Ultrasonic measurements of breast viscoelasticity

Ultrasound Viscosity Imaging in Breast Lesions: A Multicenter Prospective Study

RATIONALE AND OBJECTIVES

To explore and validate the clinical value of ultrasound (US) viscosity imaging in differentiating breast lesions by combining with BI-RADS, and then comparing the diagnostic performances with BI-RADS alone.

MATERIALS AND METHODS

This multicenter, prospective study enrolled participants with breast lesions from June 2021 to November 2022. A development cohort (DC) and validation cohort (VC) were established. Using histological results as reference standard, the viscosity-related parameter with the highest area under the receiver operating curve (AUC) was selected as the optimal one. Then the original BI-RADS would upgrade or not based on the value of this parameter. Finally, the results were validated in the VC and total cohorts. In the DC, VC and total cohorts, all breast lesions were divided into the large lesion, small lesion and overall groups respectively.

RESULTS

A total of 639 participants (mean age, 46 years ± 14) with 639 breast lesions (372 benign and 267 malignant lesions) were finally enrolled in this study including 392 participants in the DC and 247 in the VC. In the DC, the optimal viscosity-related parameter in differentiating breast lesions was calculated to be A'-S2-Vmax, with the AUC of 0.88 (95% CI: 0.84, 0.91). Using > 9.97 Pa.s as the cutoff value, the BI-RADS was then modified. The AUC of modified BI-RADS significantly increased from 0.85 (95% CI: 0.81, 0.88) to 0.91 (95% CI: 0.87, 0.93), 0.85 (95% CI: 0.80, 0.89) to 0.90 (95% CI: 0.85, 0.93) and 0.85 (95% CI: 0.82, 0.87) to 0.90 (95% CI: 0.88, 0.92) in the DC, VC and total cohorts respectively (P < .05 for all).

CONCLUSION

The quantitative viscous parameters evaluated by US viscosity imaging contribute to breast cancer diagnosis when combined with BI-RADS.

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.

Wave-based optical coherence elastography: The 10-year perspective

After 10 years of progress and innovation, optical coherence elastography (OCE) based on the propagation of mechanical waves has become one of the major and the most studied OCE branches, producing a fundamental impact in the quantitative and nondestructive biomechanical characterization of tissues. Preceding previous progress made in ultrasound and magnetic resonance elastography; wave-based OCE has pushed to the limit the advance of three major pillars: (1) implementation of novel wave excitation methods in tissues, (2) understanding new types of mechanical waves in complex boundary conditions by proposing advance analytical and numerical models, and (3) the development of novel estimators capable of retrieving quantitative 2D/3D biomechanical information of tissues. This remarkable progress promoted a major advance in answering basic science questions and the improvement of medical disease diagnosis and treatment monitoring in several types of tissues leading, ultimately, to the first attempts of clinical trials and translational research aiming to have wave-based OCE working in clinical environments. This paper summarizes the fundamental up-to-date principles and categories of wave-based OCE, revises the timeline and the state-of-the-art techniques and applications lying in those categories, and concludes with a discussion on the current challenges and future directions, including clinical translation research.

Effect of cell imprinting on viability and drug susceptibility of breast cancer cells to doxorubicin

This study demonstrates the effect of substrate's geometrical cues on viability and the efficacy of an anti-cancer drug, doxorubicin (DOX), on breast cancer cells. It is hypothesized that the surface topographical properties can mediate the cellular drug intake. Pseudo-three dimensional (3D) platforms were fabricated using imprinting technique from polydimethylsiloxane (PDMS) and gelatin methacryloyl (GelMA) hydrogel to recapitulate topography of cells' membranes. The cells exhibited higher viability on the cell-imprinted platforms for both PDMS and GelMA materials compared to the plain/flat counterparts. For instance, MCF7 cells showed a higher metabolic activity (11.9%) on MCF7-imprinted PDMS substrate than plain PDMS. The increased metabolic activity for the imprinted GelMA was about 44.2% compared to plain hydrogel. The DOX response of cells was monitored for 24 h. Although imprinted substrates demonstrated enhanced biocompatibility, the cultured cells were more susceptible to the drug compared to the plain substrates. In particular, MCF7 cells on imprinted PDMS and GelMA substrates showed 37% and 50% higher in cell death compared to the corresponding plain PDMS and GelMA, respectively. Interestingly, the drug susceptibility of the cells on the imprinted hydrogel was about 70% higher than the cells cultured on imprinted PDMS substrates. Having MCF7 cell-imprinted substrates, DOX responses of two other breast cancer cell lines, SKBR3 and ZR-75-1, were also evaluated. The results support that cell membrane curvature developed by multiscale topography is able to mediate intracellular signaling and drug intake. STATEMENT OF SIGNIFICANCE: Research in biological sciences and drug discovery mostly rely on two dimensional (2D) cell culture techniques which cannot provide a reliable physiologically relevant environment. Lack of extracellular matrix and a large shift in physicochemical properties of conventional 2D substrates can induce aberrant cellular behaviors. While chemical composition, topographical, and mechanical properties of substrates have remarkable impacts on drug susceptibility, gene expression, and protein synthesis, the most cell culture plates are from rigid and plain substrates. A number of (bio)polymeric 3D-platforms have been introduced to resemble innate cell microenvironment. However, their intricate culture protocols restrain their applications in demanding high-throughput drug screening. To address the above concerns, in the present study, a hydrogel-based pseudo-3D substrate with imprinted cell features has been introduced.

3D normalized cross-correlation for estimation of the displacement field in ultrasound elastography

This paper introduces a novel technique to estimate tissue displacement in quasi-static elastography. A major challenge in elastography is estimation of displacement (also referred to time-delay estimation) between pre-compressed and post-compressed ultrasound data. Maximizing normalized cross correlation (NCC) of ultrasound radio-frequency (RF) data of the pre- and post-compressed images is a popular technique for strain estimation due to its simplicity and computational efficiency. Several papers have been published to increase the accuracy and quality of displacement estimation based on NCC. All of these methods use 2D spatial windows in RF data to estimate NCC, wherein displacement is assumed to be constant within each window. In this work, we extend this assumption along the third dimension. Two approaches are proposed to get third dimension. In the first approach, we use temporal domain to exploit neighboring samples in both spatial and temporal directions. Considering temporal information is important since traditional and ultrafast ultrasound machines are, respectively, capable of imaging at more than 30 frame per second (fps) and 1000 fps. Another approach is to use time-delayed pre-beam formed data (channel data) instead of RF data. In this method information of all channels that are recorded as pre-beam formed data of each RF line will be considered as 3^rd dimension. We call these methods as spatial temporal normalized cross correlation (STNCC) and channel data normalized cross correlation (CNCC) and show that they substantially outperforms NCC using simulation, phantom and in-vivo experiments. Given substantial improvements of results in addition to the relative simplicity of implementing STNCC and CNCC, the proposed approaches can potentially have a large impact in both academic and commercial work on ultrasound elastography.

