A Force-Matched Approach to Large-Strain Nonlinearity in Elasticity Imaging for Breast Lesion Characterization.

OBJECTIVE: Ultrasound elasticity imaging is a class of ultrasound techniques with applications that include the detection of malignancy in breast lesions. Although elasticity imaging traditionally assumes linear elasticity, the large strain elastic response of soft tissue is known to be nonlinear. This study evaluates the nonlinear response of breast lesions for the characterization of malignancy using force measurement and force-controlled compression during ultrasound imaging. METHODS: 54 patients were recruited for this study. A custom force-instrumented compression device was used to apply a controlled force during ultrasound imaging. Motion tracking derived strain was averaged over lesion or background ROIs and matched with compression force. The resulting force-matched strain was used for subsequent analysis and curve fitting. RESULTS: Greater median differences between malignant and benign lesions were observed at higher compressional forces (p-value < 0.05 for compressional forces of 2-6N). Of three candidate functions, a power law function produced the best fit to the force-matched strain. A statistically significant difference in the scaling parameter of the power function between malignant and benign lesions was observed (p-value = 0.025). CONCLUSIONS: We observed a greater separation in average lesion strain between malignant and benign lesions at large compression forces and demonstrated the characterization of this nonlinear effect using a power law model. Using this model, we were able to differentiate between malignant and benign breast lesions. SIGNIFICANCE: With further development, the proposed method to utilize the nonlinear elastic response of breast tissue has the potential for improving non-invasive lesion characterization for potential malignancy.

Multiscale theoretical model shows that aging-related mechanical degradation of cortical bone is driven by microstructural changes in addition to porosity.

This study aims to gain mechanistic understanding of how aging-related changes in the microstructure of cortical bone drive mechanical consequences at the macroscale. To that end, cortical bone was modeled as a bundle of elastic-plastic, parallel fibers, which represented osteons and interstitial tissue, loaded in uniaxial tension. Distinct material properties were assigned to each fiber in either the osteon or interstitial fiber "families." Models representative of mature (20-60 yrs.) bone, and elderly (60+) bone were created by modeling aging via the following changes to the input parameters: (i) increasing porosity from 5% to 15%, (ii) increasing the ratio of the number of osteon fibers relative to interstitial fibers from 40% to 50%, and (iii) changing the fiber material properties from representing mature bone samples to representing elderly bone samples (i.e., increased strength and decreased toughness of interstitial fibers together with decreased toughness of osteon fibers). To understand the respective contributions of these changes, additional models isolating one or two of each of these were also created. From the computed stress-strain curve for the fiber bundle, the yield point (ϵy, σy), ultimate point (ϵu, σu), and toughness (UT) for the bundle as a whole were measured. We found that changes to all three input parameters were required for the model to capture the aging-related decline in cortical bone mechanical properties consistent with those previously reported in the literature. In both mature and elderly bundles, rupture of the interstitial fibers drove the initial loss of strength following the ultimate point. Plasticity and more gradual rupture of the osteons drove the remainder of the response. Both the onset and completion of interstitial fiber rupture occurred at lower strains in the elderly vs. mature case. These findings point to the importance of studying microstructural changes beyond porosity, such as the area fraction of osteons and the material properties of osteon and interstitial tissue, in order to further understanding of aging-related changes in bone.

Repeatability of Linear and Nonlinear Elastic Modulus Maps From Repeat Scans in the Breast.

Compression elastography allows the precise measurement of large deformations of soft tissue in vivo. From an image sequence showing tissue undergoing large deformation, an inverse problem for both the linear and nonlinear elastic moduli distributions can be solved. As part of a larger clinical study to evaluate nonlinear elastic modulus maps (NEMs) in breast cancer, we evaluate the repeatability of linear and nonlinear modulus maps from repeat measurements. Within the cohort of subjects scanned to date, 20 had repeat scans. These repeated scans were processed to evaluate NEM repeatability. In vivo data were acquired by a custom-built, digitally controlled, uniaxial compression device with force feedback from the pressure-plate. RF-data were acquired using plane-wave imaging, at a frame-rate of 200 Hz, with a ramp-and-hold compressive force of 8N, applied at 8N/sec. A 2D block-matching algorithm was used to obtain sample-level displacement fields which were then tracked at subsample resolution using 2D cross correlation. Linear and nonlinear elasticity parameters in a modified Veronda-Westmann model of tissue elasticity were estimated using an iterative optimization method. For the repeated scans, B-mode images, strain images, and linear and nonlinear elastic modulus maps are measured and compared. Results indicate that when images are acquired in the same region of tissue and sufficiently high strain is used to recover nonlinearity parameters, then the reconstructed modulus maps are consistent.

