechanical models of the tongue by means of a few mouse clicks. The FE analysis causes the tissue to realistically deform when simulating sutures and fibrosis. To personalize the models, an MRI technique called Constrained Spherical Deconvolution (CSD) was used to make intersecting muscle fibers visible in the tongue. In this way, we were able to construct fully personalized models from 10 healthy subjects which correctly predicted the measured tongue movements in 80% of the healthy subjects. Simulating surgery on personalized preoperative tongue models of patients was, unfortunately, less successful due to the artefacts present in the MRI images.
In addition to working on biomechanical models, a previously introduced optical tracking method has been developed further to track the tongue in 3D. This method was able to distinguish tongue movements of healthy subjects and patients after treatment with chemoradiation or surgery. Also, an attempt was made to measure the elasticity of the tongue, without muscle tone, in 10 patients under general anesthesia. Unexpectedly, the tongue tissue appeared to be two times stiffer than while awake.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • van der Heijden, Ferdinand, Supervisor
  • Balm, Alfonsus Jacobus Maria, Supervisor
  • Slump, Cornelis Herman, Co-Supervisor
Award date18 Dec 2020
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-5098-7
DOIs
Publication statusPublished - 18 Dec 2020

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