Modeling Uncertainty of Strain Ratio Measurements in Ultrasound Breast Strain Elastography: A Factorial Experiment

Strain elastography (SE) is a technique in which images of localized tissue strains are used to detect the relative stiffness of tissues. The application of SE in differentiating malignant breast lesions from benign ones has been broadly investigated. The strain ratio (SR) between the background and the breast tumor has been used and its results have been mixed. Due to the complex nature of tissue elasticity and how it relates to the strain fields measured in SE, the exact reason is not known. In this study, we apply a novel design-of-experiments-based metamodeling approach to mechanical simulation of SE in the human breast. To our knowledge, such a study has not been reported in the ultrasound SE literature. More specifically, we first conduct a screening study to identify the biomechanical factors/simulation inputs that most strongly determine SR. We then apply a response surface experimental design to these factors to produce a metamodel of SR as a function of said factors. Results from the screening study suggest that the SR measurements are primarily influenced by three factors: the initial shear modulus of the lesion, the elastic nonlinearity of the lesion, and the precompression applied during acquisition. In order to investigate the implications of these results, stochastic inputs for these three factors associated with the malignant and benign cases were applied to the resulting response surface. The resulting optimal cutoffs, sensitivity, and specificity were generally in line with a majority (>60%) of 19 clinical trials in the literature.

A Spline Interpolation-based Data Reconstruction Technique for Estimation of Strain Time Constant in Ultrasound Poroelastography

Ultrasound poroelastography is a cost-effective and noninvasive imaging technique, which can be used to reconstruct mechanical parameters of tissues such as Young's modulus, Poisson's ratio, interstitial permeability, and vascular permeability. To estimate interstitial permeability and vascular permeability using poroelastography, accurate estimation of the strain time constant (TC) is required. This can be a challenging task due to the nonlinearity of the exponential strain curve and noise affecting the experimental data. Due to motion artifacts caused by the sonographer, animal/patient, and/or the environment, noise affecting some strain frames can be significantly higher than the strain signal. If these frames are used for the computation of the strain TC, the resulting TC estimate can be highly inaccurate, which, in turn, can cause high errors in the reconstructed mechanical parameters. In this paper, we introduce a cubic spline-based interpolation method, which allows to use only good quality strain frames (i.e., frames with sufficiently high signal-to-noise ratio [SNR]) to estimate the strain TC. Using finite element simulations, we demonstrate that the proposed interpolation method can improve the estimation accuracy of the strain TC by 46% with respect to the case where no interpolation and filtering are used and by 37% with respect to the case where the strain frames are Kalman filtered before TC estimation (at an SNR of 30 dB). We also prove the technical feasibility of the proposed technique using in vivo experimental data. While detecting the bad frames in both simulations and experiments, we assumed the lower limit SNR to be below 10 dB. Based on our results, the proposed technique may be of great help in applications relying on the accurate assessment of the temporal behavior of strain data.

A Robust Method to Estimate the Time Constant of Elastographic Parameters

Novel viscoelastic and poroelastic elastography techniques rely on the accurate estimation of the temporal behavior of the axial or lateral strains and related parameters. From the temporal curve of the elastographic parameter of interest, the time constant (TC) is estimated using analytical models and curve-fitting techniques such as Levenberg-Marquardt (LM), Nelder-Mead (NM), and trust-region reflective (TR). In this paper, we propose a new technique named variable projection (VP) to estimate accurately and robustly the TC and steady-state value of the elastographic parameter of interest from its temporal curve. As a testing platform, the method is used with a novel analytical model, which can be used for both poroelastic and viscoelastic tissues and in most practical experimental conditions of clinical interest. Finite element and ultrasound simulations and experimental results demonstrate that VP is robust to noise and capable of estimating the TC of the elastographic parameter with accuracy higher than that of typically employed curve-fitting techniques. The results also demonstrate that the performance of VP is not affected by an incorrect initial TC guess. For example, in simulations, VP can estimate the TC of axial strain and effective Poisson's ratio accurately for initial guesses ranging from 0.001 to infinite times of the true TC value even in fairly noisy conditions (30-dB signal to noise ratio). In experiments, VP always estimates the axial strain TC reliably, whereas the LM, NM, and TR methods fail to converge or converge to wrong solutions in most of the cases.

Viscoelastic biomarker for differentiation of benign and malignant breast lesion in ultra- low frequency range

Benign and malignant tumors differ in the viscoelastic properties of their cellular microenvironments and in their spatiotemporal response to very low frequency stimuli. These differences can introduce a unique viscoelastic biomarker in differentiation of benign and malignant tumors. This biomarker may reduce the number of unnecessary biopsies in breast patients. Although different methods have been developed so far for this purpose, none of them have focused on in vivo and in situ assessment of local viscoelastic properties in the ultra-low (sub-Hertz) frequency range. Here we introduce a new, noninvasive model-free method called Loss Angle Mapping (LAM). We assessed the performance results on 156 breast patients. The method was further improved by detection of out-of-plane motion using motion compensation cross correlation method (MCCC). 45 patients met this MCCC criterion and were considered for data analysis. Among this population, we found 77.8% sensitivity and 96.3% specificity (p < 0.0001) in discriminating between benign and malignant tumors using logistic regression method regarding the pre known information about the BIRADS number and size. The accuracy and area under the ROC curve, AUC, was 88.9% and 0.94, respectively. This method opens new avenues to investigate the mechanobiology behavior of different tissues in a frequency range that has not yet been explored in any in vivo patient studies.

Viscoelastic parameters as discriminators of breast masses: Initial human study results

Shear wave elastography is emerging as a clinically valuable diagnostic tool to differentiate between benign and malignant breast masses. Elastography techniques assume that soft tissue can be modelled as a purely elastic medium. However, this assumption is often violated as soft tissue exhibits viscoelastic properties. In order to explore the role of viscoelastic parameters in suspicious breast masses, a study was conducted on a group of patients using shear wave dispersion ultrasound vibrometry in the frequency range of 50–400 Hz. A total of 43 female patients with suspicious breast masses were recruited before their scheduled biopsy. Of those, 15 patients did not meet the data selection criteria. Voigt model based shear elasticity showed a significantly (p = 7.88x10^-6) higher median value for the 13 malignant masses (16.76±13.10 kPa) compared to 15 benign masses (1.40±1.12 kPa). Voigt model based shear viscosity was significantly different (p = 4.13x10^-5) between malignant (8.22±3.36 Pa-s) and benign masses (2.83±1.47 Pa-s). Moreover, the estimated time constant from the Voigt model, which is dependent on both shear elasticity and viscosity, differed significantly (p = 6.13x10^-5) between malignant (0.68±0.33 ms) and benign masses (3.05±1.95 ms). Results suggest that besides elasticity, viscosity based parameters like shear viscosity and time constant can also be used to differentiate between malignant and benign breast masses.

