Derivation of a finite-element model of lingual deformation during swallowing from the mechanics of mesoscale myofiber tracts obtained by MRI

A Review of In Vitro and In Silico Swallowing Simulators: Design and Applications

Swallowing is a primary and complex behaviour that transports food and drink from the oral cavity, through the pharynx and oesophagus, into the stomach at an appropriate rate and speed. To understand this sophisticated behaviour, a tremendous amount of research has been carried out by utilising the in vivo approach, which is often challenging to perform, poses a risk to the subjects if interventions are undertaken and are seldom able to control for confounding factors. In contrast, in silico (computational) and in vitro (instrumental) methods offer an alternate insight into the process of the human swallowing system. However, the appropriateness of the design and application of these methods have not been formally evaluated. The purpose of this review is to investigate and evaluate the state of the art of in vitro and in silico swallowing simulators, focusing on the evaluation of their mechanical or computational designs in comparison to the corresponding swallowing mechanisms during various phases of swallowing (oral phase, pharyngeal phase and esophageal phase). Additionally, the potential of the simulators is also discussed in various areas of applications, including the study of swallowing impairments, swallowing medications, food process design and dysphagia management. We also address current limitations and recommendations for the future development of existing simulators.

Two dimensional computational model coupling myoarchitecture-based lingual tissue mechanics with liquid bolus flow during oropharyngeal swallowing

Biomechanical relationships involving lingual myoanatomy, contractility, and bolus movement are fundamental properties of human swallowing. To portray the relationship between lingual deformation and bolus flow during swallowing, a weakly one-way solid-fluid finite element model (FEM) was derived employing an elemental mesh aligned to magnetic resonance diffusional tractography (Q-space MRI, QSI) of the human tongue, an arbitrary Lagrangian-Eulerian (ALE) formulation with remeshing to account for the effects of lingual surface (boundary) deformation, an implementation of patterned fiber shortening, and a computational visualization of liquid bolus flow. Representing lingual tissue deformation in terms of its 2D principal Lagrangian strain in the mid-sagittal plane, we demonstrated that the swallow sequence was characterized by initial superior-anterior expansion directed towards the hard palate, followed by sequential, radially directed, contractions of the genioglossus and verticalis to promote lingual rotation (lateral perspective) and propulsive displacement. We specifically assessed local bolus velocity as a function of viscosity (perfect slip conditions) and observed that a low viscosity bolus (5 cP) exhibited maximal displacement, surface spreading and local velocity compared to medium (110 cP, 300 cP) and high (525 cP) viscosity boluses. Analysis of local nodal velocity revealed that all bolus viscosities exhibited a bi-phasic progression, with the low viscosity bolus being the most heterogeneous and fragmented and the high viscosity bolus being the most homogenous and cohesive. Intraoral bolus cohesion was depicted in terms of the distributed velocity gradient, with higher gradients being associated with increased shear rate and bolus fragmentation. Lastly, we made a sensitivity analysis on tongue stiffness and contractility by varying the degree of extracellular matrix (ECM) stiffness through effects on the Mooney-Rivlin derived passive matrix and by varying maximum tetanized isometric stress, and observed that a graded increase of ECM stiffness was associated with reduced bolus spreading, posterior displacement, and surface velocity gradients, whereas a reduction of global contractility resulted in a graded reduction of obtainable accommodation volume, absent bolus spreading, and loss of posterior displacement. We portray a unidirectionally coupled solid-liquid FEM which associates myoarchitecture-based lingual deformation with intra-oral bolus flow, and deduce that local elevation of the velocity gradient correlates with bolus fragmentation, a precondition believed to be associated with aspiration vulnerability during oropharyngeal swallowing.

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

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.

How Do Orodispersible Tablets Behave in an In Vitro Oral Cavity Model: A Pilot Study

Orodispersible tablets (ODTs) offer rapid disintegration of the dosage form when placed on the tongue, which leads to fast release of the active pharmaceutical ingredient. Despite increased use in diverse patient populations, there have been numerous challenges associated with ODTs. One such concern is the lack of standardised assessment of disintegration behaviour. In the European Pharmacopoeia, ‘orodispersibles’ are defined as such if disintegration time is faster than 3 min. Common in vitro measurement methods only provide single time point data and have limited physiological accuracy. To determine more bio-predictive disintegration kinetics, a bench-top in vitro oral cavity model (OCM) was modified and piloted to assess disintegration of three ODTs of differing hardness. All ODTs disintegrated similarly within the OCM—surface breakdown/swelling, initial ‘wash away’ and final ‘wash away’. The distinct advantage presented within this pilot study using the OCM is the opportunity to ascertain disintegration behaviour profiles of ODTs by evaluating changes in the observable area during simulated oral processing. The model could be implemented as a decision-support tool during the early stages of the drug design process to improve acceptability and further understand ODT disintegration behaviour.

