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This article describes a novel system for quantitative and volumetric measurement of tissue elasticity in the prostate using simultaneous multi-frequency tissue excitation. Elasticity is computed by using a local frequency estimator to measure the three-dimensional local wavelengths of steady-state shear waves within the prostate gland. The shear wave is created using a mechanical voice coil shaker which transmits simultaneous multi-frequency vibrations transperineally. Radio frequency data is streamed directly from a BK Medical 8848 transrectal ultrasound transducer to an external computer where tissue displacement due to the excitation is measured using a speckle tracking algorithm. Bandpass sampling is used that eliminates the need for an ultra-fast frame rate to track the tissue motion and allows for accurate reconstruction at a sampling frequency that is below the Nyquist rate. A roll motor with computer control is used to rotate the transducer and obtain 3D data. Two commercially available phantoms were used to validate both the accuracy of the elasticity measurements as well as the functional feasibility of using the system for in vivo prostate imaging. The phantom measurements were compared with 3D Magnetic Resonance Elastography (MRE), where a high correlation of 96% was achieved. In addition, the system has been used in two separate clinical studies as a method for cancer identification. Qualitative and quantitative results of 11 patients from these clinical studies are presented here. Furthermore, an AUC of 0.87±0.12 was achieved for malignant vs. benign classification using a binary support vector machine classifier trained with data from the latest clinical study with leave one patient out cross-validation.

Quantitative tissue stiffness characterization using ultrasound (US) has been shown to improve prostate cancer (PCa) detection in multiple studies. Shear wave absolute vibro-elastography (SWAVE) allows quantitative and volumetric assessment of tissue stiffness using external multifrequency excitation. This article presents a proof of concept of a first-of-a-kind 3-D hand-operated endorectal SWAVE system designed to be used during systematic prostate biopsy. The system is developed with a clinical US machine, requiring only an external exciter that can be mounted directly to the transducer. Subsector acquisition of radio frequency (RF) data allows imaging of shear waves with a high effective frame rate (up to 250 Hz). The system was characterized using eight different quality assurance phantoms. Due to the invasive nature of prostate imaging, at this early stage of development, validation of in vivo human tissue was instead carried out by intercostally scanning the livers of n = 7 healthy volunteers. The results are compared with 3-D magnetic resonance elastography (MRE) and an existing 3-D SWAVE system with a matrix array transducer (M-SWAVE). High correlations were found with MRE (99% in phantoms, 94% in liver data) and with M-SWAVE (99% in phantoms, 98% in liver data).

Magnetic resonance elastography (MRE) is commonly regarded as the imaging-based gold-standard for liver fibrosis staging, comparable to biopsy. While ultrasound-based elastography methods for liver fibrosis staging have been developed, they are confined to a 1D or a 2D region of interest and to a limited depth. 3D Shear Wave Absolute Vibro-Elastography (S-WAVE) is a steady-state, external excitation, volumetric elastography technique that is similar to MRE, but has the additional advantage of multi-frequency excitation. We present a novel ultrasound matrix array implementation of S-WAVE that takes advantage of 3D imaging. We use a matrix array transducer to sample axial multi-frequency steady-state tissue motion over a volume, using a Color Power Angiography sequence. Tissue motion with the frequency components {40,50,60} and {45,55,65} Hz are acquired over a (90° lateral) × (40° elevational) × (16 cm depth) sector with an acquisition time of 12 seconds. We compute the elasticity map in 3D using local spatial frequency estimation. We characterize this new approach in tissue phantoms against measurements obtained with transient elastography and MRE. Six healthy volunteers and eight patients with chronic liver disease were imaged. Their MRE and S-WAVE volumes were aligned using T1 to B-mode registration for direct comparison in common regions of interest. S-WAVE and MRE results are correlated with R 2 = 0.92, while MRE and TE results are correlated with R 2 = 0.71. Our findings show that S-WAVE with matrix array has the potential to deliver a similar assessment of liver fibrosis as MRE in a more accessible, inexpensive way, to a broader set of patients.

Purpose: In conventional three-dimensional magnetic resonance elastography, motion encoding gradients (MEGs) synchronized to a mechanical excitation are applied separately in each direction to encode tissue displacement generated by the corresponding waves. This requires long acquisition times that introduce errors due to patient motion and may hinder clinical deployment of magnetic resonance elastography. In this article, a framework for MEGs sequence design is proposed to reduce scanning time and increase signal-to-noise ratio., Theory and Methods: The approach is based on applying MEGs in all three directions simultaneously with varying parameters, and formulation of the problem as a linear estimation of the wave properties. Multidirectional MEGs sequences are derived by setting the problem in an experimental design framework. Such designs are implemented and evaluated on simulation and phantom data., Results: Estimation error of the displacement using the proposed MEGs designs is reduced up to a factor of two in comparison with a unidirectional design with a same number of acquisitions. Alternatively, for the same error, scanning time is reduced up to a factor of three using the multidirectional designs., Conclusion: The proposed framework generalizes acquisition of magnetic resonance elastography, and allows quantification of design performance, and optimization-based derivation of designs., (© 2014 Wiley Periodicals, Inc.)

