Visualization and quantification of breast cancer biomechanical properties with magnetic resonance elastography

A tissue stabilization device for MRI-guided breast biopsy

We present a breast tissue stabilization device that can be used in magnetic resonance imaging-guided biopsy. The device employs adjustable support plates with an optimized geometry to minimize the biopsy target displacement using smaller compression than the conventional parallel plates approach. It is expected that the reduced compression will cause less patient discomfort and improve image quality by enhancing the contrast intake. Precomputed optimal positions of the stabilization plates for a given biopsy target location are provided in a look-up table. The results of several experiments with a prototype of the device carried out on chicken breast tissue demonstrate the effectiveness of the new design when compared with conventional stabilization methods. The proposed stabilization mechanism provides excellent flexibility in selecting the needle insertion point and can be used in manual as well as robot-assisted biopsy procedures.

Sound transmission in the chest under surface excitation: an experimental and computational study with diagnostic applications

Chest physical examination often includes performing chest percussion, which involves introducing sound stimulus to the chest wall and detecting an audible change. This approach relies on observations that underlying acoustic transmission, coupling, and resonance patterns can be altered by chest structure changes due to pathologies. More accurate detection and quantification of these acoustic alterations may provide further useful diagnostic information. To elucidate the physical processes involved, a realistic computer model of sound transmission in the chest is helpful. In the present study, a computational model was developed and validated by comparing its predictions with results from animal and human experiments which involved applying acoustic excitation to the anterior chest, while detecting skin vibrations at the posterior chest. To investigate the effect of pathology on sound transmission, the computational model was used to simulate the effects of pneumothorax on sounds introduced at the anterior chest and detected at the posterior. Model predictions and experimental results showed similar trends. The model also predicted wave patterns inside the chest, which may be used to assess results of elastography measurements. Future animal and human tests may expand the predictive power of the model to include acoustic behavior for a wider range of pulmonary conditions.

Spatially-resolved hydraulic conductivity estimation via poroelastic magnetic resonance elastography

Poroelastic magnetic resonance elastography is an imaging technique that could recover mechanical and hydrodynamical material properties of in vivo tissue. To date, mechanical properties have been estimated while hydrodynamical parameters have been assumed homogeneous with literature-based values. Estimating spatially-varying hydraulic conductivity would likely improve model accuracy and provide new image information related to a tissue's interstitial fluid compartment. A poroelastic model was reformulated to recover hydraulic conductivity with more appropriate fluid-flow boundary conditions. Simulated and physical experiments were conducted to evaluate the accuracy and stability of the inversion algorithm. Simulations were accurate (property errors were < 2%) even in the presence of Gaussian measurement noise up to 3%. The reformulated model significantly decreased variation in the shear modulus estimate (p << 0.001) and eliminated the homogeneity assumption and the need to assign hydraulic conductivity values from literature. Material property contrast was recovered experimentally in three different tofu phantoms and the accuracy was improved through soft-prior regularization. A frequency-dependence in hydraulic conductivity contrast was observed suggesting that fluid-solid interactions may be more prominent at low frequency. In vivo recovery of both structural and hydrodynamical characteristics of tissue could improve detection and diagnosis of neurological disorders such as hydrocephalus and brain tumors.

Reconstructing 3-D skin surface motion for the DIET breast cancer screening system

Digital image-based elasto-tomography (DIET) is a prototype system for breast cancer screening. A breast is imaged while being vibrated, and the observed surface motion is used to infer the internal stiffness of the breast, hence identifying tumors. This paper describes a computer vision system for accurately measuring 3-D surface motion. A model-based segmentation is used to identify the profile of the breast in each image, and the 3-D surface is reconstructed by fitting a model to the profiles. The surface motion is measured using a modern optical flow implementation customized to the application, then trajectories of points on the 3-D surface are given by fusing the optical flow with the reconstructed surfaces. On data from human trials, the system is shown to exceed the performance of an earlier marker-based system at tracking skin surface motion. We demonstrate that the system can detect a 10 mm tumor in a silicone phantom breast.

Confocal acoustic radiation force optical coherence elastography using a ring ultrasonic transducer

We designed and developed a confocal acoustic radiation force optical coherence elastography system. A ring ultrasound transducer was used to achieve reflection mode excitation and generate an oscillating acoustic radiation force in order to generate displacements within the tissue, which were detected using the phase-resolved optical coherence elastography method. Both phantom and human tissue tests indicate that this system is able to sense the stiffness difference of samples and quantitatively map the elastic property of materials. Our confocal setup promises a great potential for point by point elastic imaging in vivo and differentiation of diseased tissues from normal tissue.

Using surface markers for MRI guided breast conserving surgery: a feasibility survey

Breast MRI is frequently performed prior to breast conserving surgery in order to assess the location and extent of the lesion. Ideally, the surgeon should also be able to use the image information during surgery to guide the excision and this requires that the MR image is co-registered to conform to the patient's position on the operating table. Recent progress in MR imaging techniques has made it possible to obtain high quality images of the patient in the supine position which significantly reduces the complexity of the registration task. Surface markers placed on the breast during imaging can be located during surgery using an external tracking device and this information can be used to co-register the images to the patient. There remains the problem that in most clinical MR scanners the arm of the patient has to be placed parallel to the body whereas the arm is placed perpendicular to the patient during surgery. The aim of this study is to determine the accuracy of co-registration based on a surface marker approach and, in particular, to determine what effect the difference in a patient's arm position makes on the accuracy of tumour localization. Obtaining a second MRI of the patient where the patient's arm is perpendicular to body axes (operating room position) is not possible. Instead we obtain a secondary MRI scan where the patient's arm is above the patient's head to validate the registration. Five patients with enhancing lesions ranging from 1.5 to 80 cm(3) in size were imaged using contrast enhanced MRI with their arms in two positions. A thin-plate spline registration scheme was used to match these two configurations. The registration algorithm uses the surface markers only and does not employ the image intensities. Tumour outlines were segmented and centre of mass (COM) displacement and Dice measures of lesion overlap were calculated. The relationship between the number of markers used and the COM-displacement was also studied. The lesion COM-displacements ranged from 0.9  to 9.3 mm and the Dice overlap score ranged from 20% to 80%. The registration procedure took less than 1 min to run on a standard PC. Alignment of pre-surgical supine MR images to the patient using surface markers on the breast for co-registration therefore appears to be feasible.