Modeling Ramp-hold Indentation Measurements based on Kelvin-Voigt Fractional Derivative Model

Interpretation of experimental data from micro- and nano-scale indentation testing is highly dependent on the constitutive model selected to relate measurements to mechanical properties. The Kelvin-Voigt Fractional Derivative model (KVFD) offers a compact set of viscoelastic features appropriate for characterizing soft biological materials. This paper provides a set of KVFD solutions for converting indentation testing data acquired for different geometries and scales into viscoelastic properties of soft materials. These solutions, which are mostly in closed-form, apply to ramp-hold relaxation, load-unload and ramp-load creep-testing protocols. We report on applications of these model solutions to macro- and nano-indentation testing of hydrogels, gastric cancer cells and ex vivo breast tissue samples using an Atomic Force Microscope (AFM). We also applied KVFD models to clinical ultrasonic breast data using a compression plate as required for elasticity imaging. Together the results show that KVFD models fit a broad range of experimental data with a correlation coefficient typically R2 > 0.99. For hydrogel samples, estimation of KVFD model parameters from test data using spherical indentation versus plate compression as well as ramp relaxation versus load-unload compression all agree within one standard deviation. Results from measurements made using macro- and nano-scale indentation agree in trend. For gastric cell and ex vivo breast tissue measurements, KVFD moduli are, respectively, 1/3 - 1/2 and 1/6 of the elasticity modulus found from the Sneddon model. In vivo breast tissue measurements yield model parameters consistent with literature results. The consistency of results found for a broad range of experimental parameters suggest the KVFD model is a reliable tool for exploring intrinsic features of the cell/tissue microenvironments.

Acoustic Radiation Force-Induced Creep-Recovery (ARFICR): A Noninvasive Method to Characterize Tissue Viscoelasticity

Ultrasound shear wave elastography is a promising noninvasive, low cost, and clinically viable tool for liver fibrosis staging. Current shear wave imaging technologies on clinical ultrasound scanners ignore shear wave dispersion and use a single group velocity measured over the shear wave bandwidth to estimate tissue elasticity. The center frequency and bandwidth of shear waves induced by acoustic radiation force depend on the ultrasound push beam (push duration, -number, etc.) and the viscoelasticity of the medium, and therefore are different across scanners from different vendors. As a result, scanners from different vendors may give different tissue elasticity measurements within the same patient. Various methods have been proposed to evaluate shear wave dispersion to better estimate tissue viscoelasticity. A rheological model such as the Kelvin-Voigt model is typically fitted to the shear wave dispersion to solve for the elasticity and viscosity of tissue. However, these rheological models impose strong assumptions about frequency dependence of elasticity and viscosity. Here, we propose a new method called Acoustic Radiation Force Induced Creep-Recovery (ARFICR) capable of quantifying rheological model-independent measurements of elasticity and viscosity for more robust tissue health assessment. In ARFICR, the creep-recovery time signal at the focus of the push beam is used to calculate the relative elasticity and viscosity (scaled by an unknown constant) over a wide frequency range. Shear waves generated during the ARFICR measurement are also detected and used to calculate the shear wave velocity at its center frequency, which is then used to calibrate the relative elasticity and viscosity to absolute elasticity and viscosity. In this paper, finite-element method simulations and experiments in tissue mimicking phantoms are used to validate and characterize the extent of viscoelastic quantification of ARFICR. The results suggest that ARFICR can measure tissue viscoelasticity reliably. Moreover, the results showed the strong frequency dependence of viscoelastic parameters in tissue mimicking phantoms and healthy liver.

Automated In Vivo Sub-Hertz Analysis of Viscoelasticity (SAVE) for Evaluation of Breast Lesions

We present an automated method for acquiring images and contrast parameters based on mechanical properties of breast lesions and surrounding tissue at load frequencies less than 1 Hz. The method called sub-Hertz analysis of viscoelasticity (SAVE) uses a compression device integrated with ultrasound imaging to perform in vivo ramp-and-hold uniaxial creep-like test on human breast in vivo. It models the internal deformations of tissues under constant surface stress as a linear viscoelastic response. We first discuss different aspects of our unique measurement approach and the expected variability of the viscoelastic parameters estimated based on a simplified one-dimensional reconstruction model. Finite-element numerical analysis is used to justify the advantages of using imaging contrast over viscoelasticity values. We then present the results of SAVE applied to a group of patients with breast masses undergoing biopsy.

Viscoelasticity Mapping by Identification of Local Shear Wave Dynamics

Estimation of soft tissue elasticity is of interest in several clinical applications. For instance, tumors and fibrotic lesions are notoriously stiff compared with benign tissue. A fully quantitative measure of lesion stiffness can be obtained by shear wave (SW) elastography. This method uses an acoustic radiation force to produce laterally propagating SWs that can be tracked to obtain the velocity, which in turn is related to Young's modulus. However, not only elasticity, but also viscosity plays an important role in the propagation process of SWs. In fact, viscosity itself is a parameter of diagnostic value for the detection and characterization of malignant lesions. In this paper, we describe a new method that enables imaging viscosity from SW elastography by local model-based system identification. By testing the method on simulated data sets and performing in vitro experiments, we show that the ability of the proposed technique to generate parametric maps of the viscoelastic material properties from SW measurements, opening up new possibilities for noninvasive tissue characterization.

Automated Compression Device for Viscoelasticity Imaging

Noninvasive measurement of tissue viscoelastic properties is gaining more attention for screening and diagnostic purposes. Recently, measuring dynamic response of tissue under a constant force has been studied for estimation of tissue viscoelastic properties in terms of retardation times. The essential part of such a test is an instrument that is capable of creating a controlled axial force and is suitable for clinical applications. Such a device should be lightweight, portable, and easy to use for patient studies to capture tissue dynamics under external stress. In this paper, we present the design of an automated compression device for studying the creep response of materials with tissue-like behaviors. The device can be used to apply a ramp-and-hold force excitation for a predetermined duration of time and it houses an ultrasound probe for monitoring the creep response of the underlying tissue. To validate the performance of the device, several creep tests were performed on tissue-mimicking phantoms, and the results were compared against those from a commercial mechanical testing instrument. Using a second-order Kelvin-Voigt model and surface measurement of the forces and displacements, retardation times T1 and T2 were estimated from each test. These tests showed strong agreement between our automated compression device and the commercial mechanical testing system, with an average relative error of 2.9% and 12.4%, for T1 and T2, respectively. Also, we present the application of compression device to measure local retardation times for four different phantoms with different size and stiffness.

