Proof of concept of a static approach to determine mechanical tissue properties during tumor surgery

The current work presents the results from an investigation of the mechanical behavior of single crystals of the energetic material pentaerythritol tetranitrate (PETN) using a nano‐indentation technique. The indentation tests have been performed on the maximum growth habit face (110) of the PETN, using a spherical, Berkovich and an anisometric (wedge‐shaped) tip. The load displacement curves along with analysis have been used to extract the mechanical properties and identify the anisotropic indentation modulus for the PETN. The indentation moduli of the PETN single crystal were found to decrease as indentation depth increases and become independent of indentation depth for depths greater than 200 nm for the spherical indenter and 300 nm for the anisometric wedge indenter and Berkovich tip. The indentation modulus obtained from spherical tip indentation is compared with the results calculated by using literature values of the elastic constants. The wedge indenter measurements and Berkovich indentation at various tip orientations are different due to the anisotropy of the PETN. The yield behaviors of the PETN single crystal were also explored using both spherical and wedge tip indentation and the differences are discussed.

The fabrication of bioinspired structures has recently gained an increasing popularity: mimicking the way in which nature develops structures is a vital prerequisite in soft robotics to achieve multiple benefits. Stiff structures connected by soft joints (recalling, for instance, human bones connected by cartilage) are highly appealing: several prototypes have been manufactured and tested, demonstrating their full potential. In the present research, the material extrusion (MEX) additive manufacturing technology has been used to manufacture stiff-soft bioinspired structures activated by shape memory alloy (SMA) actuators. First, three commercially available stiff composite plastic materials were investigated and linked to different 3D printing infills. Surprisingly, we found that the "gyroid" infill was correlated to the mechanical properties, demonstrating that it produces better results in terms of Young's modulus and ultimate tensile strength (UTS) than the widely studied "lines" infill. The primary focus of the research is an experimental study aimed at improving the adhesion at the interface between stiff and soft materials using an inexpensive method (i.e., MEX). Three different variables that have significant effects on the interface bonding were studied: (1) the interface geometry between stiff and soft parts, (2) the mesh overlapping process parameter, and (3) the annealing post-treatment. By optimizing the three variables, a Young's modulus of 48.8 MPa and a UTS of 3.8 MPa were achieved, when nylon+glass fiber (a stiff material) and thermoplastic polyurethane (a soft material) were 3D printed together. In particular, the 3.8 MPa UTS is 48% higher than the highest adhesion between the soft and stiff material (thermoplastic polyurethane [TPU] and acrylonitrile butadiene styrene) reported in literature. Finally, taking advantage of the improved stiff-soft adhesion, a bioinspired robotic finger has been fabricated and tested using an SMA actuator, showing an enormous potential for the proposed additive manufacturing approach in realizing bioinspired systems.

The mechanical behavior of granular materials is largely affected by particle breakage. Physical and mechanical properties of granular materials, such as grain size distribution, deviatoric and volumetric behavior, compressibility and mobilized friction angle are affected by particle crushing. This paper focuses on the evolution of the above mentioned characteristics using the Discrete Element Method (DEM). Behaviors of stiff and soft materials are studied using well established crushing criteria. Results from simulations indicate that stiff materials, have a typical fractal distribution of particle size, which is dominant when confining pressure increases. The fractal characteristic parameter of grain size effect is discussed. Evolution of shear stresses and volumetric strains during shearing are also predicted and analyzed. Expanded perlite, selected as a soft material, is investigated in terms of shear and volumetric behavior. For perlite, triaxial compression tests and corresponding DEM simulations are also performed. Results show good agreement between experiments and simulations and support the fact that the DEM can be considered as a useful tool to predict the behavior of crushable granular materials.

Fiber optic microindentation sensors that have the potential to be integrated into arthroscopic instruments and to allow localizing degraded articular cartilage are presented in this paper. The indenters consist of optical fibers with integrated Bragg gratings as force sensors. In a basic configuration, the tip of the fiber optic indenter consists of a cleaved fiber end, forming a cylindrical flat punch indenter geometry. When using this indenter geometry, high stresses at the edges of the cylinder are present, which can disrupt the tissue structure. This is avoided with an improved version of the indenter. A spherical indenter tip that is formed by melting the end of the glass fiber. The spherical fiber tip shows the additional advantage of strongly reducing reflections from the fiber end. This allows a reduction of the length of the fiber optic sensor element from 65 mm of the flat punch type to 27 mm of the spherical punch. In order to compare the performance of both indenter types, in vitro stress-relaxation indentation experiments were performed on bovine articular cartilage with both indenter types, to assess biomechanical properties of bovine articular cartilage. For indentation depths between 60 μm and 300 μm, the measurements with both indenter types agreed very well with each other. This shows that both indenter geometries are suitable for microindentation measuremnts . The spherical indenter however has the additional advantage that it minimizes the risk to damage the surface of the tissue and has less than half dimensions than the flat indenter.