A stochastic filtering approach to recover strain images from quasi-static ultrasound elastography

BACKGROUND

Model-based reconstruction algorithms have shown potentials over conventional strain-based methods in quasi-static elastographic image by using realistic finite element (FE) or bio-mechanical model constraints. However, it is still difficult to properly handle the discrepancies between the model constraint and ultrasound data, and the measurement noise.

METHODS

In this paper, we explore the usage of Kalman filtering algorithm for the estimation of strain imaging in quasi-static ultrasound elastography. The proposed strategy formulates the displacement distribution through biomechanical models, and the ultrasound-derived measurements through observation equations. Through this filtering strategy, the discrepancies are quantitatively modelled as one Gaussian white noise, and the measurement noise of ultrasound data is modelled as another independent Gaussian white noise. The optimal estimation of kinematic functions, i.e. the full displacement and velocity field, are computed through this Kalman filter. Then the strain images can be easily calculated from the estimated displacement field.

RESULTS

The accuracy and robustness of our proposed framework is first evaluated in synthetic data in controlled conditions, and the performance of this framework is then evaluated in the real data collected from elastography phantoms and patients with favourable results.

CONCLUSIONS

The potential of our algorithm is to provide the distribution of mechanically meaningful strain under a proper biomechanical model constraint. We address the model-data discrepancy and measurement noise by introducing process noise and measurement noise in our framework, and then the mechanically meaningful strain is estimated through the Kalman filter in the minimum mean square error (MMSE) sense.

Blood flow reduction in breast tissue due to mammographic compression

RATIONALE AND OBJECTIVES

This study measures hemodynamic properties such as blood flow and hemoglobin concentration and oxygenation in the healthy human breast under a wide range of compressive loads. Because many breast-imaging technologies derive contrast from the deformed breast, these load-dependent vascular responses affect contrast agent-enhanced and hemoglobin-based breast imaging.

METHODS

Diffuse optical and diffuse correlation spectroscopies were used to measure the concentrations of oxygenated and deoxygenated hemoglobin, lipid, water, and microvascular blood flow during axial breast compression in the parallel-plate transmission geometry.

RESULTS

Significant reductions (P < .01) in total hemoglobin concentration (∼30%), blood oxygenation (∼20%), and blood flow (∼87%) were observed under applied pressures (forces) of up to 30 kPa (120 N) in 15 subjects. Lipid and water concentrations changed <10%.

CONCLUSIONS

Imaging protocols based on injected contrast agents should account for variation in tissue blood flow due to mammographic compression. Similarly, imaging techniques that depend on endogenous blood contrasts will be affected by breast compression during imaging.

Non-identifiability of the Rayleigh damping material model in magnetic resonance elastography

Magnetic Resonance Elastography (MRE) is an emerging imaging modality for quantifying soft tissue elasticity deduced from displacement measurements within the tissue obtained by phase sensitive Magnetic Resonance Imaging (MRI) techniques. MRE has potential to detect a range of pathologies, diseases and cancer formations, especially tumors. The mechanical model commonly used in MRE is linear viscoelasticity (VE). An alternative Rayleigh damping (RD) model for soft tissue attenuation is used with a subspace-based nonlinear inversion (SNLI) algorithm to reconstruct viscoelastic properties, energy attenuation mechanisms and concomitant damping behavior of the tissue-simulating phantoms. This research performs a thorough evaluation of the RD model in MRE focusing on unique identification of RD parameters, μI and ρI. Results show the non-identifiability of the RD model at a single input frequency based on a structural analysis with a series of supporting experimental phantom results. The estimated real shear modulus values (μR) were substantially correct in characterising various material types and correlated well with the expected stiffness contrast of the physical phantoms. However, estimated RD parameters displayed consistent poor reconstruction accuracy leading to unpredictable trends in parameter behaviour. To overcome this issue, two alternative approaches were developed: (1) simultaneous multi-frequency inversion; and (2) parametric-based reconstruction. Overall, the RD model estimates the real shear shear modulus (μR) well, but identifying damping parameters (μI and ρI) is not possible without an alternative approach.

Reconstruction of elasticity: a stochastic model-based approach in ultrasound elastography

Background

The convectional strain-based algorithm has been widely utilized in clinical practice. It can only provide the information of relative information of tissue stiffness. However, the exact information of tissue stiffness should be valuable for clinical diagnosis and treatment.

Methods

In this study we propose a reconstruction strategy to recover the mechanical properties of the tissue. After the discrepancies between the biomechanical model and data are modeled as the process noise, and the biomechanical model constraint is transformed into a state space representation the reconstruction of elasticity can be accomplished through one filtering identification process, which is to recursively estimate the material properties and kinematic functions from ultrasound data according to the minimum mean square error (MMSE) criteria. In the implementation of this model-based algorithm, the linear isotropic elasticity is adopted as the biomechanical constraint. The estimation of kinematic functions (i.e., the full displacement and velocity field), and the distribution of Young’s modulus are computed simultaneously through an extended Kalman filter (EKF).

Results

In the following experiments the accuracy and robustness of this filtering framework is first evaluated on synthetic data in controlled conditions, and the performance of this framework is then evaluated in the real data collected from elastography phantom and patients using the ultrasound system. Quantitative analysis verifies that strain fields estimated by our filtering strategy are more closer to the ground truth. The distribution of Young’s modulus is also well estimated. Further, the effects of measurement noise and process noise have been investigated as well.