Virtual Breast Quasi-static Elastography (VBQE)

Viscoelasticity Imaging (VEI) has been proposed to measure relaxation time constants for characterization of in vivo breast lesions. In this technique, an external compression force on the tissue being imaged is maintained for a fixed period of time to induce strain creep. A sequence of ultrasound echo signals is then utilized to generate time-resolved strain measurements. Relaxation time constants can be obtained by fitting local time-resolved strain measurements to a viscoelastic tissue model (e.g., a modified Kevin-Voigt model). In this study, our primary objective is to quantitatively evaluate the contrast transfer efficiency (CTE) of VEI, which contains useful information regarding image interpretations. Using an open-source simulator for virtual breast quasi-static elastography (VBQE), we conducted a case study of contrast transfer efficiency of VEI. In multiple three-dimensional (3D) numerical breast phantoms containing various degrees of heterogeneity, finite element (FE) simulations in conjunction with quasi-linear viscoelastic constitutive tissue models were performed to mimic data acquisition of VEI under freehand scanning. Our results suggested that there were losses in CTE, and the losses could be as high as -18 dB. FE results also qualitatively corroborated clinical observations, for example, artifacts around tissue interfaces.

Normalization of compression-induced hemodynamics in patients responding to neoadjuvant chemotherapy monitored by dynamic tomographic optical breast imaging (DTOBI)

We characterize novel breast cancer imaging biomarkers for monitoring neoadjuvant chemotherapy (NACT) and predicting outcome. Specifically, we recruited 30 patients for a pilot study in which NACT patients were imaged using dynamic tomographic optical breast imaging (DTOBI) to quantify the hemodynamic changes due to partial mammographic compression. DTOBI scans were obtained pre-treatment (referred to as day 0), as well as 7 and 30 days into therapy on female patients undergoing NACT. We present data for the 13 patients who participated in both day 0 and 7 measurements and had evaluable data, of which 7 also returned for day 30 measurements. We acquired optical images over 2 minutes following 4-8 lbs (18-36 N) of compression. The timecourses of tissue-volume averaged total hemoglobin (HbT), as well as hemoglobin oxygen saturation (SO₂) in the tumor vs. surrounding tissues were compared. Outcome prediction metrics based on the differential behavior in tumor vs. normal areas for responders (>50% reduction in maximum diameter) vs. non-responders were analyzed for statistical significance. At baseline, all patients exhibit an initial decrease followed by delayed recovery in HbT, and SO₂ in the tumor area, in contrast to almost immediate recovery in surrounding tissue. At day 7 and 30, this contrast is maintained in non-responders; however, in responders, the contrast in hemodynamic time-courses between tumor and normal tissue starts decreasing at day 7 and substantially disappears at day 30. At day 30 into NACT, responding tumors demonstrate "normalization" of compression induced hemodynamics vs. surrounding normal tissue whereas non-responding tumors did not. This data suggests that DTOBI imaging biomarkers, which are governed by the interplay between tissue biomechanics and oxygen metabolism, may be suitable for guiding NACT by offering early predictions of treatment outcome.

Optimization of a Pixel-to-Pixel Curve-Fitting Method for Poroelastography Imaging

Ultrasound poroelastography is an imaging modality used to characterize the temporal behavior of soft tissue that can be modeled as a solid permeated by interconnected pores filled with liquid (poroelastic medium). It could be useful in the stage classification of lymphedema. Generally, time-constant models are applied to strain images, and precision of the fitting process, computational cost and versatility in response to changes in tissues properties are crucial aspects of clinical applications. In the work described here, we performed creep experiments on poroelastic phantoms and used rheologic models to visualize the changes in viscoelastic response associated with fluid mobility. We used the Levenberg-Marquardt algorithm as a fitting tool and performed parametric studies to improve its performance. On the basis of these studies, we proposed an optimization schema for the pixel-to-pixel curve-fitting process. We determined that the bimodal Kelvin-Voigt model describes efficiently the temporal evolution of the strain images in heterogeneous phantoms.

Gelatin Methacrylate Hydrogels as Biomimetic Three-Dimensional Matrixes for Modeling Breast Cancer Invasion and Chemoresponse in Vitro

Recent studies have shown that three-dimensional (3D) culture environments allow the study of cellular responses in a setting that more closely resembles the in vivo milieu. In this context, hydrogels have become popular scaffold options for the 3D cell culture. Because the mechanical and biochemical properties of culture matrixes influence crucial cell behavior, selecting a suitable matrix for replicating in vivo cellular phenotype in vitro is essential for understanding disease progression. Gelatin methacrylate (GelMA) hydrogels have been the focus of much attention because of their inherent bioactivity, favorable hydration and diffusion properties, and ease-of-tailoring of their physicochemical characteristics. Therefore, in this study we examined the efficacy of GelMA hydrogels as a suitable platform to model specific attributes of breast cancer. We observed increased invasiveness in vitro and increased tumorigenic ability in vivo in breast cancer cells cultured on GelMA hydrogels. Further, cells cultured on GelMA matrixes were more resistant to paclitaxel treatment, as shown by the results of cell-cycle analysis and gene expression. This study, therefore, validates GelMA hydrogels as inexpensive, cell-responsive 3D platforms for modeling key characteristics associated with breast cancer metastasis, in vitro.

Effect of temporal acquisition parameters on image quality of strain time constant elastography

Ultrasound methods to image the time constant (TC) of elastographic tissue parameters have been recently developed. Elastographic TC images from creep or stress relaxation tests have been shown to provide information on the viscoelastic and poroelastic behavior of tissues. However, the effect of temporal ultrasonic acquisition parameters and input noise on the image quality of the resultant strain TC elastograms has not been fully investigated yet. Understanding such effects could have important implications for clinical applications of these novel techniques. This work reports a simulation study aimed at investigating the effects of varying windows of observation, acquisition frame rate, and strain signal-to-noise ratio (SNR) on the image quality of elastographic TC estimates. A pilot experimental study was used to corroborate the simulation results in specific testing conditions. The results of this work suggest that the total acquisition time necessary for accurate strain TC estimates has a linear dependence to the underlying strain TC (as estimated from the theoretical strain-vs.-time curve). The results also indicate that it might be possible to make accurate estimates of the elastographic TC (within 10% error) using windows of observation as small as 20% of the underlying TC, provided sufficiently fast acquisition rates (>100 Hz for typical acquisition depths). The limited experimental data reported in this study statistically confirm the simulation trends, proving that the proposed model can be used as upper bound guidance for the correct execution of the experiments.

Parametric imaging of viscoelasticity using optical coherence elastography

We demonstrate imaging of soft tissue viscoelasticity using optical coherence elastography. Viscoelastic creep deformation is induced in tissue using step-like compressive loading and the resulting time-varying deformation is measured using phase-sensitive optical coherence tomography. From a series of co-located B-scans, we estimate the local strain rate as a function of time, and parameterize it using a four-parameter Kelvin-Voigt model of viscoelastic creep. The estimated viscoelastic strain and time constant are used to visualize viscoelastic creep in 2D, dual-parameter viscoelastograms. We demonstrate our technique on six silicone tissue-simulating phantoms spanning a range of viscoelastic parameters. As an example in soft tissue, we report viscoelastic contrast between muscle and connective tissue in fresh, ex vivo rat gastrocnemius muscle and mouse abdominal transection. Imaging viscoelastic creep deformation has the potential to provide complementary contrast to existing imaging modalities, and may provide greater insight into disease pathology.

