PURPOSE:Validation of Magnetic Resonance Elastography (MRE) often relies on simple geometric phantoms which lack the complexity and heterogeneity of biological tissues. This limitation creates a methodological gap when assessing reconstruction algorithms intended for heterogeneous clinical environments. The aims were to demonstrate the feasibility of fabricating advanced polyphasic plastisol phantoms using a welding method and to evaluate reconstruction performance for phantoms with increasing geometric complexity specifically at material interfaces. Four plastisol phantoms (32 mm diameter, 17 mm height) were developed: homogeneous, inclusions, sectorial divisions, and a 3 × 3 checkerboard grid. METHODS:Acquisitions were performed at 9.4T using a fast spin-echo sequence with sinusoidal motion-encoding gradients (6 G/cm) and eight temporal phase offsets, an isotropic 0.8 mm resolution, a 64 × 64 matrix, and T2 mapping. Shear stiffness (μ) and damping ratio (ξ) were reconstructed using Algebraic Inversion of the Differential Equation (AIDE) and Non-Linear Inversion (NLI). Performance was evaluated comparing welded samples to non-welded controls and analyzing property deviations from the homogeneous case. RESULTS:Polyphasic samples demonstrated mechanical properties identical to homogeneous (μ=9.9±0.5 vs. 10.1±0.5kPa), confirming that the thermal process preserves the material's intrinsic properties. The resulting interfaces exhibit full mechanical continuity, acting as a single block. While both algorithms successfully captured structural heterogeneities, increasing geometric complexity induced systematic biases, particularly the underestimation of stiff regions and the overestimation of damping ratios near boundaries. CONCLUSION:Plastisol thermal fusion assembly enables the fabrication of stable, complex phantoms with precise mechanical control. Although the heterogeneities in this study were primarily 2D due to the ratio between shear wavelength and sample dimensions, the process is inherently compatible with 3D voxel-wise assembly. While formal tensile testing was not performed, basic stress tests confirmed that the interfacial cohesion is largely sufficient for the low-amplitude strains involved in MRE. These phantoms provide a versatile experimental framework for identifying algorithmic limitations at tissue interfaces and benchmarking advanced reconstruction methods in biologically relevant models.

This work presents a novel method for measuring the 4D displacement fields within phantom materials typically used for elastography experiments. This method allows independent validation of the time-harmonic displacement and deformation measurements commonly used in elastography methods, and also allows the experimental measurement of complex systems such as flow through flexible vessels within viscoelastic media. The optical scanning tomography and digital volume correlation techniques used for this method are presented in detail, including the geometric and imaging corrections used to ensure accurate results. In addition, a spatiotemporal filtering approach to extract the frequency domain harmonic content of the measured temporal data is presented. Experimental results are analysed in multiple phantom configurations and via comparison with numerical simulation using finite element methods. Overall, the method presented here offers, repeatable, highly resolved images of the displacement field even in heterogenous phantom configurations with good agreement to theory. These results show that this method has the potential to serve as a valuable tool for the development and validation of advanced elastography methods, capable of characterizing the complex, multi-scale and multi-physics behaviours typically observed in biological tissues.

The inverse problem that underlies Magnetic Resonance Elastography (MRE) is sensitive to the measurement data and the quality of the results of this tissue elasticity imaging process can be influenced both directly and indirectly by measurement noise. In this work, we apply a coupled adjoint field formulation of the viscoelastic constitutive parameter identification problem, where the indirect influence of noise through applied boundary conditions is avoided. A well-posed formulation of the coupled field problem is obtained through conditions applied to the adjoint field, relieving the computed displacement field from kinematic errors on the boundary. The theoretical framework for this formulation via a nearly incompressible, parallel subdomain-decomposition approach is presented, along with verification and a detailed exploration of the performance of the methods via a numerical simulation study. In addition, the advantages of this novel approach are demonstrated in-vivo in the human brain, showing the ability of the method to obtain viable tissue property maps in difficult configurations, enhancing the accuracy of the method.

