Computational model of soft tissues in the human upper airway

Tissue-specified reconstruction modeling of the head and neck structure and its application in simulating airway obstruction

Background and objective

Three-dimensional (3D) reconstruction of head and neck tissues has extensive clinical applications, but due to the complexity and variability of tissue structure, there is still a lack of a complete scheme to reconstruct the head and neck tissues. This study aims to establish a tissue-specified multi-directional cross-sectional image sequence construction method to capture diverse tissue contour information.

Methods

The image sequences that are most conducive to acquiring the boundary contours of the target tissue are constructed from 3D MRI images of the head and neck in a non-traditional way based on the characteristics of each target tissue, and an effective registration strategy is used to integrate the boundaries of the target tissue segmented from multiple image sequences. The NURBS (Non-Uniform Rational B-Splines) surface modeling method is used to construct the 3D structure of the head and neck based on the segmented tissue boundaries, and then the constructed structure is used to build a fluid-structure interaction model to simulate airway collapse.

Results

The multi-directional cross-sectional image sequences of head and neck tissues were reconstructed, which successfully supplemented the missing boundary information in unidirectional image sequences commonly used in anatomical reconstructions. The boundaries of the tongue and soft palate were obtained from three corresponding sequential images respectively, and nonlinear registration methods were developed to match the intersections of the target tissue boundaries segmented from different image sequences. The complete 3D head and neck structure, including the surrounding tissues of the upper airway, was accurately reconstructed, and then directly converted into a finite element model through a meshing procedure. The head and neck numerical models successfully simulate airway collapse in both the obstructive sleep apnea patient and the normal subject, providing detailed information on soft tissue deformation and predicting the values of the airway critical closing pressure.

Conclusions

A complete 3D reconstruction scheme from multi-directional image sequence construction to nonlinear boundary registration and NURBS surface generation is established. The constructed model can accurately reflect the characteristics of real anatomical structure, and can be directly used for complex numerical simulations of upper airway collapse.

Computational Biomechanics of Sleep: A Systematic Mapping Review

Biomechanical studies play an important role in understanding the pathophysiology of sleep disorders and providing insights to maintain sleep health. Computational methods facilitate a versatile platform to analyze various biomechanical factors in silico, which would otherwise be difficult through in vivo experiments. The objective of this review is to examine and map the applications of computational biomechanics to sleep-related research topics, including sleep medicine and sleep ergonomics. A systematic search was conducted on PubMed, Scopus, and Web of Science. Research gaps were identified through data synthesis on variants, outcomes, and highlighted features, as well as evidence maps on basic modeling considerations and modeling components of the eligible studies. Twenty-seven studies (n = 27) were categorized into sleep ergonomics (n = 2 on pillow; n = 3 on mattress), sleep-related breathing disorders (n = 19 on obstructive sleep apnea), and sleep-related movement disorders (n = 3 on sleep bruxism). The effects of pillow height and mattress stiffness on spinal curvature were explored. Stress on the temporomandibular joint, and therefore its disorder, was the primary focus of investigations on sleep bruxism. Using finite element morphometry and fluid-structure interaction, studies on obstructive sleep apnea investigated the effects of anatomical variations, muscle activation of the tongue and soft palate, and gravitational direction on the collapse and blockade of the upper airway, in addition to the airflow pressure distribution. Model validation has been one of the greatest hurdles, while single-subject design and surrogate techniques have led to concerns about external validity. Future research might endeavor to reconstruct patient-specific models with patient-specific loading profiles in a larger cohort. Studies on sleep ergonomics research may pave the way for determining ideal spine curvature, in addition to simulating side-lying sleep postures. Sleep bruxism studies may analyze the accumulated dental damage and wear. Research on OSA treatments using computational approaches warrants further investigation.