Significance of the Microfluidic Flow Inside the Organ of Corti.

We study the vibration modes of a short section in the middle turn of the gerbil cochlea including both longitudinal and radial interstitial fluid spaces between the pillar cells (PC) and the sensory hair cells to determine the role of the interstitial fluid flow within the organ of corti (OoC). Three detailed finite element (FE) models of the cochlear short section (CSS) are studied. In model 1, the CSS is without fluids; model 2 includes the OoC fluid, but not the exterior scalae fluids; and model 3 is the CSS with both scalae and OoC fluids. We find that: (1) the fundamental mode shape of models 1 or 3 is similar to the classical basilar membrane (BM) bending mode that includes pivoting of the arch of corti, and hence determines the low frequency vibrational mode shape of the cochlea in the presence of the cochlear wave. (2) The fundamental mode shape of model 2 is characterized by a cross-sectional shape change similar to the passive response of the cochlea. This mode shape includes a tilting motion of the inner hair cell (IHC) region, a fluid motion within the tunnel of corti (ToC) in the radial direction and along the OoC, and a bulging motion of the reticular lamina (RL) above the outer hair cell (OHC). Each of these motions provides a plausible mode of excitation of the sensory hair cells. (3) The higher vibrational modes of model 1 are similar to the electrically evoked response within the OoC and suggests that the higher vibrational modes are responsible for the active response of the cochlea. We also observed that the fluid flow through the OoC interstitial space is significant, and the model comparison suggests that the OoC fluid contributes to the biphasic BM motion seen in electrical stimulation experiments. The effect of fluid viscosity on cilium deflection was assessed by performing a transient analysis to calculate the cilium shearing gain. The gain values are found to be within the range of experimentally measured values reported by Dallos et al. (1996, The Cochlea, Springer-Verlag, New York).

Effect of correlation between traction forces on tensional homeostasis in clusters of endothelial cells and fibroblasts.

The ability of cells to maintain a constant level of cytoskeletal tension in response to external and internal disturbances is referred to as tensional homeostasis. It is essential for the normal physiological function of cells and tissues, and for protection against disease progression, including atherosclerosis and cancer. In previous studies, we defined tensional homeostasis as the ability of cells to maintain a consistent level of cytoskeletal tension with low temporal fluctuations. In those studies, we measured temporal fluctuations of cell-substrate traction forces in clusters of endothelial cells and of fibroblasts. We observed those temporal fluctuations to decrease with increasing cluster size in endothelial cells, but not in fibroblasts. We quantified temporal fluctuation, and thus homeostasis, through the coefficient of variation (CV) of the traction field; the lower the value of CV, the closer the cell is to the state of tensional homeostasis. This metric depends on correlation between individual traction forces. In this study, we analyzed the contribution of correlation between traction forces on traction field CV in clusters of endothelial cells and fibroblasts using experimental data that we had obtained previously. Results of our analysis showed that positive correlation between traction forces was detrimental to homeostasis, and that it was cell type-dependent.

Imaging localized neuronal activity at fast time scales through biomechanics.

Mapping neuronal activity noninvasively is a key requirement for in vivo human neuroscience. Traditional functional magnetic resonance (MR) imaging, with a temporal response of seconds, cannot measure high-level cognitive processes evolving in tens of milliseconds. To advance neuroscience, imaging of fast neuronal processes is required. Here, we show in vivo imaging of fast neuronal processes at 100-ms time scales by quantifying brain biomechanics noninvasively with MR elastography. We show brain stiffness changes of ~10% in response to repetitive electric stimulation of a mouse hind paw over two orders of frequency from 0.1 to 10 Hz. We demonstrate in mice that regional patterns of stiffness modulation are synchronous with stimulus switching and evolve with frequency. For very fast stimuli (100 ms), mechanical changes are mainly located in the thalamus, the relay location for afferent cortical input. Our results demonstrate a new methodology for noninvasively tracking brain functional activity at high speed.

Dispersion in Tissue-Mimicking Gels Measured with Shear Wave Elastography and Torsional Vibration Rheometry.

Dispersion, or the frequency dependence of mechanical parameters, is a primary confounding factor in elastography comparisons. We present a study of dispersion in tissue-mimicking gels over a wide frequency band using a combination of ultrasound shear wave elastography (SWE), and a novel torsional vibration rheometry which allows independent mechanical measurement of SWE samples. Frequency-dependent complex shear modulus was measured in homogeneous gelatin hydrogels of two different bloom strengths while controlling for confounding factors such as temperature, water content and material aging. Furthermore, both techniques measured the same physical samples, thereby eliminating possible variation caused by batch-to-batch gel variation, sample geometry differences and boundary artifacts. The wide-band measurement, from 1 to 1800 Hz, captured a 30%-50% increase in the storage modulus and a nearly linear increase with frequency of the loss modulus. The magnitude of the variation suggests that accounting for dispersion is essential for meaningful comparisons between SWE implementations.

