An adaptive finite element model for steerable needles

Kirchhoff's law-based velocity-controlled motion models to predict real-time cutting forces in minimally invasive surgeries

A theoretical framework, united by a "system effect" is formulated to model the cutting/haptic force evolution at the cutting edge of a surgical cutting instrument during its penetration into soft biological tissue in minimally invasive surgery. Other cutting process responses, including tissue fracture force, friction force, and damping, are predicted by the model as well. The model is based on a velocity-controlled formulation of the corresponding equations of motion, derived for a surgical cutting instrument and tissue based on Kirchhoff's fundamental energy conservation law. It provides nearly zero residues (absolute errors) in the equations of motion balances. In addition, concurrent closing relationships for the fracture force, friction coefficient, friction force, process damping, strain rate function (a constitutive tissue model), and their implementation within the proposed theoretical framework are established. The advantage of the method is its ability to make precise real-time predictions of the aperiodic fluctuating evolutions of the cutting forces and the other process responses. It allows for the robust modeling of the interactions between a medical instrument and a nonlinear viscoelastic tissue under any physically feasible working conditions. The cutting process model was partially qualitatively verified through numerical simulations and by comparing the computed cutting forces with experimentally measured values during robotic uniaxial biopsy needle constant velocity insertion into artificial gel tissue, obtained from previous experimental research. The comparison has shown a qualitatively similar adequate trend in the evolution of the experimentally measured and numerically predicted cutting forces during insertion of the needle.

Numerical Study of Crack Prediction and Growth in Automotive Wheel Rims

Finite element analysis has become an essential tool for simulating and understanding crack growth. This technique holds significant importance in the field of mechanical engineering, where it finds wide application in the design and optimization of structural components and material properties. This work began with the identification of critical zones and estimated the number of load life repeats through fatigue analysis, specifically applied to automotive rims utilizing innovative finite element methods. To investigate crack behavior, we are used the Extended Finite Element Method (XFEM) with the volumetric approach to compute the Stress Intensity Factor (SIF). The results obtained by our study align closely with experimental tests in terms of detecting the critical zone where a crack can appear. Our findings contribute to the understanding of fatigue behavior in automotive rims, offering new insights into their structural integrity and performance under various load conditions.

Electro-localization method using a muscle conductive phantom for needle position detection towards medical training

Simulation in healthcare can help train, improve, and evaluate medical personnel's skills. In the case of needle insertion/manipulation inside the muscle during an nEMG examination, a training simulator Requires estimating the position of the needle to output the electrical muscle activity in real time according to the training plan. External cameras can be used to estimate the needle location; however, different error sources can make its implementation difficult and new medical sensing technologies are needed. This study introduces and demonstrates the feasibility of a conductive phantom that serves as the medium for needle insertion and senses the 3D needle position based on a technique named electro-localization for the first time. The proposed conductive phantom is designed so that different voltage distributions are generated in the phantom using electrodes placed on its borders. The needle is inserted in the phantom, and the recorded voltages are mapped to spatial coordinates using a finite element method (FEM)-based computational model of the conductive phantom to estimate the 3D needle tip position. Experimental and simulation results of phantom voltage distributions agreed. In 2D mapping (no depth consideration), the needle position error was 1.7 mm, which was marginally reduced if only the central area of the phantom was used (1.5 mm). In 3D mapping, the error was 4 mm. This study showed the feasibility of using a conductive muscle phantom as a new embedded sensor that estimates needle position for medical training of nEMG without relying on external sensors.

Puncturing of soft tissues: experimental and fracture mechanics-based study

The integrity of soft materials against puncturing is of great relevance for their performance because of the high sensitivity to local rupture caused by rigid sharp objects. In this work, the mechanics of puncturing is studied with respect to a sharp-tipped rigid needle with a circular cross section, penetrating a soft target solid. The failure mode associated with puncturing is identified as a mode-I crack propagation, which is analytically described by a two-dimensional model of the target solid, taking place in a plane normal to the penetration axis. It is shown that the force required for the onset of needle penetration is dependent on two energy contributions, that are, the strain energy stored in the target solid and the energy consumed in crack propagation. More specifically, the force is found to be dependent on the fracture toughness of the material, its stiffness and the sharpness of the penetrating tool. The reference case within the framework of small strain elasticity is first investigated, leading to closed-form toughness parameters related to classical linear elastic fracture mechanics. Then, nonlinear finite element analyses for an Ogden hyperelastic material are presented. Supporting the proposed theoretical framework, a series of puncturing experiments on two commercial silicones is presented. The combined experimental-theoretical findings suggest a simple, yet reliable tool to easily handle and assess safety against puncturing of soft materials.