In vivo magnetic resonance image (MRI)-based computational models have been introduced to calculate atherosclerotic plaque stress and strain conditions for possible rupture predictions. However, patient-specific vessel material properties are lacking in those models, which affects the accuracy of their stress/strain predictions. A noninvasive approach of combining in vivo Cine MRI, multicontrast 3D MRI, and computational modeling was introduced to quantify patient-specific carotid artery material properties and the circumferential shrinkage rate between vessel in vivo and zero-pressure geometries. In vivo Cine and 3D multicontrast MRI carotid plaque data were acquired from 12 patients after informed consent. For each patient, one nearly-circular slice and an iterative procedure were used to quantify parameter values in the modified Mooney-Rivlin model for the vessel and the vessel circumferential shrinkage rate. A sample artery slice with and without a lipid core and three material parameter sets representing stiff, median, and soft materials from our patient data were used to demonstrate the effect of material stiffness and circumferential shrinkage process on stress/strain predictions. Parameter values of the Mooney-Rivlin models for the 12 patients were quantified. The effective Young's modulus (YM, unit: kPa) values varied from 137 (soft), 431 (median), to 1435 (stiff), and corresponding circumferential shrinkages were 32%, 12.6%, and 6%, respectively. Using the sample slice without the lipid core, the maximum plaque stress values (unit: kPa) from the soft and median materials were 153.3 and 96.2, which are 67.7% and 5% higher than that (91.4) from the stiff material, while the maximum plaque strain values from the soft and median materials were 0.71 and 0.293, which are about 700% and 230% higher than that (0.089) from the stiff material, respectively. Without circumferential shrinkages, the maximum plaque stress values (unit: kPa) from the soft, median, and stiff models were inflated to 330.7, 159.2, and 103.6, which were 116%, 65%, and 13% higher than those from models with proper shrinkage. The effective Young's modulus from the 12 human carotid arteries studied varied from 137 kPa to 1435 kPa. The vessel circumferential shrinkage to the zero-pressure condition varied from 6% to 32%. The inclusion of proper shrinkage in models based on in vivo geometry is necessary to avoid over-estimating the stresses and strains by up 100%. Material stiffness had a greater impact on strain (up to 700%) than on stress (up to 70%) predictions. Accurate patient-specific material properties and circumferential shrinkage could considerably improve the accuracy of in vivo MRI-based computational stress/strain predictions.

Design and validation of a modular micro-robotic system for the mechanical characterization of soft tissues

We describe a comparative study between an enhanced air-cushion tactile sensor and a wheeled indentation probe. These laparoscopic tools are designed to rapidly locate soft-tissue abnormalities during minimally invasive surgery (MIS). The air-cushion tactile sensor consists of an optically based sensor with a 7.8 mm sphere "floating" on a cushion of air at the tip of a shaft. The wheeled indentation probe is a 10 mm wide and 5 mm in diameter wheel mounted to a force/torque sensor. A continuous rolling indentation technique is used to pass the sensors over the soft-tissue surfaces. The variations in stiffness of the viscoelastic materials that are detected during the rolling indentations are illustrated by stiffness maps that can be used for tissue diagnosis. The probes were tested by having to detect four embedded nodules in a silicone phantom. Each probe was attached to a robotic manipulator and rolled over the silicone phantom in parallel paths. The readings of each probe collected during the process of rolling indentation were used to achieve the final results. The results show that both sensors reliably detected the areas of variable stiffness by accurately identifying the location of each nodule. These are illustrated in the form of two three-dimensional spatiomechanical maps. These probes have the potential to be used in MIS because they could provide surgeons with information on the mechanical properties of soft tissue, consequently enhancing the reduction in haptic feedback.