In-vivo tongue stiffness measured by aspiration: Resting vs general anesthesia

Tongue cancer treatment often results in impaired speech, swallowing, or mastication. Simulating the effect of treatments can help the patient and the treating physician to understand the effects and impact of the intervention. To simulate deformations of the tongue, identifying accurate mechanical properties of tissue is essential. However, not many succeeded in characterizing in-vivo tongue stiffness. Those who did, measured the tongue At Rest (AR), in which muscle tone subsides even if muscles are not willingly activated. We expected to find an absolute rest state in participants 'under General Anesthesia' (GA). We elaborated on previous work by measuring the mechanical behavior of the in-vivo tongue under aspiration using an improved volume-based method. Using this technique, 5 to 7 measurements were performed on 10 participants both AR and under GA. The obtained Pressure-Shape curves were first analyzed using the initial slope and its variations. Hereafter, an inverse Finite Element Analysis (FEA) was applied to identify the mechanical parameters using the Yeoh, Gent, and Ogden hyperelastic models. The measurements AR provided a mean Young's Modulus of 1638 Pa (min 1035 - max 2019) using the Yeoh constitutive model, which is in line with previous ex-vivo measurements. However, while hoping to find a rest state under GA, the tongue unexpectedly appeared to be approximately 2 to 2.5 times stiffer under GA than AR. Explanations for this were sought by examining drugs administered during GA, blood flow, perfusion, and upper airway reflexes, but neither of these explanations could be confirmed.

Application of patient-specific simulation workflow for obstructive sleep apnea diagnosis and treatment with a mandibular advancement device

A computational fluid dynamics simulation workflow was developed to analyze the upper airway of patients with obstructive sleep apnea, which is a potentially serious sleep-related breathing disorder. A single characteristic parameter was introduced to assess the severity of sleep apnea on the basis of the numerical results. Additionally, a fluid-structure interaction simulation was applied to study in detail the behavior of compliant pharyngeal walls. An experimental setup was designed to validate the patient-specific upper airway modeling. The suitability of the characteristic parameter was demonstrated in a retrospective analysis of radiological and clinical data of 58 patients as well as a prospective analysis of 22 patients. The simulation workflow was successfully used as part of an ongoing clinical investigation to predict the outcome of the obstructive sleep apnea treatment with a mandibular advancement device. The simulation results provided essential information about the critical region in the pharynx for the selection of an appropriate treatment and readily demonstrated the effect of mandibular protrusion on the air flow in the upper airway.

Estimation of the hyperelastic parameters of fresh human oropharyngeal soft tissues using indentation testing

Patient-specific finite element (FE) modeling of the upper airway is an effective tool for accurate assessment of obstructive sleep apnea (OSA) syndrome. It is also useful for planning minimally invasive surgical procedures under severe OSA conditions. A major requirement of FE modeling is having reliable data characterizing the biomechanical properties of the upper airway tissues, particularly oropharyngeal soft tissue. While some data characterizing this tissue's linear elastic regime is available, reliable data characterizing its hyperelasticity is scarce. The aim of the current study is to estimate the hyperelastic mechanical properties of the oropharyngeal soft tissues, including the palatine tonsil, soft palate, uvula, and tongue base. Fresh tissue specimens of human oropharyngeal tissue were acquired from 13 OSA patients who underwent standard surgical procedures. Indentation testing was performed on the specimens to obtain their force-displacement data. To determine the specimens' hyperelastic parameters using these data, an inverse FE framework was utilized. In this work, the hyperelastic parameters corresponding to the commonly used Yeoh and 2nd order Ogden models were obtained. Both models captured the experimental force-displacement data of the tissue specimens reasonably accurately with mean errors of 11.65% or smaller. This study has provided estimates of the hyperelastic parameters of all upper airway soft tissues using fresh human tissue specimens for the first time.

