Contactless Remote Induction of Shear Waves in Soft Tissues Using a Transcranial Magnetic Stimulation Device

This study presents the first observation of shear wave induced remotely within soft tissues. It was performed through the combination of a transcranial magnetic stimulation device and a permanent magnet. A physical model based on Maxwell and Navier equations was developed. Experiments were performed on a cryogel phantom and a chicken breast sample. Using an ultrafast ultrasound scanner, shear waves of respective amplitude of 5 and 0.5 micrometers were observed. Experimental and numerical results were in good agreement. This study constitutes the framework of an alternative shear wave elastography method

Assessment of accuracy of the structure-factor-size-estimator method in determining red blood cell aggregate size from ultrasound spectrum backscattering coefficient

International audienceA computer simulation algorithm suitable for generating non-overlapping, isotropic and fairly identical red blood cell (RBC) clusters is presented. RBCs were stacked following the hexagonal close packing (HCP) structure to form a compact spherical aggregate. Such an aggregate was repeated and placed randomly under non-overlapping condition in three-dimensional space to mimic an aggregated blood sample. Backscattering coefficients (BSCs) were computed for samples at various cluster sizes and different hematocrits showing BSC increases with mean aggregate sizes. The accuracy of the structure factor size estimator (SFSE) method in determining mean aggregate size and packing factor were also examined. A good correlation (R2 ≥ 0.94) between the mean size of aggregates predicted by the SFSE and true size was found for each hematocrit. This study shows that for spherical aggregates there exists a region for each hematocrit where SFSE works most accurately. Typically, error of SFSE in estimating mean cluster size was < 20% for dimensions between 14-17 µm at 40% hematocrit. This study suggests that the theoretical framework of SFSE is valid under the assumption of isotropic aggregates

Comparison of three scattering models for ultrasound blood characterization

International audienceUltrasonic backscattered signals from blood contain frequency-dependent information that can be used to obtain quantitative parameters reflecting the aggregation level of red blood cells (RBCs). The approach consists in estimating structural aggregate parameters by fitting the spectrum of the backscattered radio-frequency echoes from blood to an estimated spectrum considering a theoretical scattering model. In this study, three scattering models were examined: a new implementation of the Gaussian Model (GM), the Structure Factor Size Estimator (SFSE) and the new Effective Medium Theory combined with the Structure Factor Model (EMTSFM). The accuracy of the three scattering models in determining mean aggregate size and compactness was compared by two- and three-dimensional (2D and 3D) computer simulations where RBC structural parameters are controlled. Two clustering conditions were studied: (1) when the aggregate size varied and the aggregate compactness was fixed in both 2D and 3D cases, and (2) when the aggregate size was fixed and the aggregate compactness varied in the 2D case. For both clustering conditions, the EMTSFM was found more suitable than the GM and SFSE for characterizing RBC aggregation

Linear Expansion And Thickness Swell Of Mdf As A Function Of Panel Density And Sorption State

Experiments were conducted using ASTM standard methods to determine the medium density fiberboard (MDF) expansion properties and swelling characteristics as a function of panel density and sorption state. Specimens without density profile were produced by removing the surface layers of laboratory MDF panels. The results from the trials showed that for laboratory MDF, linear expansion is homogenous in panel plane. When specimen density increased, linear expansion, linear expansion coefficient, thickness shrinkage coefficient, linear contraction, and linear contraction coefficient increased. Thickness swell was higher than thickness shrinkage at any density level. Thickness swell coefficient was higher than thickness shrinkage coefficient for low density levels. The values of linear contraction and linear contraction coefficient (in desorption) were higher than the values of linear expansion and linear expansion coefficient (in adsorption). The values on thickness swell and thickness shrinkage were much higher than the values of linear expansion and linear expansion and linear contraction at any density level. The effect of density on linear expansion, linear expansion coefficient and linear contraction coefficient was significantly stronger than the effect of density on thickness swell, thickness swell coefficient and thickness shrinkage

Numerical Prediction of Engineered Wood Flooring Deformation

Dimensional stability is of primary importance in the use of layered wood composites such as engineered wood flooring. It is largely due to the physical and mechanical properties and moisture content changes of each layer. Therefore, the non-homogeneous adsorption or desorption of moisture by the composite may induce its deformation, thus decreasing product value. The objective of this study was to develop a finite element model of the hygromechanical cupping in layered wood composite flooring. The model is based on two sets of equations: 1) the three-dimensional equations of unsteady-state moisture diffusion, and 2) the three-dimensional equations of elasticity including the orthotropic Hooke's law, which takes into account the shrinkage and swelling of each layer. The proposed model was used to predict the deformation of an engineered wood flooring strip following desorption by the top surface. The model was solved by the finite element method, and the calculated cupping was validated against experimental data. The results show that the proposed model can be successfully used to simulate the non-homogeneous moisture movement and the resulting cupping deformation in layered wood composites such as engineered wood flooring strips. For both predicted and measured deformation, roughly 80% of the cupping deformation appears after 3 days of conditioning. The low water vapor diffusion coefficient of the urea-formaldehyde film used between the surface and core layers of the strip plays a key role in the deformation process. After 42 days of conditioning, the model results overestimated the experimental results by 12% but were within one standard deviation of the experimental results. The model presented in this study appears to be a useful tool for product design purposes