Conclusions

The advantage of this model-based algorithm over the conventional strain-based algorithm is its potential of providing the distribution of elasticity under a proper biomechanical model constraint. We address the model-data discrepancy and measurement noise by introducing process noise and measurement noise in our framework, and then the absolute values of Young’s modulus are estimated through the EFK in the MMSE sense. However, the initial conditions, and the mesh strategy will affect the performance, i.e., the convergence rate, and computational cost, etc.

Mechanics in neuronal development and repair

Biological cells are well known to respond to a multitude of chemical signals. In the nervous system, chemical signaling has been shown to be crucially involved in development, normal functioning, and disorders of neurons and glial cells. However, there are an increasing number of studies showing that these cells also respond to mechanical cues. Here, we summarize current knowledge about the mechanical properties of nervous tissue and its building blocks, review recent progress in methodology and understanding of cellular mechanosensitivity in the nervous system, and provide an outlook on the implications of neuromechanics for future developments in biomedical engineering to aid overcoming some of the most devastating and currently incurable CNS pathologies such as spinal cord injuries and multiple sclerosis.

Strain-encoded breast MRI in phantom and ex vivo specimens with histological validation: preliminary results

PURPOSE

To evaluate the feasibility of using strain-encoded (SENC) breast magnetic resonance images (MRI) for breast cancer detection by examining the compression and relaxation response properties in phantoms and ex vivo breast samples.

METHODS

A tissue phantom was constructed to mimic different sizes of breast masses and tissue stiffness. In addition, five human ex vivo whole breast specimens with and without masses were studied. MR data was acquired on a 3T scanner consisting of T(1)-weighted, fat suppressed spin echo T(2)-weighted, and SENC breast images. Mechanical tissue characteristics (strain) of the phantoms and breast tissue samples were measured using SENC imaging in both compression and relaxation modes. The breast tissue specimens were sectioned and stained in the same plane as the MRI for histological evaluation.

RESULTS

For the phantom, SENC images showed soft masses with quantitative strain values between 35% and 50%, while harder masses had strain values between 0% and 20%. Combined compression (CMP) and relaxation (REX) breast SENC images separately categorized all masses into three different groups. For breast SENC, the signal intensities between ex vivo breast mass and breast glandular tissue were significantly different (-7.6 ± 2.6 verses -20.6 ± 5.4 for SENC-CMP, and 4.2 ± 1.5 verses 22.6 ± 5 for SENC-REX, p < 0.05).

CONCLUSIONS

We have demonstrated that SENC breast MRI can be used to obtain mechanical tissue properties and give quantitative estimates of strain in tumors. This feasibility study provides the basis for future clinical studies.

Magnetic resonance assessment of parenchymal elasticity in normal and edematous, ventilator-injured lung

Magnetic resonance elastography (MRE) is a MR imaging method capable of spatially resolving the intrinsic mechanical properties of normal lung parenchyma. We tested the hypothesis that the mechanical properties of edematous lung exhibit local properties similar to those of a fluid-filled lung at transpulmonary pressures (P(tp)) up to 25 cm H(2)O. Pulmonary edema was induced in anesthetized female adult Sprague-Dawley rats by mechanical ventilation to a pressure of 40 cm H(2)O for ≈ 30 min. Prior to imaging the wet weight of each ex vivo lung set was measured. MRE, high-resolution T(1)-weighted spin echo and T(2)* gradient echo data were acquired at each P(tp) for both normal and injured ex vivo lungs. At P(tp)s of 6 cm H(2)O and greater, the shear stiffness of normal lungs was greater than injured lungs (P ≤ 0.0003). For P(tp)s up to 12 cm H(2)O, shear stiffness was equal to 1.00, 1.07, 1.16, and 1.26 kPa for the injured and 1.31, 1.89, 2.41, and 2.93 kPa for normal lungs at 3, 6, 9, and 12 cm H(2)O, respectively. For injured lungs MRE magnitude signal and shear stiffness within regions of differing degrees of alveolar flooding were calculated as a function of P(tp). Differences in shear stiffness were statistically significant between groups (P < 0.001) with regions of lower magnitude signal being stiffer than those of higher signal. These data demonstrate that when the alveolar space filling material is fluid, MRE-derived parenchymal shear stiffness of the lung decreases, and the lung becomes inherently softer compared with normal lung.

Quantitative imaging methods for the development and validation of brain biomechanics models

Rapid deformation of brain tissue in response to head impact or acceleration can lead to numerous pathological changes, both immediate and delayed. Modeling and simulation hold promise for illuminating the mechanisms of traumatic brain injury (TBI) and for developing preventive devices and strategies. However, mathematical models have predictive value only if they satisfy two conditions. First, they must capture the biomechanics of the brain as both a material and a structure, including the mechanics of brain tissue and its interactions with the skull. Second, they must be validated by direct comparison with experimental data. Emerging imaging technologies and recent imaging studies provide important data for these purposes. This review describes these techniques and data, with an emphasis on magnetic resonance imaging approaches. In combination, these imaging tools promise to extend our understanding of brain biomechanics and improve our ability to study TBI in silico.

