Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
Department of Robotics and Mechatronics, Faculty of EEMCS, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
Biomech Model Mechanobiol. 2021 Jun;20(3):1101-1113. doi: 10.1007/s10237-021-01435-7. Epub 2021 Mar 7.
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.
对于晚期舌癌,手术和保留器官治疗的选择通常取决于治疗后舌功能预期丧失的程度。生物力学模型可以通过模拟治疗后的功能丧失来辅助做出选择。然而,这种功能丧失在患者之间存在差异,因此应该为每个患者单独预测。在本研究中,我们的目标是通过使用扩散加权 MRI 对肌肉结构进行约束球形反卷积重建来个性化生物力学模型,从而更好地预测舌的术后运动范围(ROM)。对 10 名健康志愿者进行了扩散加权 MRI 扫描,以重建其舌肌,并将其随后注册到之前描述的人群平均值或图谱中。使用从注册中获得的位移场,从图谱中分割的肌纤维轨迹被变形以创建个性化的肌纤维轨迹。从图谱和个体舌的纤维轨迹创建有限元模型。通过对突出、向下、向左和向右运动的逆模拟,预测了舌的 ROM。将该预测与使用 3D 相机测量的 ROM 进行了比较。结果表明,具有个性化肌肉束的生物力学模型比通用模型更能接近测量的 ROM。然而,为了实现这一结果,需要一个校正因子来补偿模型运动的小幅度。这些模型的未来版本可能有潜力改善对晚期舌癌治疗后功能丧失的估计。