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Foreign bodies in soft tissues are commonly encountered in daily orthopaedic practice. While most of the metals and glass foreign bodies can be detected by plain radiograph, organic substances such as wood and vegetative materials are radiolucent. Unfortunately, these radiolucent foreign bodies are usually more prone to cause an inflammatory reaction and infection. The detection can be even more difficult in cases of multiple foreign bodies and in penetrating injuries with small innocuous skin wounds. Ultrasonography is a sensitive and reliable investigation for detection of foreign bodies in soft tissue. We present a case of penetration injury to thumb with residual radiolucent foreign bodies and demonstrate the proper role of ultrasonography in the management of foreign bodies in soft tissues.

Elasticity problems can be formulated into partial differential equations while analyzing the behavior of fluid-structure coupled problems. The current focus is to study the perfusion and instantaneous material property change in the soft tissues such as myocardium, which is analyzed due to the varying stiffness conditions. The analysis performed has considered physiological range loading conditions.

Intracranial saccular aneurysms tend to be thin walled and stiffer compared with a normal artery. The current work describes computational structural dynamics (CSD) in an anatomically realistic model of a cerebral aneurysm located in the ophthalmic region, using different wall thickness, model data for the artery and aneurysm, and geometry size. The model was obtained from three-dimensional rotational angiography image data. The wall was assumed three-dimensional hyperelastic solid with different thickness in the artery and in the aneurysm regions. The effects of carotid siphon length are reported. The CSD was solved with the finite elements package ADINA. The predictions of stress and strain on the aneurysm wall were compared.

The walls of the blood vessels involved with cerebral aneurysms present different mechanical properties, when compared with those of normal artery. Consequently the models which may describe then predict an aneurysm rupture need as input their mechanical properties. This paper describes the experimental determination of the mechanical properties of the tissues of the blood vessels affected with a cerebral aneurysm. In particular, we determine and discuss the critical elongation and the rupture strength. The affected tissues were obtained from surgical clipping and extraction; six specimens were tested. The mechanical tests were performed in a tensile device. The experimental data was fitted numerically with a Mooney–Rivlin hyper elastic model. The model was compared with previous published data.

This study used biomechanical models of soft tissues based on combined exponential and polynomial models. Finite element methods were used to solve material nonlinear and geometrically nonlinear problems of soft tissue models. This involved assigning a screening coefficient in the model-accelerated computing process to filter the units involved in the calculation. The screening coefficient controlled both the accuracy of the results of simulation and the computing speed through setting up a subset of finite elements. The fast computer method based on the screening coefficient was applied to the rectus femoris simulation.

According to the vibration characteristics of the round window membrane, a mechanical model that contains round window membrane and the soft tissue is established. The Euler equation of the whole of round window membrane and the soft tissue and the complementary boundary conditions are derived by the variational principle. Combined with the Bessel function, the analytical solution of the total displacement of round window membrane and the soft tissue is obtained by using Mathematica. The results are in good agreement with experimental data, which confirms the validity of the analytical solution of the model. At the same time, the effect of different thicknesses and different elastic modulus of soft tissue on the total displacement of round window membrane and soft tissue is studied by analytical method. The results show that with the thickening of the soft tissue, the total displacement of round window membrane and the soft tissue decreased gradually. However, with the decrease of elastic modulus of the soft tissue, the total displacement of round window membrane and the soft tissue increased gradually. Furthermore, the relationship between thickness and elastic modulus of the soft tissue and the corresponding range selection is achieved, which can evaluate the transmission performance of round window membrane efficiently and provide theoretical basis for the reverse excitation of artificial prosthesis.

Finite element fingertip models are useful tools to assess product ergonomics. While “real geometry” approaches provide accurate results, developing models requires medical images. “Simpified geometry” approaches have to date not been tested to see whether they can provide equally accurate results in terms of mechanical response, i.e. force-displacement response and dimensions of fingertip contact area. Four fingertip models were built either from medical images (Visible Human project) or from simplified geometries. Simulations of fingertip flat contact compression at 20${}^{\circ }$ were performed. A 2nd order hyperelastic material property was used to effectively reproduce the mechanical behavior of the fingertip. Models based on simplified geometries such as conics proved as accurate as models reconstructed from medical images. However, accurate positioning of the bony phalanx is paramount if a biofidelic mechanical response is to be reproduced.