To analyze the relationship between the tension force of a rope and the bundled material's indentation, a model of tightening by rope for soft material was designed for testing. By calculating the indentation depth of soft materials from rope stretching displacement, the variation law of the indentation depth of tightening soft materials with different mechanical properties of ropes was analyzed. As the stretching progresses, the more the rope winding turns, and the shallower the indentation depth. The friction coefficient between the soft material and the rope does not significantly affect the theoretical indentation depth. The theoretical indentation depth of high-strength ropes shows a linear variation pattern. The theoretical indentation depth of high-extension ropes is negative. With the theoretical indentation depth of the ordinary rope increasing first and then decreasing, its indentation depth curve shows a parabolic shape. Aromatic polyester rope, cotton chainette thread, and polypropylene rope were used to tighten ethylene-vinyl acetate (EVA) foam and test the indentation depth. The results show that the deformation of the rope is much lower than that of the EVA foam, and the depth of the strangulation is closely related to the tensile displacement and tightening tension. The measured value of the indentation depth is lower than the calculated value, and the greater the stiffness of the rope, the smaller the difference between the measured and calculated indentation depth. The indentation depth method was used to calculate the tightening effect of ropes with high rigidity and has excellent results.

Numerical simulations of the indentation of glass with implications to ductile grinding: K. L. Blaedel, D. J. Nikkel, (Lawrence Livermore National Lab., CA. 25 Feb 1991). (UCRL-ID-106838)

Abstract

Mechanical difference between white and gray matter in the rat cerebellum measured by scanning force microscopy

Background: Nanoindentation is arguably the most versatile and effective method for measuring materials’ mechanical properties at nanoscale. However, due to the complexity of the deformation process during the nanoindentation tests, many experimental factors can significantly affect the nanoindentation results. Objective: This research aims to investigate the quantitative effects of material properties on nanoindentation responses and apply these relationships to the evaluation of broader material properties through nanoindentation. Methods: This study uses intensive computer modeling based on finite element analysis and modeling data analysis through curve fitting. Results: Nanoindentation responses (indentation load versus depth data) were numerically modeled by computer modeling, considering the effects of the mechanical properties of the materials (low-carbon steel AISI1018, steel alloy AISI4340, and aluminum alloy 6061-T6) and the indenter geometries (Berkovich, cylindrical, and spherical indenters). Through data analysis, the quantitative relationships between indentation load and indentation depth were established. The parameters in the formulae were optimized by the least-squares method, and high accuracy of the correlation coefficients between the modeling results and the formulae was achieved. Conclusion: It was found that the parameters of the formulae directly reflect the material properties of a testing specimen, and more material properties can be estimated through nanoindentation.

Hepatic tumors appear as stiff inclusions within the surrounding soft, healthy tissue. In open surgery they are searched for by manual palpation with the gloved fingertip. However, to exploit the benefits of MIS it is mandatory to implement a substitution for the human sense of touch. Therefore, a tactile instrument has been developed with the aim of enlarging the sensing area at the tool tip once it enters the abdominal cavity through the trocar. The provision of a large sensitive surface enables the detection of nearly all sizes of tumors and decreases the time needed for the performance of this task. A prototype was manufactured by laser sintering in PA serving as a carrier for an existing flexible silicone sensor. Automated as well as manual subject palpation tests have shown that a prototypical instrument with a laterally opening lid would be a suitable device for tumor detection in laparoscopic liver surgery.

This paper presents a novel wheeled probe for the purpose of aiding a surgeon in soft tissue abnormality identification during minimally invasive surgery (MIS), compensating the loss of haptic feedback commonly associated with MIS. Initially, a prototype for validating the concept was developed. The wheeled probe consists of an indentation depth sensor employing an optic fibre sensing scheme and a force/torque sensor. The two sensors work in unison, allowing the wheeled probe to measure the tool-tissue interaction force and the rolling indentation depth concurrently. The indentation depth sensor was developed and initially tested on a homogenous silicone phantom representing a good model for a soft tissue organ; the results show that the sensor can accurately measure the indentation depths occurring while performing rolling indentation, and has good repeatability. To validate the ability of the wheeled probe to identify abnormalities located in the tissue, the device was tested on a silicone phantom containing embedded hard nodules. The experimental data demonstrate that recording the tissue reaction force as well as rolling indentation depth signals during rolling indentation, the wheeled probe can rapidly identify the distribution of tissue stiffness and cause the embedded hard nodules to be accurately located.

Reinforcement learning design framework for nacre-like structures optimized for pre-existing crack resistance