Optimizing autoinjector devices using physics-based simulations and Gaussian processes

Autoinjectors are becoming a primary drug delivery option to the subcutaneous space. These devices need to work robustly and autonomously to maximize drug bio-availability. However, current designs ignore the coupling between autoinjector dynamics and tissue biomechanics. Here we present a Bayesian framework for optimization of autoinjector devices that can account for the coupled autoinjector-tissue biomechanics and uncertainty in tissue mechanical behavior. The framework relies on replacing the high fidelity model of tissue insertion with a Gaussian process (GP). The GP model is accurate yet computationally affordable, enabling a thorough sensitivity analysis that identified tissue properties, which are not part of the autoinjector design space, as important variables for the injection process. Higher fracture toughness decreases the crack depth, while tissue shear modulus has the opposite effect. The sensitivity analysis also shows that drug viscosity and spring force, which are part of the design space, affect the location and timing of drug delivery. Low viscosity could lead to premature delivery, but can be prevented with smaller spring forces, while higher viscosity could prevent premature delivery while demanding larger spring forces and increasing the time of injection. Increasing the spring force guarantees penetration to the desired depth, but it can result in undesirably high accelerations. The Bayesian optimization framework tackles the challenge of designing devices with performance metrics coupled to uncertain tissue properties. This work is important for the design of other medical devices for which optimization in the presence of material behavior uncertainty is needed.

Insights into Infusion-Based Targeted Drug Delivery in the Brain: Perspectives, Challenges and Opportunities

Targeted drug delivery in the brain is instrumental in the treatment of lethal brain diseases, such as glioblastoma multiforme, the most aggressive primary central nervous system tumour in adults. Infusion-based drug delivery techniques, which directly administer to the tissue for local treatment, as in convection-enhanced delivery (CED), provide an important opportunity; however, poor understanding of the pressure-driven drug transport mechanisms in the brain has hindered its ultimate success in clinical applications. In this review, we focus on the biomechanical and biochemical aspects of infusion-based targeted drug delivery in the brain and look into the underlying molecular level mechanisms. We discuss recent advances and challenges in the complementary field of medical robotics and its use in targeted drug delivery in the brain. A critical overview of current research in these areas and their clinical implications is provided. This review delivers new ideas and perspectives for further studies of targeted drug delivery in the brain.

Fracture behaviour of human skin in deep needle insertion can be captured using validated cohesive zone finite-element method

Medical needles have shown an appreciable contribution to the development of novel medical devices and surgical technologies. A better understanding of needle-skin interactions can advance the design of medical needles, modern surgical robots, and haptic devices. This study employed finite element (FE) modelling to explore the effect of different mechanical and geometrical parameters on the needle's force-displacement relationship, the required force for the skin puncture, and generated mechanical stress around the cutting zone. To this end, we established a cohesive FE model, and identified its parameters by a three-stage parameter identification algorithm to closely replicate the experimental data of needle insertion into the human skin available in the literature. We showed that a bilinear cohesive model with initial stiffness of 5000 MPa/mm, failure traction of 2 MPa, and separation length of 1.6 mm can lead to a model that can closely replicate experimental results. The FE results indicated that while the coefficient of friction between the needle and skin substantially changes the needle reaction force, the insertion velocity does not have a noticeable effect on the reaction force. Regarding the geometrical parameters, needle cutting angle is the prominent factor in terms of stress fields generated in the skin tissue. However, the needle diameter is more influential on the needle reaction force. We also presented an energy study on the frictional dissipation, damage dissipation, and strain energy throughout the insertion process.