The use of finite element models has gained popularity in the field of foot and footwear biomechanics to predict the stress–strain distribution and the treatment effectiveness of therapeutic insoles for pathological foot conditions. However, a comprehensive evaluation of mesh quality is often ignored, meanwhile no golden standard exists for the mesh density and selection of element size at an acceptable accuracy. Here, we make a convergence test and established anatomically-realistic foot models at different mesh densities. The study compared the discrepancy in output variables to the changes of element type and mesh density under barefoot and footwear conditions with compressive and shear loads, which are commonly encountered in foot and footwear biomechanics simulations. For a range of loading conditions simulated in 125 finite element models, the peak plantar pressure consistently converged with optimal mesh size determined at 2.5mm. The convergence variable of principal strains and stress tensors, however, varies significantly. The max von-Mises stress showed strong sensitive behavior to the changes of the mesh density. The pattern for contact pressure distribution became less accurate when the element sizes increase to 6.0mm; in particular, the locations of the pressure peak do not show remarkable changes, but the size of the area of contact still changes. The current study could offer a general guideline when generating a reasonable accurate finite element models for the analysis of plantar pressure distributions and stress/strain states employed for foot and footwear biomechanics evaluations.

Soft tissue is an important operation object in robot-assisted surgery and its mechanical response is of great significance to the precision of surgical operation. Accurate prediction of soft tissue mechanical properties can effectively avoid the potential damage of biological tissue caused by excessive operating force. In this paper, three typical mechanical responses of soft tissue were obtained by no-slip compression experiments of liver tissue. Second, the prediction model of soft tissue mechanical response based on gray prediction was established, and the influence of key parameters of the model on the precision of mechanical response prediction was analyzed. The results show that the gray prediction model can accurately predict the mechanical response of soft tissue, and the prediction accuracy is the highest when the number of historical data is 7. The prediction method of soft tissue mechanical response proposed in this paper will provide important data reference for accurate operation of surgery.

Background: Lower Back Pain (LBP) with radiculopathy is a potentially more serious form of mechanical low back pain. A paucity of literature exists about the effect of the gross myofascial release (MFR) technique on the management of LBP.

Objective: The study aimed to evaluate the effect of gross MFR when given as an adjunct to conventional physical therapy in subjects with low back pain with radiculopathy.

Methods: Forty subjects ($n=40$) clinically diagnosed with LBP with radiculopathy were enrolled and randomly allocated to either the control group ($n=20$) or the experimental group ($n=20$). Both study groups received 5 sessions of intervention. The control group received conventional physical therapy while the experimental group received gross MFR of the trunk and lower limb along with conventional physical therapy. The outcome measures included were pressure pain threshold for the lower back and lower extremity, lumbar flexion and extension range of motion (ROM), percentage disability, and patient satisfaction towards the treatment which were measured pre-intervention (day 1) and post-treatment (day 5). The interaction between group and time was analysed using two-way mixed ANOVA.

Results: The results suggested that the experimental group was statistically significant over the control group in terms of pressure pain threshold in the lower back ($p<0.001$) and lower limb ($p=0.003$), disability ($p<0.001$), and patient satisfaction ($p=0.034$) and lumbar flexion ($p=0.002$) except lumbar extension ROM ($p=0.973$).

Conclusion: When given as an adjuvant to conventional physical therapy, gross myofascial release proved to provide a significant and faster short-term improvement over conventional treatment alone in subjects diagnosed with low back pain with radiculopathy.

Medical image analysis gains huge advancements with deep learning approaches which boosts the computational capability and accurate prediction. An expert in the field analyzes the feature representation, and an intelligent model helps to categorize and forecast diseases. The MRI images from cancer imaging archives are used to give a novel learning approach for soft tissue diagnosis. This work suggests a Type-2 fuzzy model that chooses local and maximum absolute value to handle the data. According to the experimental investigation, the predicted model works better than several current strategies. Deep convolutional neural networks built on the VGG-16 architecture and the Adam optimizers are used to pre-train the proposed model. The classification accuracy is anticipated based on the experimentation, demonstrating the need for complementary information for learning systems. The goal is to forecast the depth of knowledge extraction by boosting pre-trained CNN’s ability to be fine-tuned by improving the accuracy of soft tissue classification. The proposed model improves performance and validates the significance of the network model by categorizing the tissues as benign or cancerous. The proposed model attains 96.8% accuracy and 9% for depths of 5 and 8 mm and 93% for 10 mm. Similarly, the model attains 96.8% without inclusion, 100% with inclusion and an average outcome of 99%.