Modeling transversely isotropic, viscoelastic, incompressible tissue-like materials with application in ultrasound shear wave elastography

In this paper, we propose a method to model the shear wave propagation in transversely isotropic, viscoelastic and incompressible media. The targeted application is ultrasound-based shear wave elastography for viscoelasticity measurements in anisotropic tissues such as the kidney and skeletal muscles. The proposed model predicts that if the viscoelastic parameters both across and along fiber directions can be characterized as a Voigt material, then the spatial phase velocity at any angle is also governed by a Voigt material model. Further, with the aid of Taylor expansions, it is shown that the spatial group velocity at any angle is close to a Voigt type for weakly attenuative materials within a certain bandwidth. The model is implemented in a finite element code by a time domain explicit integration scheme and shear wave simulations are conducted. The results of the simulations are analyzed to extract the shear wave elasticity and viscosity for both the spatial phase and group velocities. The estimated values match well with theoretical predictions. The proposed theory is further verified by an ex vivo tissue experiment measured in a porcine skeletal muscle by an ultrasound shear wave elastography method. The applicability of the Taylor expansion to analyze the spatial velocities is also discussed. We demonstrate that the approximations from the Taylor expansions are subject to errors when the viscosities across or along the fiber directions are large or the maximum frequency considered is beyond the bandwidth defined by radii of convergence of the Taylor expansions.

3-D visualization and non-linear tissue classification of breast tumors using ultrasound elastography in vivo

The goal of the study described here was to introduce new methods for the classification and visualization of human breast tumors using 3-D ultrasound elastography. A tumor's type, shape and size are key features that can help the physician to decide the sort and extent of necessary treatment. In this work, tumor type, being either benign or malignant, was classified non-invasively for nine volunteer patients. The classification was based on estimating four parameters that reflect the tumor's non-linear biomechanical behavior, under multi-compression levels. Tumor prognosis using non-linear elastography was confirmed with biopsy as a gold standard. Three tissue classification parameters were found to be statistically significant with a p-value < 0.05, whereas the fourth non-linear parameter was highly significant, having a p-value < 0.001. Furthermore, each breast tumor's shape and size were estimated in vivo using 3-D elastography, and were enhanced using interactive segmentation. Segmentation with level sets was used to isolate the stiff tumor from the surrounding soft tissue. Segmentation also provided a reliable means to estimate tumors volumes. Four volumetric strains were investigated: the traditional normal axial strain, the first principal strain, von Mises strain and maximum shear strain. It was noted that these strains can provide varying degrees of boundary enhancement to the stiff tumor in the constructed elastograms. The enhanced boundary improved the performance of the segmentation process. In summary, the proposed methods can be employed as a 3-D non-invasive tool for characterization of breast tumors, and may provide early prognosis with minimal pain, as well as diminish the risk of late-stage breast cancer.

Magnetomotive optical coherence elastography for microrheology of biological tissues

Optical coherence elastography (OCE) is an established paradigm for measuring biomechanical properties of tissues and cells noninvasively, in real time, and with high resolution. We present a different development of a spectral domain OCE technique that enables simultaneous measurements of multiple biomechanical parameters of biological tissues. Our approach extends the capabilities of magnetomotive OCE (MM-OCE), which utilizes iron oxide magnetic nanoparticles (MNPs) distributed and embedded in the specimens as transducers for inducing motion. Step-wise application of an external magnetic field results in displacements in the tissue specimens that are deduced from sensitive phase measurements made with the MM-OCE system. We analyzed freshly excised rabbit lung and muscle tissues. We observe that while they present some similarities, rabbit lung and muscle tissue displacements display characteristic differentiating features. Both tissue types undergo a fast initial displacement followed by a rapidly damped oscillation and the onset of creep. However, the damping is faster in muscle compared to lung tissue, while the creep is steeper in muscle. This approach has the potential to become a novel way of performing real-time measurements of biomechanical properties of tissues and to enable the development of different diagnostic and monitoring tools in biology and medicine.

Nonlinear characterization of breast cancer using multi-compression 3D ultrasound elastography in vivo

The main objective of this article is to introduce a new nonlinear elastography based classification method for human breast masses. Multi-compression elastography imaging is elucidated in this study to differentiate malignant from benign lesions, based on their nonlinear mechanical behavior under compression. Three classification parameters were used and compared in this work: a new nonlinear parameter based on a power-law behavior of the strain difference between breast masses and healthy tissues, mass-soft tissue strain ratio and the mass relative volume between B-mode and elastography imaging. Using 3D elastography, these parameters were tested in vivo. A pilot study on 10 patients was performed, and results were compared with biopsy diagnosis as a gold standard. Initial elastography results showed a good agreement with biopsy outcomes. The new estimated nonlinear parameter had an average value of 0.163±0.063 and 1.642±0.261 for benign and malignant masses, respectively. Strain ratio values for the benign and malignant masses had an average value of 2.135±0.707 and 4.21±2.108, respectively. Relative mass volume was 0.848±0.237 and 2.18±0.522 for benign and malignant masses. In addition to the traditional normal axial strain, new strain types were used for elastography and constructed in 3D, including the first principal, maximum shear and Von Mises strains. The new strains provided an enhanced distinction of the stiff lesion from the soft tissue. In summary, the proposed elastographic techniques can be used as a noninvasive quantitative characterization tool for breast cancer, with the capability of visualizing and separating the masses in a three dimensional space. This may reduce the number of unnecessary painful breast biopsies.

Hemodynamic signature of breast cancer under fractional mammographic compression using a dynamic diffuse optical tomography system

Near infrared dynamic diffuse optical tomography measurements of breast hemodynamics during fractional mammographic compression offer a novel contrast mechanism for detecting breast cancer and monitoring chemotherapy. Tissue viscoelastic relaxation during the compression period leads to a slow reduction in the compression force and reveals biomechanical and metabolic differences between healthy and lesion tissue. We measured both the absolute values and the temporal evolution of hemoglobin concentration during 25-35 N of compression for 22 stage II and III breast cancer patients scheduled to undergo neoadjuvant chemotherapy. 17 patients were included in the group analysis (average tumor size 3.2 cm, range: 1.3-5.7 cm). We observed a statistically significant differential decrease in total and oxy-hemoglobin, as well as in hemoglobin oxygen saturation in tumor areas vs. healthy tissue, as early as 30 seconds into the compression period. The hemodynamic contrast is likely driven by the higher tumor stiffness and different viscoelastic relaxation rate, as well as the higher tumor oxygen metabolism rate.

