Laplace-based modeling of fiber orientation in the tongue

Abstract

Mechanical modeling of tongue deformation plays a significant role in the study of breathing, swallowing, and speech production. In the absence of internal joints, fiber orientations determine the direction of sarcomeric contraction and have great influence over real and simulated tissue motion. However, subject-specific experimental observations of fiber distribution are difficult to obtain; thus, models of fiber distribution are generally used in mechanical simulations. This paper describes modeling of fiber distribution using solutions of Laplace equations and compares the effectiveness of this approach against tractography from diffusion tensor magnetic resonance imaging. The experiments included qualitative comparison of streamlines from the fiber model against experimental tractography, as well as quantitative differences between biomechanical simulations focusing in the region near the genioglossus. The model showed good overall agreement in terms of fiber directionality and muscle positioning when compared to subject-specific imaging results and the literature. The angle between the fiber distribution model against tractography in the genioglossus and geniohyoid muscles averaged [Formula: see text] likely due to experimental noise. However, kinematic responses were similar between simulations with modeled fibers versus experimentally obtained fibers; average discrepancy in surface displacement ranged from 1 to 7 mm, and average strain residual magnitude ranged from [Formula: see text] to 0.2. The results suggest that, for simulation purposes, the modeled fibers can act as a reasonable approximation for the tongue's fiber distribution. Also, given its agreement with the global tongue anatomy, the approach may be used in model-based reconstruction of displacement tracking and diffusion results.

A Narrative Review of Personalized Musculoskeletal Modeling Using the Physiome and Musculoskeletal Atlas Projects

“…In this technique, the proximal and distal aponeuroses (ie, the muscle fibers' origin and insertion) act as the inlet and outlet, respectively, for an incompressible fluid where all other muscle surfaces are defined as impenetrable. Subsequent work has demonstrated close similarity between muscle fiber directions observed in vivo with DTI and those predicted from CFD, [77][78][79] and have taken advantage of these methods to generate local fiber directions in mechanical finite element simulations. 77,79,80 It should be noted that, thus far, CFD muscle tractography has been demonstrated for 21 muscle architectural arrangements including the soleus, gastrocnemius, iliacus, adductor magnus, adductor brevis, gluteus maximus, vastus lateralis, deltoid, rectus femoris, tibialis anterior, biceps femoris, the palate muscles levator veli palatini and palatopharyngeus, 8 muscles in the tongue, as well as the Achilles tendon.…”

“…Subsequent work has demonstrated close similarity between muscle fiber directions observed in vivo with DTI and those predicted from CFD, [77][78][79] and have taken advantage of these methods to generate local fiber directions in mechanical finite element simulations. 77,79,80 It should be noted that, thus far, CFD muscle tractography has been demonstrated for 21 muscle architectural arrangements including the soleus, gastrocnemius, iliacus, adductor magnus, adductor brevis, gluteus maximus, vastus lateralis, deltoid, rectus femoris, tibialis anterior, biceps femoris, the palate muscles levator veli palatini and palatopharyngeus, 8 muscles in the tongue, as well as the Achilles tendon. [76][77][78]80 Application to more anatomical shapes with a variety of architectures remains an exciting area of future exploration and development.…”

“…Computational methods, on the other hand, exist that can create smooth and continuous fields of muscle fiber architecture for use in biomechanical modeling. [75][76][77][78][79] Template mapping is a technique whereby a template shape of muscle architecture is fit to a subject-specific 3D surface of a muscle. 75 In this method, the subject-specific 3D shape of a muscle is extracted from segmented MRI data.…”

“…77,79,80 It should be noted that, thus far, CFD muscle tractography has been demonstrated for 21 muscle architectural arrangements including the soleus, gastrocnemius, iliacus, adductor magnus, adductor brevis, gluteus maximus, vastus lateralis, deltoid, rectus femoris, tibialis anterior, biceps femoris, the palate muscles levator veli palatini and palatopharyngeus, 8 muscles in the tongue, as well as the Achilles tendon. [76][77][78]80 Application to more anatomical shapes with a variety of architectures remains an exciting area of future exploration and development. With its ability to produce smooth, continuous, and dense muscle fiber architecture throughout a 3D muscle volume, this simulation technique is attractive for use in modeling applications.…”

Prospective motion detection and re‐acquisition in diffusion MRI using a phase image–based method—Application to brain and tongue imaging

“…Diffusion MRI (dMRI), which is capable of revealing microstructure characterized by constrained diffusion of water molecules, is a powerful tool for clinical and research purposes such as detecting cerebral ischemia early, 1 tracking structural connectivity in the brain, 2,3 and studying muscle structure in the tongue. [4][5][6] However, dMRI is susceptible to motion artifacts due to long acquisition times, especially when the more advanced diffusion imaging techniques such as high angular resolution diffusion imaging 7 and q-ball imaging 8 are involved. Motion artifacts in dMRI result from unwanted phase accumulation during the diffusion or imaging gradients, 9,10 which can show up as volume-to-volume or slice-to-volume misalignment, blurring, and signal dropout.…”