Smeared Multiscale Finite Element Models for Mass Transport and Electrophysiology Coupled to Muscle Mechanics

Mass transport represents the most fundamental process in living organisms. It includes delivery of nutrients, oxygen, drugs, and other substances from the vascular system to tissue and transport of waste and other products from cells back to vascular and lymphatic network and organs. Furthermore, movement is achieved by mechanical forces generated by muscles in coordination with the nervous system. The signals coming from the brain, which have the character of electrical waves, produce activation within muscle cells. Therefore, from a physics perspective, there exist a number of physical fields within the body, such as velocities of transport, pressures, concentrations of substances, and electrical potential, which is directly coupled to biochemical processes of transforming the chemical into mechanical energy and further internal forces for motion. The overall problems of mass transport and electrophysiology coupled to mechanics can be investigated theoretically by developing appropriate computational models. Due to the enormous complexity of the biological system, it would be almost impossible to establish a detailed computational model for the physical fields related to mass transport, electrophysiology, and coupled fields. To make computational models feasible for applications, we here summarize a concept of smeared physical fields, with coupling among them, and muscle mechanics, which includes dependence on the electrical potential. Accuracy of the smeared computational models, also with coupling to muscle mechanics, is illustrated with simple example, while their applicability is demonstrated on a liver model with tumors present. The last example shows that the introduced methodology is applicable to large biological systems.

Fibre and extracellular matrix contributions to passive forces in human skeletal muscles: An experimental based constitutive law for numerical modelling of the passive element in the classical Hill-type three element model

The forces that allow body movement can be divided into active (generated by sarcomeric contractile proteins) and passive (sustained by intra-sarcomeric proteins, fibre cytoskeleton and extracellular matrix (ECM)). These are needed to transmit the active forces to the tendon and the skeleton. However, the relative contribution of the intra- and extra- sarcomeric components in transmitting the passive forces is still under debate. There is limited data in the literature about human muscle and so it is difficult to make predictions using multiscale models, imposing a purely phenomenological description for passive forces. In this paper, we apply a method for the experimental characterization of the passive properties of fibres and ECM to human biopsy and propose their clear separation in a Finite Element Model. Experimental data were collected on human single muscle fibres and bundles, taken from vastus lateralis muscle of elderly subjects. Both were progressively elongated to obtain two stress-strain curves which were fitted to exponential equations. The mechanical properties of the extracellular passive components in a bundle of fibres were deduced by the subtraction of the passive tension observed in single fibres from the passive tension observed in the bundle itself. Our results showed that modulus and tensile load bearing capability of ECM are higher than those of fibres and defined their quantitative characterization that can be used in macroscopic models to study their role in the transmission of forces in physiological and pathophysiological conditions.

Smeared multiscale finite element model for electrophysiology and ionic transport in biological tissue

Basic functions of living organisms are governed by the nervous system through bidirectional signals transmitted from the brain to neural networks. These signals are similar to electrical waves. In electrophysiology the goal is to study the electrical properties of biological cells and tissues, and the transmission of signals. From a physics perspective, there exists a field of electrical potential within the living body, the nervous system, extracellular space and cells. Electrophysiological problems can be investigated experimentally and also theoretically by developing appropriate mathematical or computational models. Due to the enormous complexity of biological systems, it would be almost impossible to establish a detailed computational model of the electrical field, even for only a single organ (e.g. heart), including the entirety of cells comprising the neural network. In order to make computational models feasible for practical applications, we here introduce the concept of smeared fields, which represents a generalization of the previously formulated multiscale smeared methodology for mass transport in blood vessels, lymph, and tissue. We demonstrate the accuracy of the smeared finite element computational models for the electric field in numerical examples. The electrical field is further coupled with ionic mass transport within tissue composed of interstitial spaces extracellularly and by cytoplasm and organelles intracellularly. The proposed methodology, which couples electrophysiology and molecular ionic transport, is applicable to a variety of biological systems.