Strain-compounding technique with ultrasound Nakagami imaging for distinguishing between benign and malignant breast tumors

PURPOSE

The scatterer properties of breast tissues are related to the presence of collagen structures, while the elasticity properties of breast tissues depend on their structural organization; these two characteristics are functionally complementary in ultrasound-based tissue characterizations. This study investigated the use of a strain-compounding technique with Nakagami imaging to provide information associated with the scatterer and elasticity characteristics of tissues when attempting to identify benign and malignant breast tumors.

METHODS

The efficacy of the proposed method was tested by collecting raw data of ultrasound backscattered signals from 50 clinical cases (25 benign tumors and 25 malignant tumors, as verified by histology biopsies). The different strain conditions were created by applying manual compression. For each region in which breast tumors were suspected, estimates of the full width at half maximum (FWHM) from the Gaussian fitting curve for the Nakagami-parameter histogram in the strain-compounding Nakagami images were divided by those of the corresponding reference Nakagami images (uncompressed images); this parameter was denoted as the FWHM ratio. Receiver operating characteristic (ROC) curve analysis was adopted to assess the diagnostic performance.

RESULTS

The results demonstrated that the difference in scatterer distributions between before and after compounding was greater for benign tumors than for malignant tumors. The FWHM ratio estimates for benign and malignant tumors were 0.76 ± 0.14 and 0.96 ± 0.06 (mean ± standard deviation), respectively (p < 0.01). The mean area under the ROC curve using the FWHM ratio estimates was 0.92, with a 95% confidence interval of 0.83-1.00.

CONCLUSIONS

These findings indicate that the strain-compounding Nakagami imaging method based on the acquisition of multiple frames under different strain states could provide objective information that would improve the ability to classify benign and malignant breast tumors.

A novel breast software phantom for biomechanical modeling of elastography

PURPOSE

In developing breast imaging technologies, testing is done with phantoms. Physical phantoms are normally used but their size, shape, composition, and detail cannot be modified readily. These difficulties can be avoided by creating a software breast phantom. Researchers have created software breast phantoms using geometric and/or mathematical methods for applications like image fusion. The authors report a 3D software breast phantom that was built using a mechanical design tool, to investigate the biomechanics of elastography using finite element modeling (FEM). The authors propose this phantom as an intermediate assessment tool for elastography simulation; for use after testing with commonly used phantoms and before clinical testing. The authors design the phantom to be flexible in both, the breast geometry and biomechanical parameters, to make it a useful tool for elastography simulation.

METHODS

The authors develop the 3D software phantom using a mechanical design tool based on illustrations of normal breast anatomy. The software phantom does not use geometric primitives or imaging data. The authors discuss how to create this phantom and how to modify it. The authors demonstrate a typical elastography experiment of applying a static stress to the top surface of the breast just above a simulated tumor and calculate normal strains in 3D and in 2D with plane strain approximations with linear solvers. In particular, they investigate contrast transfer efficiency (CTE) by designing a parametric study based on location, shape, and stiffness of simulated tumors. The authors also compare their findings to a commonly used elastography phantom.

RESULTS

The 3D breast software phantom is flexible in shape, size, and location of tumors, glandular to fatty content, and the ductal structure. Residual modulus, maps, and profiles, served as a guide to optimize meshing of this geometrically nonlinear phantom for biomechanical modeling of elastography. At best, low residues (around 1-5 KPa) were found within the phantom while errors were elevated (around 10-30 KPa) at tumor and lobule boundaries. From our FEM analysis, the breast phantom generated a superior CTE in both 2D and in 3D over the block phantom. It also showed differences in CTE values and strain contrast for deep and shallow tumors and showed significant change in CTE when 3D modeling was used. These changes were not significant in the block phantom. Both phantoms, however, showed worsened CTE values for increased input tumor-background modulus contrast.

CONCLUSIONS

Block phantoms serve as a starting tool but a next level phantom, like the proposed breast phantom, will serve as a valuable intermediate for elastography simulation before clinical testing. Further, given the CTE metrics for the breast phantom are superior to the block phantom, and vary for tumor shape, location, and stiffness, these phantoms would enhance the study of elastography contrast. Further, the use of 2D phantoms with plane strain approximations overestimates the CTE value when compared to the true CTE achieved with 3D models. Thus, the use of 3D phantoms, like the breast phantom, with no approximations, will assist in more accurate estimation of modulus, especially valuable for 3D elastography systems.

Loss tangent and complex modulus estimated by acoustic radiation force creep and shear wave dispersion

Elasticity imaging methods have been used to study tissue mechanical properties and have demonstrated that tissue elasticity changes with disease state. In current shear wave elasticity imaging methods typically only shear wave speed is measured and rheological models, e.g. Kelvin-Voigt, Maxwell and Standard Linear Solid, are used to solve for tissue mechanical properties such as the shear viscoelastic complex modulus. This paper presents a method to quantify viscoelastic material properties in a model-independent way by estimating the complex shear elastic modulus over a wide frequency range using time-dependent creep response induced by acoustic radiation force. This radiation force induced creep method uses a conversion formula that is the analytic solution of a constitutive equation. The proposed method in combination with shearwave dispersion ultrasound vibrometry is used to measure the complex modulus so that knowledge of the applied radiation force magnitude is not necessary. The conversion formula is shown to be sensitive to sampling frequency and the first reliable measure in time according to numerical simulations using the Kelvin-Voigt model creep strain and compliance. Representative model-free shear complex moduli from homogeneous tissue mimicking phantoms and one excised swine kidney were obtained. This work proposes a novel model-free ultrasound-based elasticity method that does not require a rheological model with associated fitting requirements.

Integration of crawling waves in an ultrasound imaging system. Part 2: signal processing and applications

This paper introduces methods to generate crawling wave interference patterns from the displacement fields generated from radiation force pushes on a GE Logiq 9 scanner. The same transducer and system provides both the pushing pulses to generate the shear waves and the tracking pulses to measure the displacements. Acoustic power and system limitations result in largely impulsive displacement fields. Measured displacements from pushes on either side of a region-of-interest (ROI) are used to calculate continuously varying interference patterns. This technique is explained along with a brief discussion of the conventional mechanical source-driven crawling waves for comparison. We demonstrate the method on three example cases: a gelatin-based phantom with a cylindrical inclusion, an oil-gelatin phantom and mouse livers. The oil-gelatin phantom and the mouse livers demonstrate not only shear speed estimation, but the frequency dependence of the shear wave speeds.

3-D FDTD simulation of shear waves for evaluation of complex modulus imaging

The Navier equation describing shear wave propagation in 3-D viscoelastic media is solved numerically with a finite differences time domain (FDTD) method. Solutions are formed in terms of transverse scatterer velocity waves and then verified via comparison to measured wave fields in heterogeneous hydrogel phantoms. The numerical algorithm is used as a tool to study the effects on complex shear modulus estimation from wave propagation in heterogeneous viscoelastic media. We used an algebraic Helmholtz inversion (AHI) technique to solve for the complex shear modulus from simulated and experimental velocity data acquired in 2-D and 3-D. Although 3-D velocity estimates are required in general, there are object geometries for which 2-D inversions provide accurate estimations of the material properties. Through simulations and experiments, we explored artifacts generated in elastic and dynamic-viscous shear modulus images related to the shear wavelength and average viscosity.