Application of a forward model of axisymmetric shear wave propagation in viscoelastic media to shear wave elastography.

A simple but general solution of Navier's equation for axisymmetric shear wave propagation in a homogeneous isotropic viscoelastic medium is presented. It is well-suited for use as a forward model for some acoustic radiation force impulse based shear wave elastography applications because it does not require precise knowledge of the strength of the source, nor its spatial or temporal distribution. Instead, it depends on two assumptions: (1) the source distribution is axisymmetric and confined to a small region near the axis of symmetry, and (2) the propagation medium is isotropic and homogeneous. The model accounts for the vector polarization of shear waves and exactly represents geometric spreading of the shear wavefield, whether spherical, cylindrical, or neither. It makes no assumption about the frequency dependence of material parameters, i.e., it is material-model independent. Validation using measured shear wavefields excited by acoustic radiation force in a homogeneous gelatin sample show that the model accounts for well over 90% of the measured wavefield "energy." An optimal fit of the model to simulated shear wavefields with noise in a homogeneous viscoelastic medium enables estimation of both the shear storage modulus and shear wave attenuation to within 1%.

Characterization of glioblastoma in an orthotopic mouse model with magnetic resonance elastography.

Glioblastoma (GBM) is the most common primary brain tumor. It is highly malignant and has a correspondingly poor prognosis. Diagnosis and monitoring are mainly accomplished with MRI, but remain challenging in some cases. Therefore, complementary methods for tumor detection and characterization would be beneficial. Using magnetic resonance elastography (MRE), we performed a longitudinal study of the biomechanical properties of intracranially implanted GBM in mice and compared the results to histopathology. The biomechanical parameters of viscoelastic modulus, shear wave speed and phase angle were significantly lower in tumors compared with healthy brain tissue and decreased over time with tumor progression. Moreover, some MRE parameters revealed sub-regions at later tumor stages, which were not easily detectable on anatomical MRI images. Comparison with histopathology showed that softer tumor regions contained necrosis and patches of viable tumor cells. In contrast, areas of densely packed tumor cells and blood vessels identified with histology coincided with higher values of viscoelastic modulus and shear wave speed. Interestingly, the phase angle was independent from these anatomical variations. In summary, MRE depicted longitudinal and morphological changes in GBM and may prove valuable for tumor characterization in patients.

Recovering vector displacement estimates in quasistatic elastography using sparse relaxation of the momentum equation.

We consider the problem of estimating the 2D vector displacement field in a heterogeneous elastic solid deforming under plane stress conditions. The problem is motivated by applications in quasistatic elastography. From precise and accurate measurements of one component of the 2D vector displacement field and very limited information of the second component, the method reconstructs the second component quite accurately. No a priori knowledge of the heterogeneous distribution of material properties is required. This method relies on using a special form of the momentum equations to filter ultrasound displacement measurements to produce more precise estimates. We verify the method with applications to simulated displacement data. We validate the method with applications to displacement data measured from a tissue mimicking phantom, and in-vivo data; significant improvements are noticed in the filtered displacements recovered from all the tests. In verification studies, error in lateral displacement estimates decreased from about 50% to about 2%, and strain error decreased from more than 250% to below 2%.

Direct Error in Constitutive Equation Formulation for Plane stress Inverse Elasticity Problem.

We present a new computational formulation for inverse problems in elasticity with full field data. The formulation is a variant of an error in the constitutive equation formulation, but allows direct solution for the modulus field and accommodates discontinuous strain fields. The development of the formulation is motivated by the relatively poor performance of current direct formulations, reported so far in literature, in dealing with discontinuities in the strain and material property distribution. The formulation relies on minimizing the error in the constitutive equation, and a momentum equation constraint. Numerical results on model problems show that the formulation is capable handling discontinuous, and noisy strain fields, and also converging with mesh refinement for continuous and discontinuous material property distributions. The application to reconstruct the elastic modulus distribution in solid breast tumors is shown.

Three-dimensional Ultrasound Elasticity Imaging on an Automated Breast Volume Scanning System.