The purpose of this work was to assess trans-perineal prostate magnetic resonance elastography (MRE) for (1) repeatability in phantoms/volunteers and (2) diagnostic power as correlated with histopathology in prostate cancer patients. The three-dimensional (3D) displacement field was obtained using a fractionally encoded gradient echo sequence using a custom-made transducer. The repeatability of the method was assessed based on three repeat studies and by changing the driving frequency by 3% in studies on a phantom and six healthy volunteers. Subsequently, 11 patients were examined with MRE prior to radical prostatectomy. The areas under the receiver operating characteristic curves were calculated using a windowed voxel-to-voxel approach by comparing the 2D registered slides, masked with the Gleason score. For the repeatability study, the average intraclass correlation coefficient for elasticity images was 99% for repeat phantom studies, 98% for ±6 Hz phantom studies, 95% for volunteer repeat studies with 2 min acquisition time, 82% for ±2 Hz volunteer studies with 2 min acquisition time and 73% for repeat volunteer studies with 8 min acquisition time. For the patient study, the average elasticity was 8.2 ± 1.7 kPa in the prostate capsule, 7.5 ± 1.9 kPa in the peripheral zone (PZ), 9.7 ± 3.0 kPa in the central gland (CG) and 9.0 ± 3.4 kPa in the transition zone. In the patient study, cancerous tissue with Gleason score at least 3 + 3 was significantly (p < 0.05) different from normal tissue in 10 out of 11 cases with tumors in the PZ, and 6 out of 9 cases with tumors in the CG. However, the overall case-averaged area under the curve was 0.72 in the PZ and 0.67 in the CG. Cancerous tissue was not always stiffer than normal tissue. The inversion algorithm was sensitive to (i) vibration amplitude and displacement nodes and (ii) misalignment of the 3D wave field due to subject movement., (Copyright © 2014 John Wiley & Sons, Ltd.)

The purpose of this work was (1) to develop a magnetic resonance elastography (MRE) system for imaging of the ex vivo human prostate and (2) to assess the diagnostic power of mono-frequency and multi-frequency MRE and diffusion weighted imaging (DWI) alone and combined as correlated with histopathology in a patient study. An electromagnetic driver was designed specifically for MRE studies in small-bore MR scanners. Ex vivo prostate specimens (post-fixation) of 14 patients who underwent radical prostatectomy were imaged with MRE at 7 T (nine cases had DWI). In six patients, the MRE examination was performed at three frequencies (600, 800, 1000 Hz) to extract the power-law exponent Gamma. The images were registered to wholemount pathology slides marked with the Gleason score. The areas under the receiver-operator-characteristic curves (AUC) were calculated. The methods were validated in a phantom study and it was demonstrated that (i) the driver does not interfere with the acquisition process and (ii) the driver can generate amplitudes greater than 100 µm for frequencies less than 1 kHz. In the quantitative study, cancerous tissue with Gleason score at least 3 + 3 was distinguished from normal tissue in the peripheral zone (PZ) with an average AUC of 0.75 (Gd ), 0.75 (Gl ), 0.70 (Gamma-Gd ), 0.68 (apparent diffusion coefficient, ADC), and 0.82 (Gd  + Gl  + ADC). The differentiation between PZ and central gland was modest for Gd (p < 0.07), Gl (p < 0.06) but not significant for Gamma (p < 0.2). A correlation of 0.4 kPa/h was found between the fixation time of the prostate specimen and the stiffness of the tissue, which could affect the diagnostic power results. DWI and MRE may provide complementary information; in fact MRE performed better than ADC in distinguishing normal from cancerous tissue in some cases. Multi-frequency (Gamma) analysis did not appear to improve the results. However, in light of the effect of tissue fixation, the clinical implication of our results may be inconclusive and more experiments are needed., (Copyright © 2014 John Wiley & Sons, Ltd.)