Performance analysis of a new real-time elastographic time constant estimator

New elastographic techniques such as poroelastography and viscoelasticity imaging aim at imaging the temporal mechanical behavior of tissues. These techniques usually involve the use of curve fitting methods being applied to noisy data to estimate new elastographic parameters. As of today, however, current elastographic implementations of poroelastography and viscoelasticity imaging methods are in general too slow and not optimized for clinical applications. Furthermore, image quality performance of these new elastographic techniques is still largely unknown due to a paucity of data and the lack of systematic studies that analyze their performance limitations. In this paper, we propose a new elastographic time constant (TC) estimator, which is based on the use of the least square error (LSE) curve-fitting method and the Levenberg-Marquardt (LM) optimization rule as applied to noisy elastographic data obtained from a material in a creep-type experiment. The algorithm is executed on a massively parallel general purpose graphics processing unit (GPGPU) to achieve real-time performance. The estimator's performance is analyzed using simulations. Experimental results obtained from poroelastic phantoms are presented as a proof of principle of the new estimator's technical applicability on real experimental data. The results of this study demonstrate that the newly proposed elastographic estimator can produce highly accurate and sensitive elastographic TC estimates in real-time and at high signal-to-noise ratios.

A viscoelastic model of a breast phantom for real-time palpation

Palpation of soft tissues helps to diagnose varying diseases within the tissues. Using a phantom, the current method of training palpation lacks for feedback of the training. Similar to a robot-assisted surgical system, a virtual reality (VR) system could be potential for such training due to its interactive nature. In such a VR system, studies revealed the observation that the human perception of objects is insensitive to subtle discrepancies in a simulation. Based upon this observation, we propose a real-time viscoelastic model of a breast phantom (as soft tissues). The model consists of a surface membrane and an inside gel. We evaluate this model through a comparison with a Finite Element Method (FEM) model, featuring physical parameters and different force contacts. The results show that the model can handle multi vertex force contact on an arbitrary location and yields reasonable accurate deformation compared to the FEM model.

Shear modulus estimation with vibrating needle stimulation

An ultrasonic shear wave imaging technique is being developed for estimating the complex shear modulus of biphasic hydropolymers including soft biological tissues. A needle placed in the medium is vibrated along its axis to generate harmonic shear waves. Doppler pulses synchronously track particle motion to estimate shear wave propagation speed. Velocity estimation is improved by implementing a k-lag phase estimator. Fitting shear-wave speed estimates to the predicted dispersion relation curves obtained from two rheological models, we estimate the elastic and viscous components of the complex shear modulus. The dispersion equation estimated using the standard linear solid-body (Zener) model is compared with that from the Kelvin-Voigt model to estimate moduli in gelatin gels in the 50 to 450 Hz shear wave frequency bandwidth. Both models give comparable estimates that agree with independent shear rheometer measurements obtained at lower strain rates.

Ultrasonic viscoelasticity imaging of nonpalpable breast lesions

The prognosis of breast cancer patients improves with early and accurate diagnosis. A small clinical study was conducted with 21 women having a single nonpalpable breast lesion, each detected mammographically with later pathology confirmation. Elasticity images were acquired on each patient to test for the ability to differentiating malignant and benign lesions. The mechanical relaxation time T(1) images showed a tissue-specific T(1) contrast that is negative for all 11 malignant lesions and positive for all 10 benign lesions. Strain images were estimated using a regularized multi-scale optical flow (ROF) algorithm. Adjustments to the input parameters to the ROF and their subsequent effects on T(1) estimation and computation time are shown to have a strong effect of diagnostic performance.

Elastography using harmonic ultrasonic imaging: a feasibility study

Tissue Harmonic Imaging (THI) is a relatively new modality that has had a significant impact in the ultrasound field. In the recent past, imaging the mechanical properties of tissues using elastography has also gained great interest. In this paper, we investigate the feasibility of combining these two state-of-the-art ultrasound-imaging modalities. The performance of elastograms obtained using harmonic ultrasonic signals is studied with simulations and compared to the performance of conventional elastograms using standard statistical methods. Experiments are used as a proof of the technical feasibility of generating tissue-harmonic elastograms using experimental harmonic signals. The results of our simulation study indicate that all image quality factors considered in this study (elastographic signal-to-noise ratio, elastographic contrast-to-noise ratio and spatial resolution) may be improved when using harmonic ultrasonic signals, provided that the ultrasound system is characterized by high bandwidth, high sampling frequency and large lateral sampling. Preliminary experimental results suggest that it is technically feasible to generate experimental elastograms using harmonic signals, provided that the sonographic signal-to-noise ratio of the pre- and postcompression harmonic frames is sufficiently high to guarantee reliable values of correlation.

Sensitivity of fluorophore-quencher labeled microbubbles to externally applied static pressure

A fluorophore-quencher (F-Q) labeled microbubble system is proposed as a sensor for measuring externally applied static pressure distribution in a tumor. To quantify the sensitivity of such an F-Q bubble system to the externally applied pressure, a model describing bubble response to the static pressure was derived. Additionally, a model connecting the fluorescence lifetime and bubble radius was developed for the basic F-Q bubble system. The sensitivity is quantified based on these models given typical parameters. Results show that it is possible to resolve as low as 1 mm Hg pressure variation when both the F-Q bubble system and the measurement system are optimized. Strategies for optimizing an F-Q bubble system are discussed.

Poro-Viscoelastic Behavior of Gelatin Hydrogels Under Compression-Implications for Bioelasticity Imaging

Ultrasonic elasticity imaging enables visualization of soft tissue deformation for medical diagnosis. Our aim is to understand the role of flow-dependent and flow-independent viscoelastic mechanisms in the response of biphasic polymeric media, including biological tissues and hydrogels, to low-frequency forces. Combining the results of confined and unconfined compression experiments on gelatin hydrogels with finite element analysis (FEA) simulations of the experiments, we explore the role of polymer structure, loading, and boundary conditions in generating contrast for viscoelastic features. Feature estimation is based on comparisons between the biphasic poro-elastic and biphasic poro-viscoelastic (BPVE) material models, where the latter adds the viscoelastic response of the solid polymer matrix. The approach is to develop a consistent FEA material model (BPVE) from confined compression-stress relaxation measurements to extract the strain dependent hydraulic permeability variation and cone-plate rheometer measurements to obtain the flow-independent viscoelastic constants for the solid-matrix phase. The model is then applied to simulate the unconfined compression experiment to explore the mechanics of hydropolymers under conditions of quasi-static elasticity imaging. The spatiotemporal distributions of fluid and solid-matrix behavior within the hydrogel are studied to propose explanations for strain patterns that arise during the elasticity imaging of heterogeneous media.