Insights into the mechanics of solid conical microneedle array insertion into skin using the finite element method

In order to develop optimum microneedle designs, researchers must first develop robust, repeatable and adaptable test methods which are representative of in vivo conditions. However, there is a lack of experimental tools which can accurately comparatively interrogate functional microneedle penetration of tissue. In this study, we seek to develop a state of the art finite element model of microneedle insertion into and penetration of human skin. The developed model employs a 3D hyperelastic, anisotropic pre-stressed multi-layered material which more accurately reflects in vivo skin conditions, while the microneedle is modeled as an array, which can capture the influence of adjacent microneedles on the overall response. Using the developed finite element model, we highlight the importance of accurate computational modeling which can decipher the mechanics of microneedle insertion, including the influence of its position within an array and how it correlates well with experimental observations. In particular, we have concluded that, for our model microneedle array, increasing skin pretension from 0 to 10% strain reduces the penetration force by 13%, ultimate local deformation about the microneedle by 22% and the ultimate penetration efficiency by 15%. We have also concluded that the presence of a base plate limits the penetration efficiency by up to 24%, while the penetration efficiency across a 5 × 1 microneedle array may vary by 27%. This model elucidates, for the first time, the combined effects of skin tension and needle geometry on accurately predicting microneedle penetration efficiency. STATEMENT OF SIGNIFICANCE: Microneedles arrays (MNAs) are medical devices with microscale protrusions, typically designed to penetrate the outermost layer of the skin, that upon optimisation, could lead to disruptive minimally-invasive disease management. However, the mechanics of MNA insertion are complex, due in part to a 'bed of nails' effect, and difficult to elucidate experimentally. Therefore, comparisons between designs, functional assessment of production batches and ultimately the likelihood of clinical translation are challenging to predict. Here, we have develop the most sophisticated in silico model of MNA insertion into pre-tensioned human skin to predict the extent of MNA penetration and therefore the likelihood of successful therapeutic delivery. Researchers can customise this model to predict the penetration efficiency of any MNA design.

Feasibility of extracting tissue material properties via cohesive elements: a finite element approach to probe insertion procedures in non-invasive spine surgeries

Modeling the mechanical behavior of soft tissue probe insertion remains a challenging endeavor due to involved interdependent phenomena comprising tissue nonlinear deformation, contact between the probe and the tissue, crack propagation, and viscoelastic effects. To that matter, cohesive elements allow simulating crack formation and propagation, which provides a promising path to modeling the mechanical behavior of probe insertion in soft tissues. As such, the aim of the present study was to investigate the feasibility of devising and integrating an algorithm in a finite element (FE) case study in efforts of reverse engineering the material properties of non-homogeneous soft tissues. A layered nonlinear tissue model with a cohesive zone was created in the commercial software ABAQUS. Material properties were iteratively modified via a hybrid gradient descent optimization algorithm: minimizing the resultant error to first find optimum Ogden's hyperelastic parameters, followed by obtaining the damage parameters. Perceived material properties were then compared to those obtained via experimental human cadaver testing. Under the investigated four-layered muscle model, numerical results overlapped, to a great extent, with six different force-insertion experimental profiles with an average error of [Formula: see text] 15%. The best profile fit was realized when the highest sudden force drop was less than 60% of the peak force. Lastly, the FE analysis revealed an increase in stiffness as the probe advanced inside the tissue. The optimization algorithm demonstrated its capability to reverse engineer the material parameters required for the FE analysis of real, non-homogeneous, soft tissues. The significance of this procedure lies within its ability to extract tissue material parameters, in real time, with little to no intervention or invasive experimental tests. This could potentially further serve as a database for different muscle layers and force-insertion profiles, used for surgeon and physician clinical training purposes.

A New Medical Device Modeling Framework for Predicting the Performance of Indwelling Continence Care Devices and Improving Patient Care

A computational model of the human torso has been developed to study the stability of implanted leads that are part of a sacral nerve stimulation system. The model was built using presegmented anatomies that were themselves built from imaging of human patients. The sacral leads are represented using beam elements, and their interaction with the tissue is defined using a function that relates frictional force to the amount of slip between the lead and tissue. Displacements to the skin in the sacral region are applied to simulate activities of daily living, and the resulting displacement of the tip of the lead is indicative of its tendency to dislodge in real patients. Validation of the model was performed using experimental results collected in human cadavers. In these experiments, analogous displacements of the skin were applied after implantation of the leads per normal implant procedures. The displacement of the distal tip of the lead was measured using computed tomography (CT) imaging, allowing direct comparison to the predictions of the model. Recognizing that many model inputs were informed by sparse literature values, a novel application of uncertainty quantification methodology was developed wherein all model inputs were treated as uncertain intervals. This allowed an optimization approach to be used for estimating the uncertain interval for the model outputs. The computational model and cadaver results were used to study the performance of a new sacral lead design, relative to a predicate product. The results showed that the reduction in lead axial stiffness in the new design leads to less lead tip displacement, such that the lead is more likely to remain near the therapeutic target in patients.