Purpose: Ultrasound-based solutions for diagnosis and prognosis of prostate cancer are highly desirable. The authors have devised a method for detecting prostate cancer using a vibroelastography (VE) system developed in our group and a tissue classification approach based on texture analysis of VE images., Methods: The VE method applies wide-band mechanical vibrations to the tissue. Here, the authors report on the use of this system for cancer detection and show that the texture of VE images characterized by the first and the second order statistics of the pixel intensities form a promising set of features for tissue typing to detect prostate cancer. The system was used to image patients prior to radical surgery. The removed specimens were sectioned and studied by an experienced histopathologist. The authors registered the whole-mount histology sections to the ultrasound images using an automatic registration algorithm. This enabled the quantitative evaluation of the performance of the authors' imaging method in cancer detection in an unbiased manner. The authors used support vector machine (SVM) classification to measure the cancer detection performance of the VE method. Regions of tissue of size 5 × 5 mm, labeled as cancer and noncancer based on automatic registration to histology slides, were classified using SVM., Results: The authors report an area under ROC of 0.81 ± 0.10 in cancer detection on 1066 tissue regions from 203 images. All cancer tumors in all zones were included in this analysis and were classified versus the noncancer tissue in the peripheral zone. This outcome was obtained in leave-one-patient-out validation., Conclusions: The developed 3D prostate vibroelastography system and the proposed multiparametric approach based on statistical texture parameters from the VE images result in a promising cancer detection method.

Registration of histopathology to in vivo magnetic resonance imaging (MRI) of the prostate is an important task that can be used to optimize in vivo imaging for cancer detection. Such registration is challenging due to the change in volume and deformation of the prostate during excision and fixation. One approach towards this problem involves the use of an ex vivo MRI of the excised prostate specimen, followed by in vivo to ex vivo MRI registration of the prostate. We propose a novel registration method that uses a patient-specific biomechanical model acquired using magnetic resonance elastography to deform the in vivo volume and match it to the surface of the ex vivo specimen. The forces that drive the deformations are derived from a region-based energy, with the elastic potential used for regularization. The incorporation of elastography data into the registration framework allows inhomogeneous elasticity to be assigned to the in vivo volume. We show that such inhomogeneity improves the registration results by providing a physical regularization of the deformation map. The method is demonstrated and evaluated on six clinical cases.

This article presents a new approach to magnetic resonance elastography of the prostate using transperineal mechanical excitation. This approach is validated using a prostate elasticity phantom and in vivo studies of healthy volunteers. It is demonstrated that the transperineal approach can generate shear wave amplitudes on the order of 6-30 μm in the mid-gland region. The driver was implemented using an electromagnetic actuator with a hydraulic transmission system. The magnetic resonance elastography acquisition time has been reduced significantly by using a "second harmonic" approach. Displacement fields are processed using the established three-dimensional local frequency estimation algorithm. The three-dimensional curl-based direct inversion was used to calculate the local wavelength. The traveling wave expansion algorithm was used to reconstruct the wave damping image for one case. Using the proposed method, it was possible to resolve lesions of 0.5 cc in the phantom study. Repeatability experiments were performed and analyzed. The results from this study indicate that transperineal magnetic resonance elastography--without an endorectal coil--is a suitable candidate for a patient study involving multiparametric magnetic resonance imaging of prostate cancer, where magnetic resonance elastography may provide additional information for improved diagnosis and image-based surveillance., (Copyright © 2012 Wiley Periodicals, Inc.)

The finite element method is commonly used to model tissue deformation in order to solve for unknown parameters in the inverse problem of viscoelasticity. Typically, a (regular-grid) structured mesh is used since the internal geometry of the domain to be identified is not known a priori. In this work, the generation of problem-specific meshes is studied and such meshes are shown to significantly improve inverse-problem elastic parameter reconstruction. Improved meshes are generated from axial strain images, which provide an approximation to the underlying structure, using an optimization-based mesh adaptation approach. Such strain-based adapted meshes fit the underlying geometry even at coarse mesh resolutions, therefore improving the effective resolution of the reconstruction at a given mesh size/complexity. Elasticity reconstructions are then performed iteratively using the reflective trust-region method for optimizing the fit between estimated and observed displacements. This approach is studied for Young's modulus reconstruction at various mesh resolutions through simulations, yielding 40%-72% decrease in root-mean-square reconstruction error and 4-52 times improvement in contrast-to-noise ratio in simulations of a numerical phantom with a circular inclusion. A noise study indicates that conventional structured meshes with no noise perform considerably worse than the proposed adapted meshes with noise levels up to 20% of the compression amplitude. A phantom study and preliminary in vivo results from a breast tumor case confirm the benefit of the proposed technique. Not only conventional axial strain images but also other elasticity approximations can be used to adapt meshes. This is demonstrated on images generated by combining axial strain and axial-shear strain, which enhances lateral image contrast in particular settings, consequently further improving mesh-adapted reconstructions.