A new nonlinear parameter in the developed strain-to-applied strain of the soft tissues and its application in ultrasound elasticity imaging

Strain developed under quasi-static deformation has been mostly used in ultrasound elasticity imaging (UEI) to determine the stiffness change of tissues. However, the strain measure in UEI is often less sensitive to a subtle change of stiffness. This is particularly true for Crohn's disease where we have applied strain imaging to the differentiation of acutely inflamed bowel from chronically fibrotic bowel. In this study, a new nonlinear elastic parameter of the soft tissues is proposed to overcome this limit. The purpose of this study is to evaluate the newly proposed method and demonstrate its feasibility in the UEI. A nonlinear characteristic of soft tissues over a relatively large dynamic range of strain was investigated. A simplified tissue model based on a finite element (FE) analysis was integrated with a laboratory developed ultrasound radio-frequency (RF) signal synthesis program. Two-dimensional speckle tracking was applied to this model to simulate the nonlinear behavior of the strain developed in a target inclusion over the applied average strain to the surrounding tissues. A nonlinear empirical equation was formulated and optimized to best match the developed strain-to-applied strain relation obtained from the FE simulation. The proposed nonlinear equation was applied to in vivo measurements and nonlinear parameters were further empirically optimized. For an animal model, acute and chronic inflammatory bowel disease was induced in Lewis rats with trinitrobenzene sulfonic acid (TNBS)-ethanol treatments. After UEI, histopathology and direct mechanical measurements were performed on the excised tissues. The extracted nonlinear parameter from the developed strain-to-applied strain relation differentiated the three different tissue types with 1.96 ± 0.12 for normal, 1.50 ± 0.09 for the acutely inflamed and 1.03 ± 0.08 for the chronically fibrotic tissue. T-tests determined that the nonlinear parameters between normal, acutely inflamed and fibrotic tissue types were statistically significantly different (normal/ fibrotic [p = 0.0000185], normal/acutely inflamed [p = 0.0013] and fibrotic/acutely inflamed [p = 0.0029]). This technique may provide a sensitive and robust tool to assess subtle stiffness changes in tissues such as in acutely inflamed bowel wall.

MR elastography monitoring of tissue-engineered constructs

The objective of tissue engineering (TE) is to create functional replacements for various tissues; the mechanical properties of these engineered constructs are critical to their function. Several techniques have been developed for the measurement of the mechanical properties of tissues and organs; however, current methods are destructive. The field of TE will benefit immensely if biomechanical models developed by these techniques could be combined with existing imaging modalities to enable noninvasive, dynamic assessment of mechanical properties during tissue growth. Specifically, MR elastography (MRE), which is based on the synchronization of a mechanical actuator with a phase contrast imaging pulse sequence, has the capacity to measure tissue strain generated by sonic cyclic displacement. The captured displacement is presented in shear wave images from which the complex shear moduli can be extracted or simplified by a direct measure, termed the shear stiffness. MRE has been extended to the microscopic scale, combining clinical MRE with high-field magnets, stronger magnetic field gradients and smaller, more sensitive, radiofrequency coils, enabling the interrogation of smaller samples, such as tissue-engineered constructs. The following topics are presented in this article: (i) current mechanical measurement techniques and their limitations in TE; (ii) a description of the MRE system, MRE theory and how it can be applied for the measurement of mechanical properties of tissue-engineered constructs; (iii) a summary of in vitro MRE work for the monitoring of osteogenic and adipogenic tissues originating from human adult mesenchymal stem cells (MSCs); (iv) preliminary in vivo studies of MRE of tissues originating from mouse MSCs implanted subcutaneously in immunodeficient mice with an emphasis on in vivo MRE challenges; (v) future directions to resolve current issues with in vivo MRE in the context of how to improve the future role of MRE in TE.

The tumor microenvironment is a dominant force in multidrug resistance

The emergence of clinical drug resistance is still one of the most challenging factors in cancer treatment effectiveness. Until more recently, the assumption has been that random genetic lesions are sufficient to explain the progression of malignancy and escape from chemotherapy. Here we propose an additional perspective, one in which the tumor cells despite the malignant genome could find a microenvironment either within the tumor or as a dormant cell to remain polar and blend into an organized context. Targeting this dynamic interplay could be considered a new avenue to prevent therapeutic resistance, and may even provide a promising effective cancer treatment.

Model-based elastography: a survey of approaches to the inverse elasticity problem

Elastography is emerging as an imaging modality that can distinguish normal versus diseased tissues via their biomechanical properties. This paper reviews current approaches to elastography in three areas--quasi-static, harmonic and transient--and describes inversion schemes for each elastographic imaging approach. Approaches include first-order approximation methods; direct and iterative inversion schemes for linear elastic; isotropic materials and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior. The paper's objective is to document efforts to develop elastography within the framework of solving an inverse problem, so that elastography may provide reliable estimates of shear modulus and other mechanical parameters. We discuss issues that must be addressed if model-based elastography is to become the prevailing approach to quasi-static, harmonic and transient elastography: (1) developing practical techniques to transform the ill-posed problem with a well-posed one; (2) devising better forward models to capture the complex mechanical behavior of soft tissues and (3) developing better test procedures to evaluate the performance of modulus elastograms.

Motion tracking and strain map computation for quasi-static magnetic resonance elastography

This paper presents a new imaging method for quasi-static magnetic resonance elastography (MRE). Tagged magnetic resonance (MR) imaging of human lower leg was acquired with probe indentation using a MR-compatible actuation system. Indentation force was recorded for soft tissue elasticity reconstruction. Motion tracking and strain map of human lower leg are calculated using a harmonic phase (HARP)-based method. Simulated tagged MR images were constructed and analyzed to validate the HARP-based method. Our results show that the proposed imaging method can be used to generate accurate motion distribution and strain maps of the targeted soft tissue.

Toward soft-tissue elastography using digital holography to monitor surface acoustic waves

Measuring the elasticity distribution inside the human body is of great interest because elastic abnormalities can serve as indicators of several diseases. We present a method for mapping elasticity inside soft tissues by imaging surface acoustic waves (SAWs) with digital holographic interferometry. With this method, we show that SAWs are consistent with Rayleigh waves, with velocities proportional to the square root of the elastic modulus greater than 2-40 kPa in homogeneous tissue phantoms. In two-layer phantoms, the SAW velocity transitions approximately from that of the lower layer to that of the upper layer as frequency is increased in agreement with the theoretical relationship between SAW dispersion and the depth-dependent stiffness profile. We also observed deformation in the propagation direction of SAWs above a stiff inclusion placed 8 mm below the surface. These findings demonstrate the potential for quantitative digital holography-based elastography of soft tissues as a noninvasive method for disease detection.

