A hyperelastic model to capture the mechanical behaviour and histological aspects of the soft tissues

SymTC: A symbiotic Transformer-CNN net for instance segmentation of lumbar spine MRI

Intervertebral disc disease, a prevalent ailment, frequently leads to intermittent or persistent low back pain, and diagnosing and assessing of this disease rely on accurate measurement of vertebral bone and intervertebral disc geometries from lumbar MR images. Deep neural network (DNN) models may assist clinicians with more efficient image segmentation of individual instances (discs and vertebrae) of the lumbar spine in an automated way, which is termed as instance image segmentation. In this work, we proposed SymTC, an innovative lumbar spine MR image segmentation model that combines the strengths of Transformer and Convolutional Neural Network (CNN). Specifically, we designed a parallel dual-path architecture to merge CNN layers and Transformer layers, and we integrated a novel position embedding into the self-attention module of Transformer, enhancing the utilization of positional information for more accurate segmentation. To further improve model performance, we introduced a new data synthesis technique to create synthetic yet realistic MR image dataset, named SSMSpine, which is made publicly available. We evaluated our SymTC and the other 16 representative image segmentation models on our private in-house dataset and public SSMSpine dataset, using two metrics, Dice Similarity Coefficient and the 95th percentile Hausdorff Distance. The results indicate that SymTC surpasses the other 16 methods, achieving the highest dice score of 96.169 % for segmenting vertebral bones and intervertebral discs on the SSMSpine dataset. The SymTC code and SSMSpine dataset are publicly available at https://github.com/jiasongchen/SymTC.

In vitro biomechanical properties of porcine perineal tissues to better understand human perineal tears during delivery

INTRODUCTION

Data concerning the mechanical properties of the perineum during delivery are very limited. In vivo experiments raise ethical issues. The aim of the study was to describe some of the biomechanical properties of each perineal tissue layer collected from sows in order to better understand perineal tears during childbirth.

MATERIAL AND METHODS

Samples of each perineal tissue layer were obtained from the skin, the vagina, the external anal sphincter (EAS), the internal anal sphincter (IAS), and the anal mucosa of fresh dead sows. They were tested in quasi-static uniaxial tension using the testing machine Mach-1®. Tests were performed at a displacement velocity of 0.1 mm·s-1. Stress-strain curves of each perineal tissue layer before the first damage for each sow were obtained and modeled using a hyperelastic Yeoh model described by three coefficients: C1, C2, and C3. Pearson correlation coefficients were calculated to measure the correlation between the C1 hyperelastic coefficient and the duration between the first microfailure and the complete rupture for each perineal tissue layer. Pearson correlation was computed between C1 and the number of microfailures before complete rupture for each tissue.

RESULTS

Ten samples of each perineal tissue layer were analyzed. Mean values of C1 and corresponding standard deviations were 46 ± 15, 165 ± 60, 27 ± 10, 19 ± 13, 145 ± 28 kPa for the perineal skin, the vagina, the EAS, the IAS, and the anal mucosa, respectively. According to this same sample order, the first microfailure in the population of 10 sows appeared at an average of 54%, 27%, 70%, 131%, and 22% of strain. A correlation was found between C1 hyperelastic coefficient and the duration between the first microfailure and the complete rupture (r = 0.7, p = 0.02) or the number of microfailures before complete rupture only for the vagina (r = 0.7, p = 0.02).

CONCLUSIONS

In this population of fresh dead sow's perineum, the vagina and the anal mucosa were the stiffest tissues. The IAS and EAS were more extensible and less stiff. A significantly positive correlation was found between C1 and the duration between the first microfailure and the complete rupture of the vagina, and the duration between the first microfailure and the complete rupture of the vagina.

Towards the biomechanical modelling of the behaviour of ex-vivo porcine perineal tissues

The perineum is a layered soft tissue structure with mechanical properties that maintain the integrity of the pelvic floor. During childbirth, the perineum undergoes significant deformation that often results in tears of various degrees of severity. To better understand the mechanisms underlying perineal tears, it is crucial to consider the mechanical properties of the different tissues that make up the perineum. Unfortunately, there is a lack of data on the mechanical properties of the perineum in the literature. The objective of this study is to partly fill these gaps. Hence sow perineums were dissected and the five perineal tissues involved in tears were characterized by uniaxial tension tests: Skin, Vagina, External Anal Sphincter, Internal Anal Sphincter and Anal Mucosa. From our knowledge, this study is the first to investigate all these tissues and to design a testing protocol to characterize their material properties. Six material models were used to fit the experimental data and the correlation between experimental and predicted data was evaluated for comparison. As a result, even if the tissues are of different nature, the best correlation was obtained with the Yeoh and Martins material models for all tissues. Moreover, these preliminary results show the difference in stiffness between the tissues which indicates that they might have different roles in the structure. These obtained results will serve as a basis to design an improved experimental protocol for a more robust structural model of the porcine perineum that can be used for the human perineum to predict perineal tears.