Prostate segmentation in B-mode images is a challenging task even when done manually by experts. In this paper we propose a 3D automatic prostate segmentation algorithm which makes use of information from both ultrasound B-mode and vibro-elastography data.We exploit the high contrast to noise ratio of vibro-elastography images of the prostate, in addition to the commonly used B-mode images, to implement a 2D Active Shape Model (ASM)-based segmentation algorithm on the midgland image. The prostate model is deformed by a combination of two measures: the gray level similarity and the continuity of the prostate edge in both image types. The automatically obtained mid-gland contour is then used to initialize a 3D segmentation algorithm which models the prostate as a tapered and warped ellipsoid. Vibro-elastography images are used in addition to ultrasound images to improve boundary detection.We report a Dice similarity coefficient of 0.87±0.07 and 0.87±0.08 comparing the 2D automatic contours with manual contours of two observers on 61 images. For 11 cases, a whole gland volume error of 10.2±2.2% and 13.5±4.1% and whole gland volume difference of -7.2±9.1% and -13.3±12.6% between 3D automatic and manual surfaces of two observers is obtained. This is the first validated work showing the fusion of B-mode and vibro-elastography data for automatic 3D segmentation of the prostate.

We study displacement and strain measurement error of dual transducers (two linear arrays, aligned orthogonally and coplanar). Displacements along the beam of each transducer are used to obtain measurements in two-dimensions. Simulations (5MHz) and experiments (10MHz) are compared to measurements with a single linear array, with and without angular compounding. Translation simulations demonstrate factors of 1.07 larger and 8.0 smaller biases in the axial and lateral directions respectively, for dual transducers compared to angular compounding. As the angle between dual transducers decreases from 90° to 40°, for 1% compression simulations, the lateral RMS error ranges from 2.1 to 3.9μm compared to 9μm with angular compounding. Simulation of dual transducer misalignment of 1mm and 2° result in errors of less than 9μm. Experiments demonstrate factors of 3.0 and 5.2 lower biases for dual transducers in the axial and lateral directions respectively compared to angular compounding., (Copyright © 2011 Elsevier B.V. All rights reserved.)

In this paper, vibro-elastography (VE), an ultrasound-based method that creates images of tissue viscoelasticity contrast, is evaluated as an imaging modality to visualize and segment the prostate. We report a clinical study to characterize the visibility of the prostate in VE images and the ability to detect the boundary of the gland. Measures for contrast, edge strength characterized by gradient and statistical intensity change at the edge, and the continuity of the edges are proposed and computed for VE and B-mode ultrasound images. Furthermore, using MRI as the gold standard, we compare the error in the computation of the volume of the gland from VE and B-mode images. The results demonstrate that VE images are superior to B-mode images in terms of contrast, with an approximately six fold improvement in contrast-to-noise ratio, and in terms of edge strength, with an approximately two fold improvement in the gradient in the direction normal to the edge. The computed volumes show that the VE images provide an accurate 3D visualization of the prostate with volume errors that are slightly lower than errors computed based on B-mode images. The total gland volume error is 8.8±2.5% for VE vs. MRI and 10.3±4.6% for B-mode vs. MRI, and the total gland volume difference is -4.6±11.1% for VE vs. MRI and -4.1±17.1% for B-mode vs. MRI, averaged over nine patients and three observers. Our results show that viscoelastic mapping of the prostate region using VE images can play an important role in improving the anatomic visualization of the prostate and has the potential of becoming an integral component of interventional procedures such as brachytherapy., (Copyright © 2011 Elsevier B.V. All rights reserved.)

The characterization of tissue viscoelastic properties requires the measurement of tissue motion over a region of interest at frequencies that significantly exceed the frame rates of conventional ultrasound systems. In this paper, we propose that the bandpass sampling technique be applied to tissue motion sampling. With this approach, high-frequency signals limited to a frequency band can be sampled and reconstructed without aliasing at a sampling frequency that is lower than the Nyquist rate. We first review this approach and discuss the selection of the tissue excitation frequency band and of the feasible sampling frequencies that allow signal reconstruction without aliasing. We then demonstrate the approach using simulations based on the finite element method and ultrasound simulations. Finally, we perform experiments on tissue-mimicking materials and demonstrate accurate motion estimation using a lower sampling rate than that required by the conventional sampling theorem. The estimated displacements were used to measure the elasticity and viscosity in a phantom in which an inclusion has been correctly delineated. Thus, with bandpass sampling, it is feasible to use conventional beamforming on diagnostic ultrasound systems to perform high-frequency dynamic elastography. The method is simple to implement because it does not require beam interleaving, additional hardware, or synchronization.