Viscoelastic properties of soft gels: comparison of magnetic resonance elastography and dynamic shear testing in the shear wave regime

Magnetic resonance elastography (MRE) is used to quantify the viscoelastic shear modulus, G*, of human and animal tissues. Previously, values of G* determined by MRE have been compared to values from mechanical tests performed at lower frequencies. In this study, a novel dynamic shear test (DST) was used to measure G* of a tissue-mimicking material at higher frequencies for direct comparison to MRE. A closed-form solution, including inertial effects, was used to extract G* values from DST data obtained between 20 and 200 Hz. MRE was performed using cylindrical 'phantoms' of the same material in an overlapping frequency range of 100-400 Hz. Axial vibrations of a central rod caused radially propagating shear waves in the phantom. Displacement fields were fit to a viscoelastic form of Navier's equation using a total least-squares approach to obtain local estimates of G*. DST estimates of the storage G' (Re[G*]) and loss modulus G″ (Im[G*]) for the tissue-mimicking material increased with frequency from 0.86 to 0.97 kPa (20-200 Hz, n = 16), while MRE estimates of G' increased from 1.06 to 1.15 kPa (100-400 Hz, n = 6). The loss factor (Im[G*]/Re[G*]) also increased with frequency for both test methods: 0.06-0.14 (20-200 Hz, DST) and 0.11-0.23 (100-400 Hz, MRE). Close agreement between MRE and DST results at overlapping frequencies indicates that G* can be locally estimated with MRE over a wide frequency range. Low signal-to-noise ratio, long shear wavelengths and boundary effects were found to increase residual fitting error, reinforcing the use of an error metric to assess confidence in local parameter estimates obtained by MRE.

Calculation of shear stiffness in noise dominated magnetic resonance elastography data based on principal frequency estimation

Magnetic resonance elastography (MRE) is a non-invasive phase-contrast-based method for quantifying the shear stiffness of biological tissues. Synchronous application of a shear wave source and motion encoding gradient waveforms within the MRE pulse sequence enable visualization of the propagating shear wave throughout the medium under investigation. Encoded shear wave-induced displacements are then processed to calculate the local shear stiffness of each voxel. An important consideration in local shear stiffness estimates is that the algorithms employed typically calculate shear stiffness using relatively high signal-to-noise ratio (SNR) MRE images and have difficulties at an extremely low SNR. A new method of estimating shear stiffness based on the principal spatial frequency of the shear wave displacement map is presented. Finite element simulations were performed to assess the relative insensitivity of this approach to decreases in SNR. Additionally, ex vivo experiments were conducted on normal rat lungs to assess the robustness of this approach in low SNR biological tissue. Simulation and experimental results indicate that calculation of shear stiffness by the principal frequency method is less sensitive to extremely low SNR than previously reported MRE inversion methods but at the expense of loss of spatial information within the region of interest from which the principal frequency estimate is derived.

Model-based reconstructive elasticity imaging using ultrasound

Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

Improved hardware for higher spatial resolution strain-encoded (SENC) breast MRI for strain measurements

RATIONALE AND OBJECTIVES

Early detection of breast lesions using mammography has resulted in lower mortality rates. However, some breast lesions are mammography occult, and magnetic resonance imaging (MRI) is recommended, but it has lower specificity. It is possible to achieve higher specificity by using strain-encoded (SENC) MRI and/or magnetic resonance elastography. SENC breast MRI can measure the strain properties of breast tissue. Similarly, magnetic resonance elastography is used to measure the elasticity (ie, shear stiffness) of different tissue compositions interrogating the tissue mechanical properties. Reports have shown that malignant tumors are three to 13 times stiffer than normal tissue and benign tumors.

MATERIALS AND METHODS

The investigators have developed a SENC breast hardware device capable of periodically compressing the breast, thus allowing for longer scanning time and measuring the strain characteristics of breast tissue. This hardware enables the use of SENC MRI with high spatial resolution (1 × 1 × 5 mm(3)) instead of fast SENC imaging. Simple controls and multiple safety measures were added to ensure accurate, repeatable, and safe in vivo experiments.

RESULTS

Phantom experiments showed that SENC breast MRI has higher signal-to-noise ratio and contrast-to-noise ratio than fast SENC imaging under different scanning resolutions. Finally, the SENC breast device reproducibility measurements resulted in a difference of <1 mm with a 1% strain difference.

CONCLUSIONS

SENC breast magnetic resonance images have higher signal-to-noise ratio and contrast-to-noise ratios than fast SENC images. Thus, combining SENC breast strain measurements with diagnostic breast MRI to differentiate benign from malignant lesions could potentially increase the specificity of diagnosis in the clinical setting.

Frequency-dependent viscoelastic parameters of mouse brain tissue estimated by MR elastography

Viscoelastic properties of mouse brain tissue were estimated non-invasively, in vivo, using magnetic resonance elastography (MRE) at 4.7 T to measure the dispersive properties of induced shear waves. Key features of this study include (i) the development and application of a novel MR-compatible actuation system which transmits vibratory motion into the brain through an incisor bar, and (ii) the investigation of the mechanical properties of brain tissue over a 1200 Hz bandwidth from 600-1800 Hz. Displacement fields due to propagating shear waves were measured during continuous, harmonic excitation of the skull. This protocol enabled characterization of the true steady-state patterns of shear wave propagation. Analysis of displacement fields obtained at different frequencies indicates that the viscoelastic properties of mouse brain tissue depend strongly on frequency. The average storage modulus (G') increased from approximately 1.6 to 8 kPa over this range; average loss modulus (G″) increased from approximately 1 to 3 kPa. Both moduli were well approximated by a power-law relationship over this frequency range. MRE may be a valuable addition to studies of disease in murine models, and to pre-clinical evaluations of therapies. Quantitative measurements of the viscoelastic parameters of brain tissue at high frequencies are also valuable for modeling and simulation of traumatic brain injury.