Biomechanics of the Human Osteochondral Unit: A Systematic Review

The damping system ensured by the osteochondral (OC) unit is essential to deploy the forces generated within load-bearing joints during locomotion, allowing furthermore low-friction sliding motion between bone segments. The OC unit is a multi-layer structure including articular cartilage, as well as subchondral and trabecular bone. The interplay between the OC tissues is essential in maintaining the joint functionality; altered loading patterns can trigger biological processes that could lead to degenerative joint diseases like osteoarthritis. Currently, no effective treatments are available to avoid degeneration beyond tissues' recovery capabilities. A thorough comprehension on the mechanical behaviour of the OC unit is essential to (i) soundly elucidate its overall response to intra-articular loads for developing diagnostic tools capable of detecting non-physiological strain levels, (ii) properly evaluate the efficacy of innovative treatments in restoring physiological strain levels, and (iii) optimize regenerative medicine approaches as potential and less-invasive alternatives to arthroplasty when irreversible damage has occurred. Therefore, the leading aim of this review was to provide an overview of the state-of-the-art-up to 2022-about the mechanical behaviour of the OC unit. A systematic search is performed, according to PRISMA standards, by focusing on studies that experimentally assess the human lower-limb joints' OC tissues. A multi-criteria decision-making method is proposed to quantitatively evaluate eligible studies, in order to highlight only the insights retrieved through sound and robust approaches. This review revealed that studies on human lower limbs are focusing on the knee and articular cartilage, while hip and trabecular bone studies are declining, and the ankle and subchondral bone are poorly investigated. Compression and indentation are the most common experimental techniques studying the mechanical behaviour of the OC tissues, with indentation also being able to provide information at the micro- and nanoscales. While a certain comparability among studies was highlighted, none of the identified testing protocols are currently recognised as standard for any of the OC tissues. The fibril-network-reinforced poro-viscoelastic constitutive model has become common for describing the response of the articular cartilage, while the models describing the mechanical behaviour of mineralised tissues are usually simpler (i.e., linear elastic, elasto-plastic). Most advanced studies have tested and modelled multiple tissues of the same OC unit but have done so individually rather than through integrated approaches. Therefore, efforts should be made in simultaneously evaluating the comprehensive response of the OC unit to intra-articular loads and the interplay between the OC tissues. In this regard, a multidisciplinary approach combining complementary techniques, e.g., full-field imaging, mechanical testing, and computational approaches, should be implemented and validated. Furthermore, the next challenge entails transferring this assessment to a non-invasive approach, allowing its application in vivo, in order to increase its diagnostic and prognostic potential.

In-silico simulation of nanoindentation on bone using a 2D cohesive finite element model

This study proposed and validated a 2D finite element (FE) model for conducting in-silico simulations of in-situ nanoindentation tests on mineralized collagen fibrils (MCF) and the extrafibrillar matrix (EFM) within human cortical bone. Initially, a multiscale cohesive FE model was developed by adapting a previous model of bone lamellae, encompassing both MCF and EFM. Subsequently, nanoindentation tests were simulated in-silico using this model, and the resulting predictions were compared to AFM nanoindentation test data to verify the model's accuracy. The FE model accurately predicted nanoindentation results under wet conditions, closely aligning with outcomes obtained from AFM nanoindentation tests. Specifically, it successfully mirrored the traction/separation curve, nanoindentation modulus, plastic energy dissipation, and plastic energy ratio obtained from AFM nanoindentation tests. Additionally, this in-silico model demonstrated its ability to capture alterations in nanoindentation properties caused by the removal of bound water, by considering corresponding changes in mechanical properties of the collagen phase and the interfaces among bone constituents. Notably, significant changes in the elastic modulus and plastic energy dissipation were observed in both MCF and EFM compartments of bone, consistent with observations in AFM nanoindentation tests. These findings indicate that the proposed in-silico model effectively captures the influence of ultrastructural changes on bone's mechanical properties at sub-lamellar levels. Presently, no experimental methods exist to conduct parametric studies elucidating the ultrastructural origins of bone tissue fragility. The introduction of this in-silico model presents an invaluable tool to bridge this knowledge gap in the future.

Stress Concentration on PDMS: An evaluation of three numerical constitutive models using digital image correlation

The examination of hyperelastic materials' behavior, such as polydimethylsiloxane (PDMS), is crucial for applications in areas as biomedicine and electronics. However, the limitations of hyperelastic models for specific stress scenarios, with stress concentration, are not well explored on the literature. To address this, firstly, three constitutive models were evaluated (Neo-Hookean, Mooney-Rivlin, and Ogden) using numerical simulations and Digital Image Correlation (DIC) analysis during a uniaxial tensile test. The samples were made of PDMS with stress concentration geometries (center holes, shoulder fillets, and edge notches). Results of ANOVA analysis showed that any of the three models can be chosen for numerical analysis of PDMS since no significant differences in suitability were found. Finally, the Ogen model was chosen to obtain the stress concentration factors for these geometries, a property which characterize how discontinuities change the maximum stress supported by an element. Our study provides new values for variables needed to analyze and design hyperelastic elements and produce a foundation for understanding PDMS stress-strain behavior.