This paper describes a new ultrasound-based system for high-frame-rate measurement of periodic motion in 2-D for tissue elasticity imaging. Similarly to conventional 2-D flow vector imaging, the system acquires the RF signals from the region of interest at multiple steering angles. A custom sector subdivision technique is used to increase the temporal resolution while keeping the total acquisition time within the range suitable for real-time applications. Within each sector, 1-D motion is estimated along the beam direction. The intra- and inter-sector delays are compensated using our recently introduced delay compensation algorithm. In-plane 2-D motion vectors are then reconstructed from these delay-compensated 1-D motions. We show that Young's modulus images can be reconstructed from these 2-D motion vectors using local inversion algorithms. The performance of the system is validated quantitatively using a commercial flow phantom and a commercial elasticity phantom. At the frame rate of 1667 Hz, the estimated flow velocities with the system are in agreement with the velocity measured with a pulsed-wave Doppler imaging mode of a commercial ultrasound machine with manual angle correction. At the frame rate of 1250 Hz, phantom Young's moduli of 29, 6, and 54 kPa for the background, the soft inclusion, and the hard inclusion, are estimated to be 30, 11, and 53 kPa, respectively.

In this paper we propose a fully automatic 2D prostate segmentation algorithm using fused ultrasound (US) and elastography images. We show that the addition of information from mechanical tissue properties acquired from elastography to acoustic information from B-mode ultrasound, can improve segmentation results. Gray level edge similarity and edge continuity in both US and elastography images deform an Active Shape Model. Comparison of automatic and manual contours on 107 transverse images of the prostate show a mean absolute error of 2.6 +/- 0.9 mm and a running time of 17.9 +/- 12.2 s. These results show that the combination of the high contrast elastography images with the more detailed but low contrast US images can lead to very promising results for developing an automatic 3D segmentation algorithm.

In this paper, the effect of the boundary conditions and excitation dimensions on the speed of longitudinal waves in a medium is investigated. It is shown that with appropriate boundary conditions, a low-speed longitudinal wave can be generated in the medium which can be tracked by standard pulse-echo ultrasound motion tracking techniques. Three different cases of boundary conditions are explored in which the longitudinal wave speed in an incompressible material can be as high as the acoustic wave speed or as low as the shear wave speed. It is shown that the displacement spectrum can be used to estimate the wave speed in a viscoelastic medium. Numerical simulations with 3D viscoelastic finite element models and experiments on tissue-mimicking phantoms are performed to validate the theory.

In finite element simulation, size, shape, and placement of the elements in a model are significant factors that affect the interpolation and numerical errors of a solution. In medical simulations, such models are desired to have higher accuracy near features such as anatomical boundaries (surfaces) and they are often required to have element faces lying along these surfaces. Conventional modelling schemes consist of a segmentation step delineating the anatomy followed by a meshing step generating elements conforming to this segmentation. In this paper, a one-step energy-based model generation technique is proposed. An objective function is minimized when each element of a mesh covers similar image intensities while, at the same time, having desirable FEM characteristics. Such a mesh becomes essential for accurate models for deformation simulation, especially when the image intensities represent a mechanical feature of the tissue such as the elastic modulus. The use of the proposed mesh optimization is demonstrated on synthetic phantoms, 2D/3D brain MR images, and prostate ultrasound-elastography data.

We show that vibro-elastography, an ultrasound-based method that creates images of tissue viscoelasticity contrast, can be used for visualization and segmentation of the prostate. We use MRI as the gold standard and show that VE images yield more accurate 3D volumes of the prostate gland than conventional B-mode imaging. Furthermore, we propose two novel measures characterizing the strength and continuity of edges in noisy images. These measures, as well as contrast to noise ratio, demonstrate the utility of VE as a prostate imaging modality. The results of our study show that in addition to mapping the visco-elastic properties of tissue, VE can play a central role in improving the anatomic visualization of the prostate region and become an integral component of interventional procedures such as brachytherapy.

An iterative solution to the inverse problem of elasticity and viscosity is proposed in this paper. A finite elements model has been derived to account for the viscoelastic changes in soft tissue that is consistent with known rheological models. Using this deformation model and the observed dynamic data, the viscosity and elasticity have been reconstructed in the medium by using a Gauss-Newton based approach. Previous knowledge of the parameters on the boundaries of the medium are necessary to assure uniqueness and convergence and to obtain an accurate map of the viscoelastic properties. The methods have been studied in FEM simulations and also tested through experiments, where the viscosity and elasticity of a gelatin based phantom with an inclusion of known properties have been reconstructed successfully.