Background: Soft tissue sarcomas (STS) are rare, and little is known about the factors that affect the delays in the initial treatment. The aim of this study is to quantify the period between onset of symptoms and start of treatment of STS and determine the factors affecting delays in initial treatment.

Methods: This is a retrospective study of all STS treated in our institution between October 2009 and March 2019. We analysed patient record to determine the period from onset of symptoms to start of initial treatment. We also collected data with regard to patient characteristics and features of the tumour. Tumours were classified into upper extremity, lower extremity, trunk and others based on location of the tumour. Statistical tests were done to identify factors that affected delay in initial treatment.

Results: The study included 134 patients (76 male and 58 female) with STS with an average age of 56.6 years. The tumours involved the upper extremity in 20 patients, lower extremity and trunk in 50 patients each and other areas in 14 patients. The most frequent histological subtypes were liposarcomas (n = 31, 23.5%) and undifferentiated pleomorphic sarcomas (n = 24, 18.2%). Initial treatment was delayed by an average of 9.9 months for all groups. The period of treatment delay for tumours involving the upper extremity was shorter (7.9 months) and these tumours were smaller at initial presentation (57.6 mm) compared to tumours in other locations (p < 0.05). Other factors that were positively associated with treatment delays were a history of diabetes mellitus (p = 0.037) and smoking (p = 0.026).

Conclusion: Patients with upper-extremity STS may have the benefit of a relatively better prognosis as they present earlier and with a smaller tumour. In addition, factors, such as diabetes and smoking, which indicate a low interest in health also influenced the delay in the initial treatment.

Level of Evidence: Level III (Therapeutic)

This paper presents the concept of a technology for the automation of laser incisions on soft tissue, especially for application in Transoral Laser Microsurgery (TLM) interventions. The technology aims at automatically controlling laser incisions based on high-level commands from the surgeon, i.e. desired incision shape, length and depth. It is based on a recently developed robotic laser microsurgery platform, which offers the controlled motion of the laser beam on the surgical site. A feed-forward controller provides (i) commands to the robotic laser aiming system and (ii) regulates the parameters of the laser source to achieve the desired results. The controller for the incision depth is extracted from experimental data. The required energy density and the number of passes are calculated to reach the targeted depth. Experimental results demonstrate that targeted depths can be achieved with $\pm 100\mu$m accuracy, which proves the feasibility of this approach. The proposed technology has the potential to facilitate the surgeon’s control over laser incisions.

A decade ago, the so-called Kröner-Lee decomposition—primarily introduced to discern between elastic and (visco-)plastic strains—was given a broader scope and a deeper interpretation than the original ones, as describing the interplay between the actual and the relaxed configuration of each body element. The main intended application was to growth mechanics of soft living tissues. In 2002, a novel (tensorial) balance law governing the time evolution of the relaxed configuration was devised, and endowed with a proper constitutive theory, thus establishing the foundations of a dynamical theory of material remodelling.

Material remodelling does not describe explicitly the chemistry or whatever else is acting behind the changes in material structure. However, it does account explicitly for the power expended by the biochemical control system, which is of the essence for modelling the mechanics of living tissue. Material remodelling discriminates active from passive remodelling, while treating both on the same footing. Thus it provides mechanistic models of living materials without conceiving of them as inert materials engineered with magic constitutive recipes. The present study develops a toy model of saccular aneurysms, focussing on the two-way coupling between growth and stress.

Young's modulus and Poisson's ratio are the important parameters for representing the mechanical properties of soft tissue. Indentation test is an in vivo, non-invasive and convenient technique for measuring the tissue properties. In this chapter, two methods for the simultaneous estimation of Young's modulus and Poisson's ratio of soft tissues using indentation are presented. With the consideration of the finite deformation effect, the first method is based on the use of two sized indentors for conducting two different indentation tests, whereas the second one is only a single indentation test. Finite element (FE) analysis was used to demonstrate the feasibility of these two methods. The FE results were found to be comparable to the one shown in the previous literatures. It was revealed that finite deformation effect is of vital importance in the estimation of the Young's modulus and Poisson's ratio. Simultaneous estimation of these two parameters is necessary for achieving an accurate measurement of the Young's modulus.