Finite Element Modeling Of The Hygroscopic Warping Of Medium Density Fiberboard

The objective of this study was to develop a three-dimensional finite element model of the hygromechanical deformation of medium density fiberboard (MDF) panels with various vertical density profiles subjected to moisture adsorption on one face. The theoretical model was based on three sets of equations: 1) three-dimensional equations of unsteady-state moisture diffusion, 2) three-dimensional equations of mechanical equilibrium, and 3) Hooke's law for plane isotropy, which takes into account shrinkage and swelling through the panel thickness. The finite element model was applied to six panels with various density profiles. For both the simulations and the experiments, the warping was caused by moisture adsorption from one of the faces of 560-mm x 560-mm x 12-mm MDF panels while the other surface and the edges were sealed. Physical and mechanical characteristics defined as a function of density and moisture content were used as model inputs. The model made it possible to capture the rapid initial development of maximum warp and its following decrease as moisture content equalized through panel thickness; the effect of the density profile on the level of warp caused by moisture adsorption; and warp fluctuations resulting from changes in the ambient relative humidity, and from the hysteresis in the expansion coefficient between adsorption and desorption. To validate the model, the warp development of laboratory MDF panels was compared to simulation results. The agreement between calculated and actual panel warping confirmed that the model could successfully be used to simulate moisture movement in MDF and the resulting warp, and to help in the optimization of panel vertical density profiles aiming at better stability of form in MDF panels. For the typical experimental cases, it was observed that there was a strong effect of panel density profile on the levels of warp and its dynamics. The levels of warp increased with average panel density. The panels with sharper density profile developed stronger warp compared to panels with an even profile. When the density profile was skewed towards one of the surfaces, the panel developed positive or negative warp and did not return to the original flat form

Wood I-Joist Model Sensitivity to Oriented Strandboard Web Mechanical Properties

Research on wood I-joist design has often used laboratory testing, but simulation using the finite element method (FEM) offers advantages, including the possibility to separately study different joist components. The objective of this project was to perform a sensitivity analysis using FEM to determine which oriented strandboard (OSB) properties have higher impact on I-joist shear strain and deflection. OSB mechanical properties were changed from 50 to 200% of the reference value to determine their impact on web shear strain and I-joist deflection. The model was primarily sensitive to in-plane web shear stiffness, which changed I-joist deflection up to 23%. The model was also sensitive to the web tensile modulus of elasticity parallel and perpendicular to joist length and, to a lesser extent, to web shear stiffness. These properties changed I-joist deflection up to 2 and 1%, respectively. These findings will be used to plan future work to experimentally determine sensitive OSB web properties required to develop a finite element model of the mechanical behavior of wood I-joists

Acousto-electrical speckle pattern in Lorentz force electrical impedance tomography

Ultrasound speckle is a granular texture pattern appearing in ultrasound imaging. It can be used to distinguish tissues and identify pathologies. Lorentz force electrical impedance tomography is an ultrasound-based medical imaging technique of the tissue electrical conductivity. It is based on the application of an ultrasound wave in a medium placed in a magnetic field and on the measurement of the induced electric current due to Lorentz force. Similarly to ultrasound imaging, we hypothesized that a speckle could be observed with Lorentz force electrical impedance tomography imaging. In this study, we first assessed the theoretical similarity between the measured signals in Lorentz force electrical impedance tomography and in ultrasound imaging modalities. We then compared experimentally the signal measured in both methods using an acoustic and electrical impedance interface. Finally, a bovine muscle sample was imaged using the two methods. Similar speckle patterns were observed. This indicates the existence of an "acousto-electrical speckle" in the Lorentz force electrical impedance tomography with spatial characteristics driven by the acoustic parameters but due to electrical impedance inhomogeneities instead of acoustic ones as is the case of ultrasound imaging

Channel selection for test-time adaptation under distribution shift

To ensure robustness and generalization to real-world scenarios, test-time adaptation has been recently studied as an approach to adjust models to a new data distribution during inference. Test-time batch normalization is a simple and popular method that achieved compelling performance on domain shift benchmarks by recalculating batch normalization statistics on test batches. However, in many practical applications this technique is vulnerable to label distribution shifts. We propose to tackle this challenge by only selectively adapting channels in a deep network, minimizing drastic adaptation that is sensitive to label shifts. We find that adapted models significantly improve the performance compared to the baseline models and counteract unknown label shifts