Acoustic radiation contrast in MR images for breast cancer diagnostics--initial phantom study

Acoustic radiation contrast in magnetic resonance images is an approach to visualize the changes in ultrasonic loss and viscoelastic changes of the sample with the resolution of a magnetic resonance imaging (MRI) system. By irradiating ultrasound (US) into a tissue-mimicking sample, a displacement along the US beam path caused by the acoustic radiation force is obtained. This displacement varies with the US intensity, the duration of irradiation, the US attenuation and the viscoelastic properties of the sample. US pulses of 2.5 MHz with a duration of 20 ms and an intensity of <17 W/cm(2) are used. An MRI sequence was programmed to produce images in which the magnitude of the displacement is visualized by gray value changes. In addition, a finite element simulation of the measurements was performed to demonstrate the feasibility of the method. Through examination of the measurements and the simulations, information about viscoelastic changes was achieved. In this work, measurements on different breast phantoms are presented.

Imaging the elastic properties of tissue: the 20 year perspective

After 20 years of innovation in techniques that specifically image the biomechanical properties of tissue, the evolution of elastographic imaging can be viewed from its infancy, through a proliferation of approaches to the problem to incorporation on research and then clinical imaging platforms. Ultimately this activity has culminated in clinical trials and improved care for patients. This remarkable progression represents a leading example of translational research that begins with fundamentals of science and engineering and progresses to needed improvements in diagnostic and monitoring capabilities applied to major categories of disease, surgery and interventional procedures. This review summarizes the fundamental principles, the timeline of developments in major categories of elastographic imaging, and concludes with recent results from clinical trials and forward-looking issues.

Time-harmonic magnetic resonance elastography of the normal feline brain

Imaging of the mechanical properties of in vivo brain tissue could eventually lead to non-invasive diagnosis of hydrocephalus, Alzheimer's disease and other pathologies known to alter the intracranial environment. The purpose of this work is to (1) use time-harmonic magnetic resonance elastography (MRE) to estimate the mechanical property distribution of cerebral tissue in the normal feline brain and (2) compare the recovered properties of grey and white matter. Various in vivo and ex vivo brain tissue property measurement strategies have led to the highly variable results that have been reported in the literature. MR elastography is an imaging technique that can estimate mechanical properties of tissue non-invasively and in vivo. Data was acquired in 14 felines and elastic parameters were estimated using a globo-regional nonlinear image reconstruction algorithm. Results fell within the range of values reported in the literature and showed a mean shear modulus across the subject group of 7-8 kPa with all but one animal falling within 5-15 kPa. White matter was statistically stiffer (p<0.01) than grey matter by about 1 kPa on a per subject basis. To the best of our knowledge, the results reported represent the most extensive set of estimates in the in vivo brain which have been based on MRE acquisition of the three-dimensional displacement field coupled to volumetric shear modulus image reconstruction achieved through nonlinear parameter estimation. However, the inter-subject variation in mean shear modulus indicates the need for further study, including the possibility of applying more advanced models to estimate the relevant tissue mechanical properties from the data.

Intra-operative ultrasound hand-held strain imaging for the visualization of ablations produced in the liver with a toroidal HIFU transducer: first in vivo results

The use of hand-held ultrasound strain imaging for the intra-operative real-time visualization of HIFU (high-intensity focused ultrasound) ablations produced in the liver by a toroidal transducer was investigated. A linear 12 MHz ultrasound imaging probe was used to obtain radiofrequency signals. Using a fast cross-correlation algorithm, strain images were calculated and displayed at 60 frames s(-1), allowing the use of hand-held strain imaging intra-operatively. Fourteen HIFU lesions were produced in four pigs. Intra-operative strain imaging of HIFU ablations in the liver was feasible owing to the high frame rate. The correlation between dimensions measured on gross pathology and dimensions measured on B-mode images and on strain images were R = 0.72 and R = 0.94 respectively. The contrast between ablated and non-ablated tissue was significantly higher (p < 0.05) in the strain images (22 dB) than in the B-mode images (9 dB). Strain images allowed equivalent or improved definition of ablated regions when compared with B-mode images. Real-time intra-operative hand-held strain imaging seems to be a promising complement to conventional B-mode imaging for the guidance of HIFU ablations produced in the liver during an open procedure. These results support that hand-held strain imaging outperforms conventional B-mode ultrasound and could potentially be used for the assessment of thermal therapies.

An inverse problem approach for elasticity imaging through vibroacoustics

A methodology for estimating the spatial distribution of elastic moduli using the steady-state dynamic response of solids immersed in fluids is presented. The technique relies on the ensuing acoustic field from a remotely excited solid to inversely estimate the spatial distribution of Young's modulus of biological structures (e.g., breast tissue). This work proposes the use of Gaussian radial basis functions (GRBF) to represent the spatial variation of elastic moduli. GRBF are shown to possess the advantage of representing smooth functions with quasi-compact support and can efficiently represent elastic moduli distributions such as those that occur in soft biological tissue in the presence of unhealthy tissue (e.g., tumors and calcifications). The direct problem consists of a coupled acoustic-structure interaction boundary-value problem solved in the frequency domain using the finite element method. The inverse problem is cast as an optimization problem in which the error functional is defined as a measure of discrepancy between an experimentally measured response and a finite element representation of the system. Nongradient based optimization algorithms are used to solve the resulting optimization problem. The feasibility of the proposed approach is demonstrated through a series of simulations and an experiment. For comparison purposes, the surface velocity response was also used for the inverse characterization as the measured response in place of the acoustic pressure.

