Personalized biomechanical tongue models based on diffusion-weighted MRI and validated using optical tracking of range of motion

K. D.R. Kappert*, L. Voskuilen, L. E. Smeele, A. J.M. Balm, B. Jasperse, A. J. Nederveen, F. van der Heijden

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

For advanced tongue cancer, the choice between surgery and organ-sparing treatment is often dependent on the expected loss of tongue functionality after treatment. Biomechanical models might assist in this choice by simulating the post-treatment function loss. However, this function loss varies between patients and should, therefore, be predicted for each patient individually. In the present study, the goal was to better predict the postoperative range of motion (ROM) of the tongue by personalizing biomechanical models using diffusion-weighted MRI and constrained spherical deconvolution reconstructions of tongue muscle architecture. Diffusion-weighted MRI scans of ten healthy volunteers were obtained to reconstruct their tongue musculature, which were subsequently registered to a previously described population average or atlas. Using the displacement fields obtained from the registration, the segmented muscle fiber tracks from the atlas were morphed back to create personalized muscle fiber tracks. Finite element models were created from the fiber tracks of the atlas and those of the individual tongues. Via inverse simulation of a protruding, downward, left and right movement, the ROM of the tongue was predicted. This prediction was compared to the ROM measured with a 3D camera. It was demonstrated that biomechanical models with personalized muscles bundles are better in approaching the measured ROM than a generic model. However, to achieve this result a correction factor was needed to compensate for the small magnitude of motion of the model. Future versions of these models may have the potential to improve the estimation of function loss after treatment for advanced tongue cancer.

Original languageEnglish
JournalBiomechanics and modeling in mechanobiology
DOIs
Publication statusE-pub ahead of print/First online - 7 Mar 2021

Keywords

  • UT-Hybrid-D
  • Finite element
  • Magnetic resonance imaging
  • Personalized modeling
  • Range of motion
  • Tongue
  • Constrained spherical deconvolution

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