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

The Compartmental Tongue

PURPOSE

Tongue anatomy and function is widely described as consisting of four extrinsic muscles to control position and four intrinsic muscles to control shape. This myoarchitecture cannot, however, explain independent tongue body and blade movement nor accurately model the subtlety of observed lingual shapes. This study presents the case for a finer neuromuscular structure and functional description.

METHOD

Using the theoretical framework of the partitioning hypothesis, evidence for neuromuscular compartments of each of the lingual muscles was discerned by reviewing studies of lingual anatomy, hypoglossal nerve staining, hypoglossal motoneuron axon tracing, muscle fiber type distribution, and electromyography. Muscle fibers of the visible human female were manually traced to produce a three-dimensional atlas of muscular compartments. A kinematic study was undertaken to determine the degree of independent movement between different parts of the tongue. A simple biomechanical model was used to demonstrate how synergistic groups of compartments can control sectors of the tongue.

RESULTS

Results indicated as many as 10 compartments of genioglossus, two each of superior and inferior longitudinal, eight of styloglossus, three of hyoglossus, and six each of transversus and verticalis, while palatoglossus may not have a significant role in tongue function. Kinematic analysis indicated independent control of five sectors of the tongue body, and biomechanical modeling demonstrated how this control may be achieved.

CONCLUSION

Evidence is presented for a lingual structure based on neuromuscular compartments, which work together to position and shape sectors of the tongue and independently control tongue body and blade.

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.

A computational model of upper airway respiratory function with muscular coupling

A two dimensional finite element model of upper airway respiratory function was developed emphasizing the effects of dilator muscular activation on the human retro-lingual airway. The model utilized an upright mid-sagittal computed tomography of the human head and neck to reconstruct relevant structures of the tongue, mandible, and the hyoid-related soft tissues, along with the retro-lingual airway. The reconstructed geometry was divided into fluid and solid domains and discretized into finite element (FE) meshes used for the computational model. Three cases were investigated: standing position; supine position; and supine position coupled with dilator muscle activation. Computations were performed for the inspiration stage of the breathing cycle, utilizing a fluid-structure interaction (FSI) method to couple structural deformation with airflow dynamics. The spatio-temporal deformation of the structures surrounding the airway wall were predicted to be in general agreement with known changes from upright to supine posture on luminal opening, as well as the distribution of airflow. The model effectively captured the effects of muscular stimulation on the upper airway anatomical changes, the flow characteristics relevant to airway reduction in the supine position and airway enlargement with muscle activation. The smallest airway opening in the retro-lingual section is predicted to occur at the epiglottic region in all the three cases considered, an unexpected vulnerable location of airway obstruction. The model also predicted that hyoid displacement would be associated with recovery from airway collapse. This information may be useful for building more complex models relevant to mechanisms and clinical interventions for obstructive sleep apnea.

Airflow dynamics in obese minipigs with obstructive sleep apnea

Objectives

Obstructive sleep apnea (OSA) is associated with anatomical restrictions of pharyngeal airway, but the mechanism of airflow dynamics in OSA is largely unknown. This study utilized computational flow dynamics (CFD) to build a 3D model of the pharynx and to test the hypothesis that an increased restriction in the pharynx in OSA/obese minipigs leads to higher resistance, which in turn creates turbulence to induce temporary blockage of pharyngeal airway patency.

Design

Of five 9-11-months-old Yucatan minipigs, 3 were non-obese (BMI<35) and two obese (BMI>51). After natural sleep monitoring using BioRadio system, pigs were sedated to collect MRI images and airflow parameters. The MRI images were processed to create 3D configurations of pharynx. These 3D configurations were meshed to create finite element models (FEM) of CFD. The obtained airflow parameters were input into the configurations to identify turbulent airflow and its location.

Results

Heavy snoring and multiple >5s hypopnea/apnea episodes (AHI = 32-35) were identified in both obese minipigs during sleep. Compared to the non-obese/non-OSA controls, obese/OSA minipigs showed much lower respiratory tidal volumes and inspiratory airflow speed. FEM simulation found that turbulence was not present in the pharynx in either model. However, a 25% increase of airflow velocity was observed at the narrowest part of the nasal pharynx in the obese/OSA minipig model.