Magnetic resonance elastography: a general overview of its current and future applications in brain imaging

Magnetic resonance elastography (MRE) has been developed over the last few years as a non-invasive means of evaluating the elasticity of biological tissues. The presence of the skull has always prevented semeiotic palpation of the brain, but MRE now offers the possibility of "palpating by imaging" in order to detect brain consistency under physiological and pathological conditions. The aim of this article is to review the current state-of-the-art of MRE imaging and discuss its possible future diagnostic applications in neuroscience.

Abdominal magnetic resonance elastography

Magnetic resonance elastography (MRE) is a magnetic resonance imaging-based technique for quantitatively assessing the mechanical properties of tissues based on the propagation of shear waves. Multiple studies have described many potential applications of MRE, from characterizing tumors to detecting diffuse disease processes. Studies have shown that MRE can be successfully implemented to assess abdominal organs. The first clinical application of MRE to be well documented is the detection and characterization of hepatic fibrosis, which systematically increases the stiffness of liver tissue. In this diagnostic role, it offers a safer, less expensive, and potentially more accurate alternative to invasive liver biopsy. Emerging results suggest that measurements of liver and spleen stiffness may provide an indirect way to assess portal hypertension. Preliminary studies have demonstrated that it is possible to use MRE to evaluate the mechanical properties of other abdominal structures, such as the pancreas and kidneys. Steady technical progress in developing practical protocols for applying MRE in the abdomen and the pelvis provides opportunities to explore many other potential applications of this emerging technology.

Matrix density-induced mechanoregulation of breast cell phenotype, signaling and gene expression through a FAK-ERK linkage

Mammographically dense breast tissue is one of the greatest risk factors for developing breast carcinoma, yet the associated molecular mechanisms remain largely unknown. Importantly, regions of high breast density are associated with increased stromal collagen and epithelial cell content. We set out to determine whether increased collagen-matrix density, in the absence of stromal cells, was sufficient to promote proliferation and invasion characteristic of a malignant phenotype in non-transformed mammary epithelial cells. We demonstrate that increased collagen-matrix density increases matrix stiffness to promote an invasive phenotype. High matrix stiffness resulted in increased formation of activated three-dimensional (3D)-matrix adhesions and a chronically elevated outside-in/inside-out focal adhesion (FA) kinase (FAK)-Rho signaling loop, which was necessary to generate and maintain the invasive phenotype. Moreover, this signaling network resulted in hyperactivation of the Ras-mitogen-activated protein kinase (MAPK) pathway, which promoted growth of mammary epithelial cells in vitro and in vivo and activated a clinically relevant proliferation signature that predicts patient outcome. Hence, the current data provide compelling evidence for the importance of the mechanical features of the microenvironment, and suggest that mechanotransduction in these cells occurs through a FAK-Rho-ERK signaling network with extracellular signal-regulated kinase (ERK) as a bottleneck through which much of the response to mechanical stimuli is regulated. As such, we propose that increased matrix stiffness explains part of the mechanism behind increased epithelial proliferation and cancer risk in human patients with high breast tissue density.

In vivo skin elastography with high-definition optical videos

BACKGROUND/AIMS

Continuous measurements of biomechanical properties of skin provide potentially valuable information to dermatologists for both clinical diagnosis and quantitative assessment of therapy. This paper presents an experimental study on in vivo imaging of skin elastic properties using high-definition optical videos. The objective is to (i) investigate whether skin property abnormalities can be detected in the computed strain elastograms, (ii) quantify property abnormalities with a Relative Strain Index (RSI), so that an objective rating system can be established, (iii) determine whether certain skin diseases are more amenable to optical elastography and (iv) identify factors that may have an adverse impact on the quality of strain elastograms.

METHODS

There are three steps in optical skin elastography: (i) skin deformations are recorded in a video sequence using a high-definition camcorder, (ii) a dense motion field between two adjacent video frames is obtained using a robust optical flow algorithm, with which a cumulative motion field between two frames of a larger interval is derived and (iii) a strain elastogram is computed by applying two weighted gradient filters to the cumulative motion data.

RESULTS

Experiments were carried out using videos of 25 patients. In the three cases presented in this article (hypertrophic lichen planus, seborrheic keratosis and psoriasis vulgaris), abnormal tissues associated with the skin diseases were successfully identified in the elastograms. There exists a good correspondence between the shape of property abnormalities and the area of diseased skin. The computed RSI gives a quantitative measure of the magnitude of property abnormalities that is consistent with the skin stiffness observed on clinical examinations.

CONCLUSIONS

Optical elastography is a promising imaging modality that is capable of capturing disease-induced property changes. Its main advantage is that an elastogram presents a continuous description of the spatial variation of skin properties on the pixel level that would otherwise be impossible with other sensors. Its value will be further enhanced when used with a point-wise measuring device such as a cutometer that yields absolute elasticity values.

Diagnostic value of MR elastography in addition to contrast-enhanced MR imaging of the breast-initial clinical results

OBJECTIVE

The purpose of the study was to assess the additional value of magnetic resonance (MR) elastography (MRE) to contrast-enhanced (ce) MR imaging (MRI) for breast lesion characterisation.

METHODS

Fifty-seven suspected breast lesions in 57 patients (mean age 52.4 years) were examined by ce MRI and MRE. All lesions were classified into BI-RADS categories. Viscoelastic parameters, e.g. alpha0 as an indicator of tissue stiffness, were calculated. Histology of the lesions was correlated with BI-RADS and viscoelastic properties. The positive predictive value (PPV) for malignancy, and the sensitivity and specificity of ce MRI were calculated. Receiver-operating characteristics (ROC) curves were separately calculated for both ce MRI and viscoelastic properties and conjoined to analyse the accuracy of diagnostic performance.