Fluid-solid interaction in the rate-dependent failure of brain tissue and biomimicking gels

Brain tissue is a heterogeneous material, constituted by a soft matrix filled with cerebrospinal fluid. The interactions between, and the complexity of each of these components are responsible for the non-linear rate-dependent behaviour that characterises what is one of the most complex tissue in nature. Here, we investigate the influence of the cutting rate on the fracture properties of brain, through wire cutting experiments. We also present a computational model for the rate-dependent behaviour of fracture propagation in soft materials, which comprises the effects of fluid interaction through a poro-hyperelastic formulation. The method is developed in the framework of finite strain continuum mechanics, implemented in a commercial finite element code, and applied to the case of an edge-crack remotely loaded by a controlled displacement. Experimental and numerical results both show a toughening effect with increasing rates, which is linked to the energy dissipated by the fluid-solid interactions in the region surrounding the crack tip.

Infusion Mechanisms in Brain White Matter and Their Dependence on Microstructure: An Experimental Study of Hydraulic Permeability

OBJECTIVE

Hydraulic permeability is a topic of deep interest in biological materials because of its important role in a range of drug delivery-based therapies. The strong dependence of permeability on the geometry and topology of pore structure and the lack of detailed knowledge of these parameters in the case of brain tissue makes the study more challenging. Although theoretical models have been developed for hydraulic permeability, there is limited consensus on the validity of existing experimental evidence to complement these models. In the present study, we measure the permeability of white matter (WM) of fresh ovine brain tissue considering the localised heterogeneities in the medium using an infusion-based experimental set up, iPerfusion. We measure the flow across different parts of the WM in response to applied pressures for a sample of specific dimensions and calculate the permeability from directly measured parameters. Furthermore, we directly probe the effect of anisotropy of the tissue on permeability by considering the directionality of tissue on the obtained values. Additionally, we investigate whether WM hydraulic permeability changes with post-mortem time. To our knowledge, this is the first report of experimental measurements of the localised WM permeability, also demonstrating the effect of axon directionality on permeability. This work provides a significant contribution to the successful development of intra-tumoural infusion-based technologies, such as convection-enhanced delivery (CED), which are based on the delivery of drugs directly by injection under positive pressure into the brain.

Computer Assisted Planning for Curved Laser Interstitial Thermal Therapy

Laser interstitial thermal therapy (LiTT) is a minimally invasive alternative to conventional open surgery for drug-resistant focal mesial temporal lobe epilepsy (MTLE). Recent studies suggest that higher seizure freedom rates are correlated with maximal ablation of the mesial hippocampal head, whilst sparing of the parahippocampal gyrus (PHG) may reduce neuropsychological sequelae. Current commercially available laser catheters are inserted following manually planned straight-line trajectories, which cannot conform to curved brain structures, such as the hippocampus, without causing collateral damage or requiring multiple insertions. The clinical feasibility and potential of curved LiTT trajectories through steerable needles has yet to be investigated. This is the focus of our work. We propose a GPU-accelerated computer-assisted planning (CAP) algorithm for steerable needle insertions that generates optimized curved 3D trajectories with maximal ablation of the amygdalohippocampal complex and minimal collateral damage to nearby structures, while accounting for a variable ablation diameter ( 5-15mm). Simulated trajectories and ablations were performed on 5 patients with mesial temporal sclerosis (MTS), which were identified from a prospectively managed database. The algorithm generated obstacle-free paths with significantly greater target area ablation coverage and lower PHG ablation variance compared to straight line trajectories. The presented CAP algorithm returns increased ablation of the amygdalohippocampal complex, with lower patient risk scores compared to straight-line trajectories. This is the first clinical application of preoperative planning for steerable needle based LiTT. This study suggests that steerable needles have the potential to improve LiTT procedure efficacy whilst improving the safety and should thus be investigated further.