A novel diffusion-tensor MRI approach for skeletal muscle fascicle length measurements

Musculoskeletal (dys‐)function relies for a large part on muscle architecture which can be obtained using Diffusion‐Tensor MRI (DT‐MRI) and fiber tractography. However, reconstructed tracts often continue along the tendon or aponeurosis when using conventional methods, thus overestimating fascicle lengths. In this study, we propose a new method for semiautomatic segmentation of tendinous tissue using tract density (TD). We investigated the feasibility and repeatability of this method to quantify the mean fascicle length per muscle. Additionally, we examined whether the method facilitates measuring changes in fascicle length of lower leg muscles with different foot positions. Five healthy subjects underwent two DT‐MRI scans of the right lower leg, with the foot in 15° dorsiflexion, neutral, and 30° plantarflexion positions. Repeatability of fascicle length measurements was assessed using Bland–Altman analysis. Changes in fascicle lengths between the foot positions were tested using a repeated multivariate analysis of variance (MANOVA). Bland–Altman analysis showed good agreement between repeated measurements. The coefficients of variation in neutral position were 8.3, 16.7, 11.2, and 10.4% for soleus (SOL), fibularis longus (FL), extensor digitorum longus (EDL), and tibialis anterior (TA), respectively. The plantarflexors (SOL and FL) showed significant increase in fascicle length from plantarflexion to dorsiflexion, whereas the dorsiflexors (EDL and TA) exhibited a significant decrease. The use of a tract density for semiautomatic segmentation of tendinous structures provides more accurate estimates of the mean fascicle length than traditional fiber tractography methods. The method shows moderate to good repeatability and allows for quantification of changes in fascicle lengths due to passive stretch.

Investigation of interaction phenomena between crural fascia and muscles by using a three-dimensional numerical model

The focus of this work is the numerical modeling of the anterior compartment of the human leg with particular attention to crural fascia. Interaction phenomena between fascia and muscles are of clinical interest to explain some pathologies, as the compartment syndrome. A first step to enhance knowledge on this topic consists in the investigation of fascia biomechanical role and its interaction with muscles in physiological conditions. A three-dimensional finite element model of the anterior compartment is developed based on anatomical data, detailing the structural conformation of crural fascia, composed of three layers, and modeling the muscles as a unique structure. Different constitutive models are implemented to describe the mechanical response of tissues. Crural fascia is modeled as a hyperelastic fiber-reinforced material, while muscle tissue via a three-element Hill's model. The numerical analysis of isotonic contraction of muscles is performed, allowing the evaluation of pressure induced within muscles and consequent stress and strain fields arising on the crural fascia. Numerical results are compared with experimental measurements of the compartment radial deformation and intracompartmental pressure during concentric contraction, to validate the model. The numerical model provides a suitable description of muscles contraction of the anterior compartment and the consequent mechanical interaction with the crural fascia.

Assessing the multiscale architecture of muscular tissue with Q-space magnetic resonance imaging: Review

Contraction of muscular tissue requires the synchronized shortening of myofibers arrayed in complex geometrical patterns. Imaging such myofiber patterns with diffusion-weighted MRI reveals architectural ensembles that underlie force generation at the organ scale. Restricted proton diffusion is a stochastic process resulting from random translational motion that may be used to probe the directionality of myofibers in whole tissue. During diffusion-weighted MRI, magnetic field gradients are applied to determine the directional dependence of proton diffusion through the analysis of a diffusional probability distribution function (PDF). The directions of principal (maximal) diffusion within the PDF are associated with similarly aligned diffusion maxima in adjacent voxels to derive multivoxel tracts. Diffusion-weighted MRI with tractography thus constitutes a multiscale method for depicting patterns of cellular organization within biological tissues. We provide in this review, details of the method by which generalized Q-space imaging is used to interrogate multidimensional diffusion space, and thereby to infer the organization of muscular tissue. Q-space imaging derives the lowest possible angular separation of diffusion maxima by optimizing the conditions by which magnetic field gradients are applied to a given tissue. To illustrate, we present the methods and applications associated with Q-space imaging of the multiscale myoarchitecture associated with the human and rodent tongues. These representations emphasize the intricate and continuous nature of muscle fiber organization and suggest a method to depict structural "blueprints" for skeletal and cardiac muscle tissue.

Development and validation of a computational finite element model of the rabbit upper airway: simulations of mandibular advancement and tracheal displacement

The mechanisms leading to upper airway (UA) collapse during sleep are complex and poorly understood. We previously developed an anesthetized rabbit model for studying UA physiology. On the basis of this body of physiological data, we aimed to develop and validate a two-dimensional (2D) computational finite element model (FEM) of the passive rabbit UA and peripharyngeal tissues. Model geometry was reconstructed from a midsagittal computed tomographic image of a representative New Zealand White rabbit, which included major soft (tongue, soft palate, constrictor muscles), cartilaginous (epiglottis, thyroid cartilage), and bony pharyngeal tissues (mandible, hard palate, hyoid bone). Other UA muscles were modeled as linear elastic connections. Initial boundary and contact definitions were defined from anatomy and material properties derived from the literature. Model parameters were optimized to physiological data sets associated with mandibular advancement (MA) and caudal tracheal displacement (TD), including hyoid displacement, which featured with both applied loads. The model was then validated against independent data sets involving combined MA and TD. Model outputs included UA lumen geometry, peripharyngeal tissue displacement, and stress and strain distributions. Simulated MA and TD resulted in UA enlargement and nonuniform increases in tissue displacement, and stress and strain. Model predictions closely agreed with experimental data for individually applied MA, TD, and their combination. We have developed and validated an FEM of the rabbit UA that predicts UA geometry and peripharyngeal tissue mechanical changes associated with interventions known to improve UA patency. The model has the potential to advance our understanding of UA physiology and peripharyngeal tissue mechanics.