Ultrasound elasticity imaging has demonstrated utility in breast imaging, but it is typically performed with handheld transducers and two-dimensional imaging. Two-dimensional (2D) elastography images tissue stiffness of only a plane and hence suffers from errors due to out-of-plane motion, whereas three-dimensional (3D) data acquisition and motion tracking can be used to track out-of-plane motion that is lost in 2D elastography systems. A commercially available automated breast volume scanning system that acquires 3D ultrasound data with precisely controlled elevational movement of the 1D array ultrasound transducer was employed in this study. A hybrid guided 3D motion-tracking algorithm was developed that first estimated the displacements in one plane using a modified quality-guided search method, and then performed an elevational guided-search for displacement estimation in adjacent planes. To assess the performance of the method, 3D radiofrequency echo data were acquired with this system from a phantom and from an in vivo human breast. For both experiments, the axial displacement fields were smooth and high cross-correlation coefficients were obtained in most of the tracking region. The motion-tracking performance of the new method was compared with a correlation-based exhaustive-search method. For all motion-tracking volume pairs, the average motion-compensated cross-correlation values obtained by the guided-search motion-tracking method were equivalent to those by the exhaustive-search method, and the computation time was about a factor of 10 lesser. Therefore, the proposed 3D ultrasound elasticity imaging method was a more efficient approach to produce a high quality of 3D ultrasound strain image.

Improving three-dimensional mechanical imaging of breast lesions with principal component analysis.

PURPOSE: Elastography has emerged as a new tool for detecting and diagnosing many types of diseases including breast cancer. To date, most clinical applications of elastography have utilized two-dimensional strain images. The goal of this paper is to present a new quasi-static elastography technique that yields shear modulus images in three dimensions. METHODS: An automated breast volume scanner was used to acquire ultrasound images of the breast as it was gently compressed. Cross-correlation between successive images was used to determine the displacement within the tissue. The resulting displacement field was filtered of all but compressive motion through principal component analysis. This displacement field was used to infer spatial distribution of shear modulus by solving a 3D elastic inverse problem. RESULTS: Three dimensional shear modulus images of benign breast lesions for two subjects were generated using the techniques described above. It was found that the lesions were visualized more clearly in images generated using the displacement data de-noised through the use of principal components. CONCLUSIONS: We have presented experimental and algorithmic techniques that lead to three-dimensional imaging of shear modulus using quasi-static elastography. This work demonstrates feasibility of this approach, and lays the foundation for images of other, more informative, mechanical parameters.

Spatial distribution of airway wall displacements during breathing and bronchoconstriction measured by ultrasound elastography using finite element image registration.

With every breath, the airways within the lungs are strained. This periodic stretching is thought to play an important role in determining airway caliber in health and disease. Particularly, deep breaths can mitigate excessive airway narrowing in healthy subjects, but this beneficial effect is absent in asthmatics, perhaps due to an inability to stretch the airway smooth muscle (ASM) embedded within an airway wall. The heterogeneous composition throughout an airway wall likely modulates the strain felt by the ASM but the magnitude of ASM strain is difficult to measure directly. In this study, we optimized a finite element image registration method to measure the spatial distribution of displacements and strains throughout an airway wall during pressure inflation within the physiological breathing range before and after induced narrowing with acetylcholine (ACh). The method was shown to be repeatable, and displacements estimated from different image sequences of the same deformation agreed to within 5.3µm (0.77%). We found the magnitude and spatial distribution of displacements were radially and longitudinally heterogeneous. The region in the middle layer of the airway experienced the largest radial strain due to a transmural pressure (Ptm) increase simulating tidal breathing and a deep inspiration (DI), while the region containing the ASM (i.e., closest to the lumen) strained least. During induced narrowing with ACh, we observed temporal longitudinal heterogeneity of the airway wall. After constriction, the displacements and strain are much smaller than the relaxed airway and the pattern of strains changed, suggesting the airway stiffened heterogeneously.

Inferring spatial variations of microstructural properties from macroscopic mechanical response.

Disease alters tissue microstructure, which in turn affects the macroscopic mechanical properties of tissue. In elasticity imaging, the macroscopic response is measured and is used to infer the spatial distribution of the elastic constitutive parameters. When an empirical constitutive model is used, these parameters cannot be linked to the microstructure. However, when the constitutive model is derived from a microstructural representation of the material, it allows for the possibility of inferring the local averages of the spatial distribution of the microstructural parameters. This idea forms the basis of this study. In particular, we first derive a constitutive model by homogenizing the mechanical response of a network of elastic, tortuous fibers. Thereafter, we use this model in an inverse problem to determine the spatial distribution of the microstructural parameters. We solve the inverse problem as a constrained minimization problem and develop efficient methods for solving it. We apply these methods to displacement fields obtained by deforming gelatin-agar co-gels and determine the spatial distribution of agar concentration and fiber tortuosity, thereby demonstrating that it is possible to image local averages of microstructural parameters from macroscopic measurements of deformation.