RESULTS

The lesions (mean size 27.6 mm) were malignant in 64.9% (n = 37) of cases. The PPV for malignancy was significantly (p < 0.0001) dependent on BI-RADS classification. The sensitivity of ce MRI for breast cancer detection was 97.3% (36/37), whereas specificity was 55% (11/20). If ce MRI was combined with alpha0, the diagnostic accuracy could be significantly increased (p < 0.05; AUC(ce MRI) = 0.93, AUC(combined) = 0.96).

CONCLUSIONS

In this study, the combination of MRE and ce MRI could increase the diagnostic performance of breast MRI. Further investigations of larger cohorts and smaller lesions (in particular those only visible on MRI) are necessary to validate these results.

Magnetic resonance elastography hardware design: A survey

Magnetic resonance elastography (MRE) is an emerging technique capable of measuring the shear modulus of tissue. A suspected tumour can be identified by comparing its properties with those of tissues surrounding it; this can be achieved even in deep-lying areas as long as mechanical excitation is possible. This would allow non-invasive methods for cancer-related diagnosis in areas not accessible with conventional palpation. An actuating mechanism is required to generate the necessary tissue displacements directly on the patient in the scanner and three different approaches, in terms of actuator action and position, exist to derive stiffness measurements. However, the magnetic resonance (MR) environment places considerable constraints on the design of such devices, such as the possibility of mutual interference between electrical components, the scanner field, and radio frequency pulses, and the physical space restrictions of the scanner bore. This paper presents a review of the current solutions that have been developed for MRE devices giving particular consideration to the design criteria including the required vibration frequency and amplitude in different applications, the issue of MR compatibility, actuation principles, design complexity, and scanner synchronization issues. The future challenges in this field are also described.

Shear wave spectroscopy for in vivo quantification of human soft tissues visco-elasticity

In vivo assessment of dispersion affecting the propagation of visco-elastic waves in soft tissues is key to understand the rheology of human tissues. In this paper, the ability of the supersonic shear imaging (SSI) technique to generate planar shear waves propagating in tissues is fully exploited. First, by strongly limiting shear wave diffraction in the imaging plane, this imaging technique enables to discriminate between the usually concomitant influences of both medium rheological properties and diffraction affecting the shear wave dispersion. Second, transient propagation of these plane shear waves in soft tissues can be measured using echographic images acquired at very high frame. In vitro and in vivo experiments demonstrate that dispersion curves, which characterize the rheological behavior of tissues by measuring the frequency dependence of shear wave speed and attenuation, can be recovered in the 75-600 Hz frequency range. Based on a phase difference algorithm, the dispersion curves are computed in 1 cm2 regions of interest from the acquired propagation movie. In vivo measurements in Biceps Brachii muscle and liver of three healthy volunteers show important differences in the rheological behavior of these different tissues. Liver tissue appears to be much more dispersive with a phase velocity ranging from approximately 1.5 m/s at 75 Hz to approximately 3 m/s at 500 Hz whereas muscle tissue shows an important anisotropy, shear waves propagating longitudinally to the muscular fibers are almost nondispersive while those propagating transversally are very dispersive with a shear wave speed ranging from 0.5 to 2 m/s between 75 and 500 Hz. The estimation of dispersion curves is local and can be performed separately in different regions of the organ. This signal processing approach based on the SSI modality introduces the new concept of in vivo shear wave spectroscopy (SWS) that could become an additional tool for tissue characterization. This paper demonstrates the in vivo ability of this SWS to quantify both local shear elasticity and dispersion in real time.

Predicting tumor location by modeling the deformation of the breast

Breast cancer is one of the biggest killers in the western world, and early diagnosis is essential for improved prognosis. The shape of the breast varies hugely between the scenarios of magnetic resonance (MR) imaging (patient lies prone, breast hanging down under gravity), X-ray mammography (breast strongly compressed) and ultrasound or biopsy/surgery (patient lies supine), rendering image fusion an extremely difficult task. This paper is concerned with the use of the finite-element method and nonlinear elasticity to build a 3-D, patient-specific, anatomically accurate model of the breast. The model is constructed from MR images and can be deformed to simulate breast shape and predict tumor location during mammography or biopsy/surgery. Two extensions of the standard elasticity problem need to be solved: an inverse elasticity problem (arising from the fact that only a deformed, stressed, state is known initially), and the contact problem of modeling compression. The model is used for craniocaudal mediolateral oblique mammographic image matching, and a number of numerical experiments are performed.

New technologies for human cancer imaging

Despite technical advances in many areas of diagnostic radiology, the detection and imaging of human cancer remains poor. A meaningful impact on cancer screening, staging, and treatment is unlikely to occur until the tumor-to-background ratio improves by three to four orders of magnitude (ie, 10(3)- to 10(4)-fold), which in turn will require proportional improvements in sensitivity and contrast agent targeting. This review analyzes the physics and chemistry of cancer imaging and highlights the fundamental principles underlying the detection of malignant cells within a background of normal cells. The use of various contrast agents and radiotracers for cancer imaging is reviewed, as are the current limitations of ultrasound, x-ray imaging, magnetic resonance imaging (MRI), single-photon emission computed tomography, positron emission tomography (PET), and optical imaging. Innovative technologies are emerging that hold great promise for patients, such as positron emission mammography of the breast and spectroscopy-enhanced colonoscopy for cancer screening, hyperpolarization MRI and time-of-flight PET for staging, and ion beam-induced PET scanning and near-infrared fluorescence-guided surgery for cancer treatment. This review explores these emerging technologies and considers their potential impact on clinical care. Finally, those cancers that are currently difficult to image and quantify, such as ovarian cancer and acute leukemia, are discussed.