BACKGROUND:Fetal alcohol spectrum disorders (FASD), a group of prevalent conditions resulting from prenatal alcohol exposure, affect the maturation of cerebral white matter as first identified with neuroimaging. However, traditional methods are unable to track subtle microstructural alterations to white matter. This preliminary study uses a highly sensitive and clinically translatable magnetic resonance elastography (MRE) protocol to assess brain tissue microstructure through its mechanical properties following an exercise intervention in a rat model of FASD. METHODS:Female rat pups were either alcohol-exposed (AE) via intragastric intubation of alcohol in milk substitute (5.25 g/kg/day) or sham-intubated (SI) on postnatal days (PD) four through nine to model alcohol exposure during the brain growth spurt. On PD 30, half of AE and SI rats were randomly assigned to either a wheel-running or standard cage for 12 days. Magnetic resonance elastography was used to measure whole brain and callosal mechanical properties at the end of the intervention (around PD 42) and at 1 month post-intervention, and findings were validated with histological quantification of oligoglia. RESULTS:Alcohol exposure reduced forebrain stiffness (p = 0.02) in standard-housed rats. The adolescent exercise intervention mitigated this effect, confirming that increased aerobic activity supports proper neurodevelopmental trajectories. Forebrain damping ratio was lowest in standard-housed AE rats (p < 0.01), but this effect was not mitigated by intervention exposure. At 1 month post-intervention, all rats exhibited comparable forebrain stiffness and damping ratio (p > 0.05). Callosal stiffness and damping ratio increased with age. With cessation of exercise, there was a negative rebound effect on the quantity of callosal oligodendrocytes, irrespective of treatment group, which diverged from our MRE results. CONCLUSIONS:This is the first application of MRE to measure the brain's mechanical properties in a rodent model of FASD. MRE successfully captured alcohol-related changes in forebrain stiffness and damping ratio. Additionally, MRE identified an exercise-related increase to forebrain stiffness in AE rats.

Background:Fetal Alcohol Spectrum Disorders (FASD) encompass a group of highly prevalent conditions resulting from prenatal alcohol exposure. Alcohol exposure during the third trimester of pregnancy overlapping with the brain growth spurt is detrimental to white matter growth and myelination, particularly in the corpus callosum, ultimately affecting tissue integrity in adolescence. Traditional neuroimaging techniques have been essential for assessing neurodevelopment in affected youth; however, these methods are limited in their capacity to track subtle microstructural alterations to white matter, thus restricting their effectiveness in monitoring therapeutic intervention. In this preliminary study we use a highly sensitive and clinically translatable Magnetic Resonance Elastography (MRE) protocol for assessing brain tissue microstructure through its mechanical properties following an exercise intervention in a rat model of FASD. Methods:Rat pups were divided into two groups: alcohol-exposed (AE) pups which received alcohol in milk substitute (5.25 g/kg/day) via intragastric intubation on postnatal days (PD) four through nine during the rat brain growth spurt (Dobbing and Sands, 1979), or sham-intubated (SI) controls. In adolescence, on PD 30, half AE and SI rats were randomly assigned to either a modified home cage with free access to a running wheel or to a new home cage for 12 days (Gursky and Klintsova, 2017). Previous studies conducted in the lab have shown that 12 days of voluntary exercise intervention in adolescence immediately ameliorated callosal myelination in AE rats (Milbocker et al., 2022, 2023). MRE was used to measure longitudinal changes to mechanical properties of the whole brain and the corpus callosum at intervention termination and one-month post-intervention. Histological quantification of precursor and myelinating oligoglia in corpus callosum was performed one-month post-intervention. Results:Prior to intervention, AE rats had lower forebrain stiffness in adolescence compared to SI controls ( p = 0.02). Exercise intervention immediately mitigated this effect in AE rats, resulting in higher forebrain stiffness post-intervention in adolescence. Similarly, we discovered that forebrain damping ratio was lowest in AE rats in adolescence ( p < 0.01), irrespective of intervention exposure. One-month post-intervention in adulthood, AE and SI rats exhibited comparable forebrain stiffness and damping ratio (p > 0.05). Taken together, these MRE data suggest that adolescent exercise intervention supports neurodevelopmental "catch-up" in AE rats. Analysis of the stiffness and damping ratio of the body of corpus callosum revealed that these measures increased with age. Finally, histological quantification of myelinating oligodendrocytes one-month post-intervention revealed a negative rebound effect of exercise cessation on the total estimate of these cells in the body of corpus callosum, irrespective of treatment group which was not convergent with noninvasive MRE measures. Conclusions:This is the first application of MRE to measure changes in brain mechanical properties in a rodent model of FASD. MRE successfully captured alcohol-related changes to forebrain stiffness and damping ratio in adolescence. These preliminary findings expand upon results from previous studies which used traditional diffusion neuroimaging to identify structural changes to the adolescent brain in rodent models of FASD (Milbocker et al., 2022; Newville et al., 2017). Additionally, in vivo MRE identified an exercise-related alteration to forebrain stiffness that occurred in adolescence, immediately post-intervention.

Identification of the mechanical properties of a viscoelastic material depends on characteristics of the observed motion field within the object in question. For certain physical and experimental configurations and certain resolutions and variance within the measurement data, the viscoelastic properties of an object may become non-identifiable. Elastographic imaging methods seek to provide maps of these viscoelastic properties based on displacement data measured by traditional imaging techniques, such as magnetic resonance and ultrasound. Here, 1D analytic solutions of the viscoelastic wave equation are used to generate displacement fields over wave conditions representative of diverse time-harmonic elastography applications. These solutions are tested through the minimization of a least squares objective function suitable for framing the elastography inverse calculation. Analysis shows that the damping ratio and the ratio of the viscoelastic wavelength to the size of the domain play critical roles in the form of this least squares objective function. In addition, it can be shown analytically that this objective function will contain local minima, which hinder discovery of the global minima via gradient descent methods.

