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

Evaluation of breast skin and tissue stiffness using a non-invasive aspiration device and impact of clinical predictors

A personalized 3D breast model could present a real benefit for preoperative discussion with patients, surgical planning, and guidance. Breast tissue biomechanical properties have been poorly studied in vivo, although they are important for breast deformation simulation. The main objective of our study was to determine breast skin thickness and breast skin and adipose/fibroglandular tissue stiffness. The secondary objective was to assess clinical predictors of elasticity and thickness: age, smoking status, body mass index, contraception, pregnancies, breastfeeding, menopausal status, history of radiotherapy or breast surgery. Participants were included at the Montpellier University Breast Surgery Department from March to May 2022. Breast skin thickness was measured by ultrasonography, breast skin and adipose/fibroglandular tissue stiffnesses were determined with a VLASTIC non-invasive aspiration device at three different sites (breast segments I-III). Multivariable linear models were used to assess clinical predictors of elasticity and thickness. In this cohort of 196 women, the mean breast skin and adipose/fibroglandular tissue stiffness values were 39 and 3 kPa, respectively. The mean breast skin thickness was 1.83 mm. Only menopausal status was significantly correlated with breast skin thickness and adipose/fibroglandular tissue stiffness. The next step will be to implement these stiffness and thickness values in a biomechanical breast model and to evaluate its capacity to predict breast tissue deformations.

Applied use of biomechanical measurements from human tissues for the development of medical skills trainers: a scoping review

OBJECTIVE

The objective of this review was to identify quantitative biomechanical measurements of human tissues, the methods for obtaining these measurements, and the primary motivations for conducting biomechanical research.

INTRODUCTION

Medical skills trainers are a safe and useful tool for clinicians to use when learning or practicing medical procedures. The haptic fidelity of these devices is often poor, which may be because the synthetic materials chosen for these devices do not have the same mechanical properties as human tissues. This review investigates a heterogeneous body of literature to identify which biomechanical properties are available for human tissues, the methods for obtaining these values, and the primary motivations behind conducting biomechanical tests.

INCLUSION CRITERIA

Studies containing quantitative measurements of the biomechanical properties of human tissues were included. Studies that primarily focused on dynamic and fluid mechanical properties were excluded. Additionally, studies only containing animal, in silico , or synthetic materials were excluded from this review.

METHODS

This scoping review followed the JBI methodology for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Sources of evidence were extracted from CINAHL (EBSCO), IEEE Xplore, MEDLINE (PubMed), Scopus, and engineering conference proceedings. The search was limited to the English language. Two independent reviewers screened titles and abstracts as well as full-text reviews. Any conflicts that arose during screening and full-text review were mediated by a third reviewer. Data extraction was conducted by 2 independent reviewers and discrepancies were mediated through discussion. The results are presented in tabular, figure, and narrative formats.

RESULTS

Data were extracted from a total of 186 full-text publications. All of the studies, except for 1, were experimental. Included studies came from 33 countries, with the majority coming from the United States. Ex vivo methods were the predominant approach for extracting human tissue samples, and the most commonly studied tissue type was musculoskeletal. In this study, nearly 200 unique biomechanical values were reported, and the most commonly reported value was Young's (elastic) modulus. The most common type of mechanical test performed was tensile testing, and the most common reason for testing human tissues was to characterize biomechanical properties. Although the number of published studies on biomechanical properties of human tissues has increased over the past 20 years, there are many gaps in the literature. Of the 186 included studies, only 7 used human tissues for the design or validation of medical skills training devices. Furthermore, in studies where biomechanical values for human tissues have been obtained, a lack of standardization in engineering assumptions, methodologies, and tissue preparation may implicate the usefulness of these values.

CONCLUSIONS

This review is the first of its kind to give a broad overview of the biomechanics of human tissues in the published literature. With respect to high-fidelity haptics, there is a large gap in the published literature. Even in instances where biomechanical values are available, comparing or using these values is difficult. This is likely due to the lack of standardization in engineering assumptions, testing methodology, and reporting of the results. It is recommended that journals and experts in engineering fields conduct further research to investigate the feasibility of implementing reporting standards.

REVIEW REGISTRATION

Open Science Framework https://osf.io/fgb34.

Identifiability of soft tissue constitutive parameters from in-vivo macro-indentation