Mechanical behaviors of tension and relaxation of tongue and soft palate: Experimental and analytical modeling

This study is to characterize mechanical properties of uniaxial tension and stress relaxation responses of muscle tissues of tongue and soft palate. Uniaxial tension test and stress relaxation test on 39 fresh tissue samples from four five-month-old boars (65 ± 15 kg) are conducted. Firstly, the rationality of the samples' dimension design and experimenal data measurement is validated by one-way ANOVA F-type test. Mechanical properties, including stress-strain relationship and stress relaxation characteristic, are then investigated in details to show the nonlinear behaviors of the tissue samples clearly. Finally, a constitutive model of representing the mechanical properties is formulated within the nonlinear integral representation framework proposed by Pinkin and Rogers, and corresponding material parameters are fitted to the experimental data based on the Levenberg-Marquardt minimization algorithm. The results of the fitting comparison prove that the formulated constitutive model can capture the observed nonlinear behaviors of the muscle tissue samples in both the axial tension and stress relaxation experiments.

Biomechanics of the soft-palate in sleep apnea patients with polycystic ovarian syndrome

Highly compliant tissue supporting the pharynx and low muscle tone enhance the possibility of upper airway occlusion in children with obstructive sleep apnea (OSA). The present study describes subject-specific computational modeling of flow-induced velopharyngeal narrowing in a female child with polycystic ovarian syndrome (PCOS) with OSA and a non-OSA control. Anatomically accurate three-dimensional geometries of the upper airway and soft-palate were reconstructed for both subjects using magnetic resonance (MR) images. A fluid-structure interaction (FSI) shape registration analysis was performed using subject-specific values of flow rate to iteratively compute the biomechanical properties of the soft-palate. The optimized shear modulus for the control was 38 percent higher than the corresponding value for the OSA patient. The proposed computational FSI model was then employed for planning surgical treatment for the apneic subject. A virtual surgery comprising of a combined adenoidectomy, palatoplasty and genioglossus advancement was performed to estimate the resulting post-operative patterns of airflow and tissue displacement. Maximum flow velocity and velopharyngeal resistance decreased by 80 percent and 66 percent respectively following surgery. Post-operative flow-induced forces on the anterior and posterior faces of the soft-palate were equilibrated and the resulting magnitude of tissue displacement was 63 percent lower compared to the pre-operative case. Results from this pilot study indicate that FSI computational modeling can be employed to characterize the mechanical properties of pharyngeal tissue and evaluate the effectiveness of various upper airway surgeries prior to their application.

Computational modeling of tracheal angioedema due to swelling of the submucous tissue layer

Angioedema is a tissue-swelling pathology due to rapid change in soft tissue fluid content. Its occurrence in the trachea is predominantly localized to the soft mucous tissue that forms the innermost tracheal layer. The biomechanical consequences, such as airway constriction, are dependent upon the ensuing mechanical interactions between all of the various tissues that comprise the tracheal tube. We model the stress interactions by treating the trachea organ as a three-tissue system consisting of swellable mucous in conjunction with nonswelling cartilage and nonswelling trachealis musculature. Hyperelastic constitutive modeling is used by generalizing the standard anisotropic, incompressible soft tissue framework to incorporate the swelling effect. Finite element stress analysis then proceeds with swelling of the mucous layer providing the driving factor for the mechanical analysis. The amount of airway constriction is governed by the mechanical interaction between the three predominant tissue types. The detailed stress analysis indicates the presence of stress concentrations near the various tissue junctions. Because of the tissue's nonlinear mechanical behavior, this can lead to material stiffness fluctuations as a function of location on the trachea. Patient specific modeling is presented. The role of the modeling in the interpretation of diagnostic procedures and the assessment of therapies is discussed.

Numerical simulation of interaction between organs and food bolus during swallowing and aspiration

The mechanism of swallowing is still not fully understood, because the process of swallowing is a rapid and complex interaction among several involved organs and the food bolus. In this work, with the aim of studying swallowing and aspiration processes noninvasively and systematically, a computer simulation method for analyzing the involved organs and water (considered as the food bolus) is proposed. The shape and motion of the organs involved in swallowing are modeled in the same way as in our previous study, by using the Hamiltonian moving particle simulation (MPS) method and forced displacements on the basis of motion in a healthy volunteer. The bolus flow is simulated using the explicit MPS method for fluid analysis. The interaction between the organs and the bolus is analyzed using a fluid-structure coupling scheme. To validate the proposed method, the behavior of the simulated bolus flow is compared qualitatively and quantitatively with corresponding medical images. In addition to the healthy motion model, disorder motion models are constructed for reproducing the aspiration phenomenon by computer simulation. The behaviors of the organs and the bolus considered as the food bolus in the healthy and disorder motion models are compared for evaluating the mechanism of aspiration.