Quasi-Static Ultrasound Elastography

Elastography is a new imaging modality where elastic tissue parameters related to the structural organization of normal and pathological tissues are imaged. Basic principles underlying the quasi-static elastography concept and principles are addressed. The rationale for elastographic imaging is reinforced using data on elastic properties of normal and abnormal soft tissues. The several orders of magnitude difference between the elastic modulus of normal and abnormal tissues which is the primary contrast mechanism in elastographic imaging underlines the probability of success with this imaging modality. Recent advances enabling the clinical practice of elastographic imaging in real-time on clinical ultrasound systems is also discussed.In quasi-static elastography, radiofrequency echo signals acquired before and after a small (about 1%) of applied deformation are correlated to estimate tissue displacements. Local tissue displacement vector estimates between small segments of the pre- and post-deformation signals are estimated and the corresponding strain distribution imaged. Elastographic imaging techniques are based on the hypothesis that soft tissues deform more than stiffer tissue, and these differences can be quantified in images of the tissue strain tensor or the Young's modulus.Clinical applications of quasi-static elastography have mushroomed over the last decade, with the most commonly imaged areas being the breast, prostate, thyroid, cardiac, treatment monitoring of ablation procedures and vascular imaging applications.

Material properties from acoustic radiation force step response

An ultrasonic technique for estimating viscoelastic properties of hydrogels, including engineered biological tissues, is being developed. An acoustic radiation force is applied to deform the gel locally while Doppler pulses track the induced movement. The system efficiently couples radiation force to the medium through an embedded scattering sphere. A single-element, spherically-focused, circular piston element transmits a continuous-wave burst to suddenly apply and remove a radiation force to the sphere. Simultaneously, a linear array and spectral Doppler technique are applied to track the position of the sphere over time. The complex shear modulus of the gel was estimated by applying a harmonic oscillator model to measurements of time-varying sphere displacement. Assuming that the stress-strain response of the surrounding gel is linear, this model yields an impulse response function for the gel system that may be used to estimate material properties for other load functions. The method is designed to explore the force-frequency landscape of cell-matrix viscoelasticity. Reported measurements of the shear modulus of gelatin gels at two concentrations are in close agreement with independent rheometer measurements of the same gels. Accurate modulus measurements require that the rate of Doppler-pulse transmission be matched to a priori estimates of gel properties.

Fractional derivative models for ultrasonic characterization of polymer and breast tissue viscoelasticity

The viscoelastic response of hydropolymers, which include glandular breast tissues, may be accurately characterized for some applications with as few as 3 rheological parameters by applying the Kelvin-Voigt fractional derivative (KVFD) modeling approach. We describe a technique for ultrasonic imaging of KVFD parameters in media undergoing unconfined, quasi-static, uniaxial compression. We analyze the KVFD parameter values in simulated and experimental echo data acquired from phantoms and show that the KVFD parameters may concisely characterize the viscoelastic properties of hydropolymers. We then interpret the KVFD parameter values for normal and cancerous breast tissues and hypothesize that this modeling approach may ultimately be applied to tumor differentiation.

pH-induced contrast in viscoelasticity imaging of biopolymers

Understanding contrast mechanisms and identifying discriminating features is at the heart of diagnostic imaging development. This paper focuses on how pH influences the viscoelastic properties of biopolymers to better understand the effects of extracellular pH on breast tumour elasticity imaging. Extracellular pH is known to decrease as much as 1 pH unit in breast tumours, thus creating a dangerous environment that increases cellular mutation rates and therapeutic resistance. We used a gelatin hydrogel phantom to isolate the effects of pH on a polymer network with similarities to the extracellular matrix in breast stroma. Using compressive unconfined creep and stress relaxation measurements, we systematically measured the viscoelastic features sensitive to pH by way of time-domain models and complex modulus analysis. These results are used to determine the sensitivity of quasi-static ultrasonic elasticity imaging to pH. We found a strong elastic response of the polymer network to pH, such that the matrix stiffness decreases as pH was reduced; however, the viscous response of the medium to pH was negligible. While physiological features of breast stroma such as proteoglycans and vascular networks are not included in our hydrogel model, observations in this study provide insight into viscoelastic features specific to pH changes in the collagenous stromal network. These observations suggest that the large contrast common in breast tumours with desmoplasia may be reduced under acidic conditions, and that viscoelastic features are unlikely to improve discriminability.

Ultrasonic viscoelasticity imaging of nonpalpable breast tumors: preliminary results

RATIONALE AND OBJECTIVES

Improvements in the diagnosis of early breast cancers depend on a physician's ability to obtain the information necessary to distinguish nonpalpable malignant and benign tumors. Viscoelastic features that describe mechanical properties of tissues may help to distinguish these types of lesions.

MATERIALS AND METHODS

Twenty-one patients with nonpalpable, pathology-confirmed Breast Imaging Reporting and Data System (BIRADS) 4 or 5 breast lesions (10 benign, 11 malignant) detected by mammography were studied. Viscoelastic parameters were extracted from a time sequence of ultrasonic strain images, and differences in the parameters between malignant and benign tumors were compared. Parametric data were color coded and superimposed on sonograms.

RESULTS

The strain retardance time parameter, T(1), provided the best discrimination between malignant and benign tumors (P < .01). T(1) measures the time required for tissues to fully deform (strain) once compressed; therefore, it describes the time-varying viscous response of tissue to a small deforming force. Compared to the surrounding background tissues, malignant lesions have smaller average T(1) values, whereas benign lesions have higher T(1) values. This tissue-specific contrast correlates with known changes in the extracellular matrix of breast stroma.

CONCLUSION

Characterization of nonpalpable breast lesions is improved by the addition of viscoelastic strain imaging parameters. The differentiation of malignant and benign BI-RADS 4 or 5 tumors is especially evident with the use of the retardation time estimates, T(1).

Dynamic functional and mechanical response of breast tissue to compression

Physiological tissue dynamics following breast compression offer new contrast mechanisms for evaluating breast health and disease with near infrared spectroscopy. We monitored the total hemoglobin concentration and hemoglobin oxygen saturation in 28 healthy female volunteers subject to repeated fractional mammographic compression. The compression induces a reduction in blood flow, in turn causing a reduction in hemoglobin oxygen saturation. At the same time, a two phase tissue viscoelastic relaxation results in a reduction and redistribution of pressure within the tissue and correspondingly modulates the tissue total hemoglobin concentration and oxygen saturation. We observed a strong correlation between the relaxing pressure and changes in the total hemoglobin concentration bearing evidence of the involvement of different vascular compartments. Consequently, we have developed a model that enables us to disentangle these effects and obtain robust estimates of the tissue oxygen consumption and blood flow. We obtain estimates of 1.9+/-1.3 micromol/100 mL/min for OC and 2.8+/-1.7 mL/100 mL/min for blood flow, consistent with other published values.