Reliable identification of soft tissue material parameters is frequently required in a variety of applications, particularly for biomechanical simulations using finite element analysis (FEA). However, determining representative constitutive laws and material parameters is challenging and often comprises a bottleneck that hinders the successful implementation of FEA. Soft tissues exhibit a nonlinear response and are commonly modeled using hyperelastic constitutive laws. In-vivo material parameter identification, for which standard mechanical tests (e.g., uniaxial tension and compression) are inapplicable, is commonly achieved using finite macro-indentation test. Due to the lack of analytical solutions, the parameters are commonly identified using inverse FEA (iFEA), in which simulated results and experimental data are iteratively compared. However, determining what data must be collected to accurately identify a unique parameter set remains unclear. This work investigates the sensitivities of two types of measurements: indentation force-depth data (e.g., measured using an instrumented indenter) and full-field surface displacements (e.g., using digital image correlation). To eliminate model fidelity and measurement-related errors, we employed an axisymmetric indentation FE model to produce synthetic data for four 2-parameter hyperelastic constitutive laws: compressible Neo-Hookean, and nearly incompressible Mooney-Rivlin, Ogden, and Ogden-Moerman models. For each constitutive law, we computed the objective functions representing the discrepancies in the reaction force, the surface displacement, and their combination, and visualized them for hundreds of parameter sets, spanning a representative range as found in the literature for the bulk soft tissue complex in human lower limbs. Moreover, we quantified three identifiability metrics, which provided insights into the uniqueness (or lack thereof) and the sensitivities. This approach provides a clear and systematic evaluation of the parameter identifiability, which is independent of the selection of the optimization algorithm and initial guesses required in iFEA. Our analysis indicated that the indenter's force-depth data, despite being commonly used for parameter identification, was insufficient for reliably and accurately identifying both parameters for all the investigated material models and that the surface displacement data improved the parameter identifiability in all cases, although the Mooney-Rivlin parameters remained poorly identifiable. Informed by the results, we then discuss several identification strategies for each constitutive model. Finally, we openly provide the codes used in this study, to allow others to further investigate the indentation problem according to their specifications (e.g., by modifying the geometries, dimensions, mesh, material models, boundary conditions, contact parameters, or objective functions).

A review of the characterizations of soft tissues used in human body modeling: Scope, limitations, and the path forward

Soft tissue material properties are vital to human body models that evaluate interactions between the human body and its environment. Such models evaluate internal stress/strain responses in soft tissues to investigate issues like pressure injuries. Numerous constitutive models and parameters have been used to represent mechanical behavior of soft tissues in biomechanical models under quasi-static loading. However, researchers reported that generic material properties cannot accurately represent specific target populations due to large inter-individual variability. Two challenges that exist are experimental mechanical characterization and constitutive modeling of biological soft tissues and personalization of constitutive parameters using non-invasive, non-destructive bedside testing methods. It is imperative to understand the scope and appropriate applications for reported material properties. Thus, the goal of this paper was to compile studies from which soft tissue material properties were obtained and categorize them by source of tissue samples, methods used to quantify deformation, and material models used to describe tissues. The collected studies displayed wide ranges of material properties, and factors that affected the properties included whether tissue samples were in vivo or ex vivo, from humans or animals, the body region tested, body position during in vivo studies, deformation measurements, and material models used to describe tissues. Because of the factors that affected reported material properties, it is clear that much progress has been made in understanding soft tissue responses to loading, yet there is a need to broaden the scope of reported soft tissue material properties and better match reported properties to appropriate human body models.

A review of upper airway physiology relevant to the delivery and deposition of inhalation aerosols

Developing effective oral inhaled drug delivery treatment strategies for respiratory diseases necessitates a thorough knowledge of the respiratory system physiology, such as the differences in the airway channel's structure and geometry in health and diseases, their surface properties, and mechanisms that maintain their patency. While respiratory diseases, such as chronic obstructive pulmonary disease (COPD) and asthma and their implications on the lower airways have been the core focus of most of the current research, the role of the upper airway in these diseases is less known, especially in the context of inhaled drug delivery. This is despite the fact that the upper airway is the passageway for inhaled drugs to be delivered to the lower airways, and their replicas are indispensable in current standards, such as the cascade impactor experiments for testing inhaled drug delivery technology. This review provides an overview of upper airway collapsibility and their mechanical properties, the effects of age and gender on upper airway geometry, and surface properties. The review also discusses how COPD and asthma affect the upper airway and the typical inhalation flow characteristics exhibited by the patients with these diseases.

In vivo measurement of breast tissues stiffness using a light aspiration device

BACKGROUND

This paper addresses the question of the in vivo measurement of breast tissue stiffness, which has been poorly adressed until now, except for elastography imaging which has shown promising results but which is still difficult for clinicians to use on a day-to-day basis. Estimating subject-specific tissue stiffness is indeed a critical area of research due to the development of a large number of Finite Element (FE) breast models for various medical applications.

METHODS

This paper proposes to use an original aspiration device, put into contact with breast surface, and to estimate tissue stiffness using an inverse analysis of the aspiration experiment. The method assumes that breast tissue is composed of a bilayered structure made of fatty and fribroglandular tissues (lower layer) superimposed with the skin (upper layer). Young moduli of both layers are therefore estimated based on repeating low intensity suction tests (<40 mbar) of breast tissues using cups of 7 different diameters.

FINDINGS

Seven volunteers were involved in this pilot study with average Young moduli of 56.3 kPa  ± 16.4 and 3.04 kPa  ± 1.17 respectively for the skin and the fatty and fibroglandular tissue. The measurements were carried out in a reasonable time scale (<60 min in total) without any discomfort perceived by the participants. These encouraging results should be confirmed in a clinical study that will include a much larger number of volunteers and patients.

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.