Noninvasive In-Vivo Quantification of Mechanical Heterogeneity of Invasive Breast Carcinomas.

Heterogeneity is a hallmark of cancer whether one considers the genotype of cancerous cells, the composition of their microenvironment, the distribution of blood and lymphatic microvasculature, or the spatial distribution of the desmoplastic reaction. It is logical to expect that this heterogeneity in tumor microenvironment will lead to spatial heterogeneity in its mechanical properties. In this study we seek to quantify the mechanical heterogeneity within malignant and benign tumors using ultrasound based elasticity imaging. By creating in-vivo elastic modulus images for ten human subjects with breast tumors, we show that Young's modulus distribution in cancerous breast tumors is more heterogeneous when compared with tumors that are not malignant, and that this signature may be used to distinguish malignant breast tumors. Our results complement the view of cancer as a heterogeneous disease on multiple length scales by demonstrating that mechanical properties within cancerous tumors are also spatially heterogeneous.

Stiffness versus prestress relationship at subcellular length scale.

Local intracellular variations of cell mechanical properties, which are essential for vital cellular functions, have not been well characterized and are poorly understood. Here, we used results from our previous biomechanical imaging study to obtain relationships between intracellular shear modulus and prestress. We found that the subcellular shear modulus vs. prestress relationships exhibited positive linear correlations, consistent with previously observed behaviors at the whole cell and tissue levels. This, in turn, suggests that the prestress may be a unifying factor that determines material properties of living matter at different length scales.

Algorithms for quantitative quasi-static elasticity imaging using force data.

Quasi-static elasticity imaging can improve diagnosis and detection of diseases that affect the mechanical behavior of tissue. In this methodology, images of the shear modulus of the tissue are reconstructed from the measured displacement field. This is accomplished by seeking the spatial distribution of mechanical properties that minimizes the difference between the predicted and the measured displacement fields, where the former is required to satisfy a finite element approximation to the equations of equilibrium. In the absence of force data, the shear modulus is determined only up to a multiplicative constant. In this manuscript, we address the problem of calibrating quantitative elastic modulus reconstructions created from measurements of quasi-static deformations. We present two methods that utilize the knowledge of the applied force on a portion of the boundary. The first involves rescaling the shear modulus of the original minimization problem to best match the measured force data. This approach is easily implemented but neglects the spatial distribution of tractions. The second involves adding a force-matching term to the original minimization problem and a change of variables wherein we seek the log of the shear modulus. We present numerical results that demonstrate the usefulness of both methods.

Biomechanical imaging of cell stiffness and prestress with subcellular resolution.

Knowledge of cell mechanical properties, such as elastic modulus, is essential to understanding the mechanisms by which cells carry out many integrated functions in health and disease. Cellular stiffness is regulated by the composition, structural organization, and indigenous mechanical stress (or prestress) borne by the cytoskeleton. Current methods for measuring stiffness and cytoskeletal prestress of living cells necessitate either limited spatial resolution but with high speed, or spatial maps of the entire cell at the expense of long imaging times. We have developed a novel technique, called biomechanical imaging, for generating maps of both cellular stiffness and prestress that requires less than 30 s of interrogation time, but which provides subcellular spatial resolution. The technique is based on the ability to measure tractions applied to the cell while simultaneously observing cell deformation, combined with capability to solve an elastic inverse problem to find cell stiffness and prestress distributions. We demonstrated the application of this technique by carrying out detailed mapping of the shear modulus and cytoskeletal prestress distributions of 3T3 fibroblasts, making no assumptions regarding those distributions or the correlation between them. We also showed that on the whole cell level, the average shear modulus is closely associated with the average prestress, which is consistent with the data from the literature. Data collection is a straightforward procedure that lends itself to other biochemical/biomechanical interventions. Biomechanical imaging thus offers a new tool that can be used in studies of cell biomechanics and mechanobiology where fast imaging of cell properties and prestress is desired at subcellular resolution.

Discriminating resonant targets from clutter using Lanczos iterated single-channel time reversal.

Power iterated single-channel time-reversal is extended to employ Lanczos iterations. The properties of these algorithms are studied in the presence of varying levels of noise and broadband clutter. It is shown the Lanczos iterated method possesses superior convergence properties in comparison to the standard power iterated technique. Results demonstrate that such algorithms provide an efficient means through which to isolate and extract the properties of resonant scatterers in the presence of noise and coherent interference.