Patterns of intersecting fiber arrays revealed in whole muscle with generalized Q-space imaging

The multiscale attributes of mammalian muscle confer significant challenges for structural imaging in vivo. To achieve this, we employed a magnetic resonance method, termed "generalized Q-space imaging", that considers the effect of spatially distributed diffusion-weighted magnetic field gradients and diffusion sensitivities on the morphology of Q-space. This approach results in a subvoxel scaled probability distribution function whose shape correlates with local fiber orientation. The principal fiber populations identified within these probability distribution functions can then be associated by streamline methods to create multivoxel tractlike constructs that depict the macroscale orientation of myofiber arrays. We performed a simulation of Q-space input parameters, including magnetic field gradient strength and direction, diffusion sensitivity, and diffusional sampling to determine the optimal achievable fiber angle separation in the minimum scan time. We applied this approach to resolve intravoxel crossing myofiber arrays in the setting of the human tongue, an organ with anatomic complexity based on the presence of hierarchical arrays of intersecting myocytes. Using parameters defined by simulation, we imaged at 3T the fanlike configuration of the human genioglossus and the laterally positioned merging fibers of the styloglossus, inferior longitudinalis, chondroglossus, and verticalis. Comparative scans of the excised mouse tongue at 7T demonstrated similar midline and lateral crossing fiber patterns, whereas histological analysis confirmed the presence and distribution of these myofiber arrays at the microscopic scale. Our results demonstrate a magnetic resonance method for acquiring and displaying diffusional data that defines highly ordered myofiber patterns in architecturally complex tissue. Such patterns suggest inherent multiscale fiber organization and provide a basis for structure-function analyses in vivo and in model tissues.

Upper Airway Elasticity Estimation in Pediatric Down Syndrome Sleep Apnea Patients Using Collapsible Tube Theory

Elasticity of the soft tissues surrounding the upper airway lumen is one of the important factors contributing to upper airway disorders such as snoring and obstructive sleep apnea. The objective of this study is to calculate patient specific elasticity of the pharynx from magnetic resonance (MR) images using a 'tube law', i.e., the relationship between airway cross-sectional area and transmural pressure difference. MR imaging was performed under anesthesia in children with Down syndrome (DS) and obstructive sleep apnea (OSA). An airway segmentation algorithm was employed to evaluate changes in airway cross-sectional area dilated by continuous positive airway pressure (CPAP). A pressure-area relation was used to make localized estimates of airway wall stiffness for each patient. Optimized values of patient specific Young's modulus for tissue in the velopharynx and oropharynx, were estimated from finite element simulations of airway collapse. Patient specific deformation of the airway wall under CPAP was found to exhibit either a non-linear 'hardening' or 'softening' behavior. The localized airway and tissue elasticity were found to increase with increasing severity of OSA. Elasticity based patient phenotyping can potentially assist clinicians in decision making on CPAP and airway or tissue elasticity can supplement well-known clinical measures of OSA severity.

Automatic prediction of tongue muscle activations using a finite element model

Computational modeling has improved our understanding of how muscle forces are coordinated to generate movement in musculoskeletal systems. Muscular-hydrostat systems, such as the human tongue, involve very different biomechanics than musculoskeletal systems, and modeling efforts to date have been limited by the high computational complexity of representing continuum-mechanics. In this study, we developed a computationally efficient tracking-based algorithm for prediction of muscle activations during dynamic 3D finite element simulations. The formulation uses a local quadratic-programming problem at each simulation time-step to find a set of muscle activations that generated target deformations and movements in finite element muscular-hydrostat models. We applied the technique to a 3D finite element tongue model for protrusive and bending movements. Predicted muscle activations were consistent with experimental recordings of tongue strain and electromyography. Upward tongue bending was achieved by recruitment of the superior longitudinal sheath muscle, which is consistent with muscular-hydrostat theory. Lateral tongue bending, however, required recruitment of contralateral transverse and vertical muscles in addition to the ipsilateral margins of the superior longitudinal muscle, which is a new proposition for tongue muscle coordination. Our simulation framework provides a new computational tool for systematic analysis of muscle forces in continuum-mechanics models that is complementary to experimental data and shows promise for eliciting a deeper understanding of human tongue function.