Conclusions

Despite the narrower pharyngeal airway and the higher velocity of airflow, FEM simulation indicated that turbulence was not produced in the obese/OSA minipigs.

Reconstruction of vocal tract geometries from biomechanical simulations

Medical imaging techniques are usually utilized to acquire the vocal tract geometry in 3D, which may then be used, eg, for acoustic/fluid simulation. As an alternative, such a geometry may also be acquired from a biomechanical simulation, which allows to alter the anatomy and/or articulation to study a variety of configurations. In a biomechanical model, each physical structure is described by its geometry and its properties (such as mass, stiffness, and muscles). In such a model, the vocal tract itself does not have an explicit representation, since it is a cavity rather than a physical structure. Instead, its geometry is defined implicitly by all the structures surrounding the cavity, and such an implicit representation may not be suitable for visualization or for acoustic/fluid simulation. In this work, we propose a method to reconstruct the vocal tract geometry at each time step during the biomechanical simulation. Complexity of the problem, which arises from model alignment artifacts, is addressed by the proposed method. In addition to the main cavity, other small cavities, including the piriform fossa, the sublingual cavity, and the interdental space, can be reconstructed. These cavities may appear or disappear by the position of the larynx, the mandible, and the tongue. To illustrate our method, various static and temporal geometries of the vocal tract are reconstructed and visualized. As a proof of concept, the reconstructed geometries of three cardinal vowels are further used in an acoustic simulation, and the corresponding transfer functions are derived.

Simulation of the upper airways in patients with obstructive sleep apnea and nasal obstruction: A novel finite element method

Objective

To evaluate the biomechanical properties of the soft palate and velopharynx in patients with obstructive sleep apnea (OSA) and nasal obstruction.

Study design

Prospective experimental study.

Materials and methods

Two finite element (FE) models of the soft palate were created in six patients undergoing nasal surgery, one homogeneous model based on CT images, and one layered model based on soft tissue composition. The influence of anatomy on displacement caused by a gravitational load and closing pressure were evaluated in both models. The strains in the transverse and longitudinal direction were obtained for each patient.

Results

The individual anatomy influences both its structural stiffness and its gravitational displacement. The soft palate width was the sole anatomical parameter correlated to the critical closing pressure, but the maximal displacement due to gravity may have a relationship to closing pressure of possibly an exponential order. The airway occlusion occurred mainly at the lateral attachments of the soft palate. The total transverse strain showed a strong correlation with maximal closing pressure. There was no relationship between the critical closing pressure and the preoperative AHI levels, or the change in AHI after surgery.

Conclusion

Hyperelastic FE models both in the homogeneous and layered model represent a novel method of evaluating soft tissue biomechanics of the upper airway. The obstruction occurs mainly at the level of the lateral attachments to the pharyngeal wall, and the width of the soft palate is an indicator of the degree of critical closing pressure. A less negative closing pressure corresponds to small total transverse strain. The effect of nasal surgery on OSA is most likely not explained by change in soft palate biomechanics.

Level of Evidence

NA.

Predicting 3D lip movement using facial sEMG: a first step towards estimating functional and aesthetic outcome of oral cancer surgery

In oral cancer, loss of function due to surgery can be unacceptable, designating the tumour as functionally inoperable. Other curative treatments can then be considered. Currently, predictions of these functional consequences are subjective and unreliable. We want to create patient-specific models to improve and objectify these predictions. A first step was taken by controlling a 3D lip model with volunteer-specific sEMG activities. We focus on the lips first, because they are essential for speech, oral food transport, and facial mimicry. Besides, they are more accessible to measurements than intraoral organs. 3D lip movement and corresponding sEMG activities are measured in five healthy volunteers, who performed 19 instructions repeatedly, to create a quantitative lip model by establishing the relationship between sEMG activities of eight facial muscles bilaterally on the input side and the corresponding 3D lip displacements on the output side. The relationship between 3D lip movement and sEMG activities was accommodated in a state-space model. A good relationship between sEMG activities and 3D lip movement was established with an average root mean square error of 2.43 mm for the first-order system and 2.46 mm for the second-order system. This information can be incorporated into biomechanical models to further personalise functional outcome assessment after treatment.