The multiscale characterization and constitutive modeling of healthy and type 2 diabetes mellitus Sprague Dawley rat skin

In type 2 diabetes mellitus (T2DM), elevated glucose level impairs the biochemistry of the skin which may result in alteration of its mechanical and structural properties. The several aspects of structural and mechanical changes in skin due to T2DM remain poorly understood. To fill these research gaps, we developed a non-obese T2DM rat (Sprague Dawley (SD)) model for investigating the effect of T2DM on the in vivo strain stress state, mechanical and structural properties of skin. In vivo strain and mechanical anisotropy of healthy and T2DM skin were measured using the digital imaging correlation (DIC) technique and DIC coupled bulge experiment, respectively. Fluorescence microscopy and histology were used to assess the collagen and elastin fibers microstructure whereas nanoscale structure was captured through atomic force microscopy (AFM). Based on the microstructural observations, skin was modeled as a multilayer membrane where in and out of plane distribution of collagen fibers and planar distribution of elastin fibers were cast in constitutive model. Further, the state of in vivo stresses of healthy and T2DM were measured using model parameters and in vivo strain in the constitutive model. The results showed that T2DM causes significant loss in in vivo stresses (p < 0.01) and increase in anisotropy (p < 0.001) of skin. These changes were found in good correlation with T2DM associated alteration in skin microstructure. Statistical analysis emphasized that increase in blood glucose concentration (HbA1c) was the main cause of impaired biomechanical properties of skin. The presented data in this study can help to understand the skin pathology and to simulate the skin related clinical procedures. STATEMENT OF SIGNIFICANCE: Our study is significant as it presents findings related to the effect of T2DM on the physiologic stress strain, structural and mechanical response of SD rat skin. In this study, we developed a non-obese T2DM SD rat model which mimics the phenotype of Asian type 2 diabetics (non-obese). Several structural and mechanical characterization techniques were explored for multiscale characterization of healthy and T2DM skin. Further, based on microstructural information, we presented the constitutive models that incorporate the real microstructure of skin. The presented results can be helpful to simulate the realistic mechanical response of skin during various clinical trials.

Maximum likelihood-based extended Kalman filter for soft tissue modelling

Realistic modelling of human soft tissue is very important in medical applications. This paper proposes a novel method by dynamically incorporating soft tissue characterisation in the process of soft tissue modelling to increase the modelling fidelity. This method defines nonlinear tissue deformation with unknown mechanical properties as a problem of nonlinear filtering identification to dynamically identify mechanical properties and further estimate nonlinear deformation behaviour of soft tissue. It combines maximum likelihood theory, nonlinear filtering and nonlinear finite element method (NFEM) for modelling of nonlinear tissue deformation behaviour based on dynamic identification of homogeneous tissue properties. On the basis of hyperelasticity, a nonlinear state-space equation is established by discretizing tissue deformation through NFEM for dynamic filtering. A maximum likelihood algorithm is also established to dynamically identify tissue mechanical properties during the deformation process. Upon above, a maximum likelihood-based extended Kalman filter is further developed for dynamically estimating tissue nonlinear deformation based on dynamic identification of tissue mechanical properties. Simulation and experimental analyses reveal that the proposed method not only overcomes the NFEM limitation of expensive computations, but also absorbs the NFEM merit of high accuracy for modelling of homogeneous tissue deformation. Further, the proposed method also effectively identifies tissue mechanical properties during the deformation modelling process.

Effect of collagen fibre orientation on the Poisson's ratio and stress relaxation of skin: an ex vivo and in vivo study

During surgical treatment skin undergoes extensive deformation, hence it must be able to withstand large mechanical stresses without damage. Therefore, understanding the mechanical properties of skin becomes important. A detailed investigation on the relationship between the three-dimensional deformation response of skin and its microstructure is conducted in the current study. This study also discloses the underlying science of skin viscoelasticity. Deformation response of skin is captured using digital image correlation, whereas micro-CT, scanning electron microscopy and atomic force microscopy are used for microstructure analysis. Skin shows a large lateral contraction and expansion (auxeticity) when stretched parallel and perpendicular to the skin tension lines, respectively. Large lateral contraction is a result of fluid exudation from the tissue, while large rotation of the stiff collagen fibres in the loading direction explains the skin auxeticity. During stress relaxation, lateral contraction and fluid effluxion from skin reveal that tissue volume loss is the intrinsic science of skin viscoelasticity. Furthermore, the results obtained from in vivo study on human skin show the relevance of the ex vivo study to physiological conditions and stretching of the skin during its treatments.