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.

A physically motivated constitutive model for 3D numerical simulation of skeletal muscles

A detailed numerical implementation within the FEM is presented for a physically motivated three-dimensional constitutive model describing the passive and active mechanical behaviors of the skeletal muscle. The derivations for the Cauchy stress tensor and the consistent material tangent are provided. For nearly incompressible skeletal muscle tissue, the strain energy function may be represented either by a coupling or a decoupling of the distortional and volumetric material response. In the present paper, both functionally different formulations are introduced allowing for a direct comparison between the coupled and decoupled isochoric-volumetric approach. The numerical validation of both implementations revealed significant limitations for the decoupled approach. For an extensive characterization of the model response to different muscle contraction modes, a benchmark model is introduced. Finally, the proposed implementation is shown to provide a reliable tool for the analysis of complex and highly nonlinear problems through the example of the human mastication system by studying bite force and three-dimensional muscle shape changes during mastication.

The role of oral soft tissues in swallowing function: what can tongue pressure tell us?

Tongue pressure data taken from healthy subjects during normal oral activities such as mastication, speech and swallowing are providing us with new ways of understanding the role of the tongue in craniofacial growth and function. It has long been recognized that the sequential contact between the tongue and the palate plays a crucial role in the oropharyngeal phase of swallowing. However, because the focus of most research on intraoral pressure has been on the generation of positive pressure by the tongue on the hard palate and teeth, generation and coordination of absolute intraoral pressures and regional pressure gradients has remained unexplored. Ongoing research in our laboratory has uncovered highly variable individual pressure patterns during swallowing, which can nonetheless be divided into four stages: preparatory, primary propulsive, intermediate and terminal. These stages may further be sub-classified according to pressure patterns generated at the individual level as tipper or dipper patterns in the preparatory stage, roller or slapper in the primary propulsive and monophasic or biphasic during the intermediate stage. Interestingly, while an increase in bolus viscosity can result in significant changes to pressure patterns in some individuals, it has little effect in others. Highly individual responses to increased viscosity are also observed with swallowing duration. The above, together with other findings, have important implications for our understanding of the aetiology of widely differing conditions such as protrusive and retrusive malocclusions, dysphagia and sleep apnoea, as well as the development of novel food products.

Development of a computational biomechanical model of the human upper-airway soft-tissues toward simulating obstructive sleep apnea

Numerous challenges are faced in investigations aimed at developing a better understanding of the pathophysiology of obstructive sleep apnea (OSA). The anatomy of the tongue and other upper-airway tissues, and the ability to model their behavior, are central to such investigations. We present details of the construction and development of a soft-tissue model of the human upper airway, with the ultimate goal of simulating obstructive sleep apnea. The steps taken to produce a representative anatomical geometry, of which the associated muscle histology is also captured, are documented. An overview of the mathematical models used to describe tissue behavior, both at a macro- and microscopic level, is given. A neurological model, which mimics the proprioceptive capabilities of the body, is described as it is applies to control of the active dynamics of the tongue. A simplified scenario, which allows for the manipulation of several environmental influences, is presented. It is demonstrated that the response of the genioglossus is qualitatively similar to that determined through experimental techniques. Furthermore, insights into the stress distribution developed within the tongue are discussed. It is shown that changes in almost any aspect of the breathing or physiological conditions invoke a significant change in the response of the airway dilators. The results of this study provide further evidence of the importance of modeling and simulation techniques as an aid in understanding the complex behavior of the human body.