1 mm thick sheets of 6016-T4 aluminum alloy and Zn coated steel were joined in a lap configuration using the Cold Metal Transfer (CMT) welding process with an Al-5Si filler metal and different powers and welding speeds. The formed reaction layer ensuring the bonding between the aluminum melting zone and the steel sheet doesn't exceed 10 mu m in thickness, and is composed of an iron-rich Fe-Al intermetallic on the steel side, and a Fe-Al-Si ternary compound on the aluminum weld side. The current waveform producing the lowest mean electrical power gives the most regular welds with lowest porosity in the melting zone. By optimizing the welding speed with this current waveform, the strength of the assembly under monotonic shear-tensile loading can reach 70% of that of the aluminum base material, and its lifetime under cyclic tensile loading exceeds 10(4) cycles for a maximal linear loading of 98 N mm(-1) and 10(7) cycles for a maximal linear loading of 42 N mm(-1).

Magnetic Resonance Elastography (MRE) is a modality that allows the mapping of the mechanical properties of soft tissues such as brain or liver from Magnetic Resonance Imaging (MRI) data. Specific MRI sequences have been developed in order to estimate the 3D displacement field in biological tissues undergoing harmonic solicitations [1]. The aim of this work consists in comparing the performance of different identification methods proposed for MRE in a situation straightforward enough –while still representative of elastography applications– to permit both analytic and experimental approaches. For the sake of simplicity, we present only the homogeneous case. The mechanical analysis of the problem illustrated in Figure 1 leads, for an adapted set of boundary conditions, to the resolution of the following usual problem. (voir annexe) For a given set of experimental conditions, we determine the complex-valued solution fields. The so-obtained displacement fields can be perturbed to represent experimental noise. These modified displacements are then introduced as input for different identification methods (Finite Element Model Updating [2], Constitutive Equation Gap [3] or Modified Constitutive Equation Gap [4]) in order to characterize their different efficiencies. In parallel, experimental tests are performed on gelatin samples with “controlled” properties in order to characterize these methods using real data.

With the intention of achieving an experimental grain scale energy balance at finite strain and at the grain scale, a mechanical test on a coarse-grained aluminium is presented in this paper using two complementary imaging techniques based on visible and infrared light. Specific image processing methods referred to as Constrained Digital Image Correlation (Constrained DIC) and Constrained InfraRed Thermography (Constrained IRT) are applied to investigate the thermomechanical behavior at the microstructural scale. Constrained DIC is used to obtain displacement and strain fields during the test, while Constrained IRT provides an estimate of temperature and heat source fields induced by the mechanical loading. The proposed “constrained” methods allow to enforce an adjustable level of constraints on a measured field (displacement or temperature) without referring to a specific finite-element description. In that manner, it is possible to decouple the measurement model and the interpretation model while keeping regularizing constraints (such as continuity of the fields). In this paper, we mainly focus on the kinematic analysis of the experimental test. Electron Backscatter Diffraction (EBSD) is also used in this case to experimentally characterize the microstucture of a 3 mm thick specimen with centimetric grain size.

The literature contains many studies on assessment of DIC uncertainties, particularly in the ultimate error regime, when the shape function used to describe the material transformation perfectly matches the actual transformation. For pure sub-pixel translations, bias and random errors obtained for experimental or synthetic images show more complex evolution versus the fractional part of displacement than those predicted by the existing theoretical models. Indeed, small deviations arise, mainly around integer values of imposed displacements for noisy images, and they are interpreted as the unrepresentativeness of the underlying hypotheses of the theoretical models. In a first step, differences between imposed and measured displacements are analysed: random error is independent of fractional displacement, and systematic error does not decrease for values close to integer displacements whatever the noise level. Therefore, new prediction models are proposed based on the analysis of identified phenomena from synthetic speckle-pattern 8-bit images. The statistical approach used in this paper generalizes the methods proposed in the literature and mimics the experimental methodology usually used for displacement measurements performed in different subsets in the same image. Two closed-form expressions for the systematic and random errors and a linear interpolation scheme are developed. These models, depending only on image properties and the imposed displacement, are built with a very limited number of parameters. It is then possible to predict the evolution of bias and random errors from one to four images.

In DIC, the "ultimate error regime" corresponds to situations for which the shape function used to describe the material transformation perfectly matches the actual one. We propose to confront results obtained from numerically-shifted images with the predictions of theoretical models developed in the literature to describe bias and random error evolutions with respect to the imposed displacement. Results show the overall good predictions of these models but small deviations arise, mainly around integer values of imposed displacements for noisy images. These deviations are interpreted as the unrepresentativeness of the underlying hypotheses of the theoretical models in these particular cases.

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