In quantitative elastography, maps of the mechanical properties of soft tissue, or elastograms, are calculated from the measured displacement data by solving an inverse problem. The model assumptions have a significant effect on elastograms. Motivated by the high sensitivity of imaging results to the model assumptions for in vivo magnetic resonance elastography of the prostate, we compared elastograms obtained with four different methods. Two finite-element method (FEM)-based methods developed by our group were compared with two other commonly used methods, local frequency estimator (LFE) and curl based direct inversion (c-DI). All the methods assume a linear isotropic elastic model, but the methods vary in their assumptions, such as local homogeneity or incompressibility, and in the specific approach used. We report results using simulations, phantom, and ex vivo and in vivo data. The simulation and phantom studies show, for regions with an inclusion, that the contrast to noise ratio (CNR) for the FEM methods is about three to five times higher than the CNR for the LFE and c-DI and the rms error is about half. The LFE method produces very smooth results (i.e., low CNR) and is fast. c-DI is faster than the FEM methods but it is only accurate in areas where elasticity variations are small. The artifacts resulting from the homogeneity assumption in c-DI is detrimental in regions with large variations. The ex vivo and in vivo results also show similar trends as the simulation and phantom studies. The c-FEM method is more sensitive to noise compared with the mixed-FEM due to higher orders derivatives. This is especially evident at lower frequencies, where the wave curvature is smaller and it is more prone to such error, causing a discrepancy in the absolute values between the mixed-FEM and c-FEM in our in vivo results. In general, the proposed FEMs use fewer simplifying assumptions and outperform the other methods but they are computationally more expensive.

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 7T (nine cases had DWI). In six patients, the MRE examination was performed at three frequencies (600, 800, 1000Hz) 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 mu m for frequencies less than 1kHz. 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 (G(d)), 0.75 (G(l)), 0.70 (Gamma-G(d)), 0.68 (apparent diffusion coefficient, ADC), and 0.82 (G(d)+G(l)+ADC). The differentiation between PZ and central gland was modest for G(d) (p<0.07), G(l) (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 (c) 2014 John Wiley & Sons, Ltd.

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. Magn Reson Med 73:1514–1525, 2015. © 2014 Wiley Periodicals, Inc.

Segmentation of the prostate in medical imaging is a challenging and important task for surgical planning and delivery of prostate cancer treatment. Automatic prostate segmentation can improve speed, reproducibility and consistency of the process. In this work, we propose a method for automatic segmentation of the prostate in magnetic resonance elastography (MRE) images. The method utilizes the complementary property of the elastogram and the corresponding T2-weighted image, which are obtained from the phase and magnitude components of the imaging signal, respectively. It follows a variational approach to propagate an active contour model based on the combination of region statistics in the elastogram and the edge map of the T2-weighted image. The method is fast and does not require prior shape information. The proposed algorithm is tested on 35 clinical image pairs from five MRE data sets, and is evaluated in comparison with manual contouring. The mean absolute distance between the automatic and manual contours is 1.8mm, with a maximum distance of 5.6mm. The relative area error is 7.6%, and the duration of the segmentation process is 2s per slice.

Our aim is to develop a clinically viable, fast‐acquisition, prostate MR elastography (MRE) system with transperineal excitation. We developed a new actively shielded electromagnetic transducer, designed to enable quick deployment and positioning within the scanner. The shielding of the transducer was optimized using simulations. We also employed a new rapid pulse sequence that encodes the three‐dimensional displacement field in the prostate gland using a fractionally encoded steady‐state gradient echo sequence, thereby shortening the acquisition time to a clinically acceptable 8–10 min. The methods were tested in two phantoms and seven human subjects (six volunteers and one patient with prostate cancer). The MRE acquisition time for 24 slices, with an isotropic resolution of 2 mm and eight phase offsets, was 8 min, and the total scan, including positioning and set‐up, was performed in 15–20 min. The phantom study demonstrated that the transducer does not interfere with the acquisition process and that it generates displacement amplitudes that exceed 100 µm even at frequencies as high as 300 Hz. In the in vivo human study, average wave amplitudes of 30 µm (46 µm at the apex) were routinely achieved within the prostate gland at 70 Hz. No pain or discomfort was reported. Results in a single patient suggest that MRE can identify cancer tumors, although this result is preliminary. The proposed methods allow the integration of prostate MRE with other multiparametric MRI methods. The results of this study clearly motivate the clinical evaluation of transperineal MRE in patients. Copyright © 2014 John Wiley & Sons, Ltd.

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.

Registration of histological slices to volumetric imaging of the prostate is an important task that can be used to optimize imaging for cancer detection. Such registration is challenging due to physical changes of the specimen during excision and fixation, and misalignment of the histological slices during preparation and digital scanning. In this work, we consider a multi-slice to volume registration method in which a stack of sparse, unaligned 2-D whole-mount histological slices is registered to a 3-D volumetric imaging of the prostate. We propose a particle filtering framework to contend with the high dimensionality of the search space and multimodal nature of the optimization. Such framework allows modeling of the uncertainty in the pose of the slices and in the imaged information, in order to derive optimal registration parameters in a Bayesian approach. Intensity-, region-, and point-based similarity metrics were incorporated into the registration algorithm to account for different imaging modalities. We demonstrate and evaluate our method on a diverse set of data that includes a synthetic volume, ex vivo and in vivo magnetic resonance imaging, and in vivo ultrasound.

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. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.

In MR elastography (MRE), periodic tissue motion is phase encoded using motion‐encoding gradients synchronized to an externally applied periodic mechanical excitation. Conventional methods result in extended scan time for quality phase images, thus limiting the broad application of MRE in the clinic. For practical scan times, researchers have been relying on one‐dimensional or two‐dimensional motion‐encoding, low‐phase sampling and a limited number of slices, and artifact‐prone, single‐shot, echo planar imaging (EPI) readout. Here, we introduce a rapid multislice pulse sequence capable of three‐dimensional motion encoding that is also suitable for simultaneously encoding motion with multiple frequency components. This sequence is based on a gradient‐recalled echo (GRE) sequence and exploits the principles of fractional encoding. This GRE MRE pulse sequence was validated as capable of acquiring full three‐dimensional motion encoding of isotropic voxels in a large volume within less than a minute. This sequence is suitable for monofrequency and multifrequency MRE experiments. In homogeneous paraffin phantoms, the eXpresso sequence yielded similar storage modulus values as those obtained with conventional methods, although with markedly reduced variances (7.11 ± 0.26 kPa for GRE MRE versus 7.16 ± 1.33 kPa for the conventional spin‐echo EPI sequence). The GRE MRE sequence obtained better phase‐to‐noise ratios than the equivalent spin‐echo EPI sequence (matched for identical acquisition time) in both paraffin phantoms and in vivo data in the liver (59.62 ± 11.89 versus 27.86 ± 3.81, 61.49 ± 14.16 versus 24.78 ± 2.48 and 58.23 ± 10.39 versus 23.48 ± 2.91 in the X, Y and Z components, respectively, in the case of liver experiments). Phase‐to‐noise ratios were similar between GRE MRE used in monofrequency or multifrequency experiments (75.39 ± 14.93 versus 86.13 ± 18.25 at 28 Hz, 71.52 ± 24.74 versus 86.96 ± 30.53 at 56 Hz and 95.60 ± 36.96 versus 61.35 ± 26.25 at 84Hz, respectively). Copyright © 2013 John Wiley & Sons, Ltd.

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.

In elasticity imaging, the shear modulus is obtained from measured tissue displacement data by solving an inverse problem based on the wave equation describing the tissue motion. In most inversion approaches, the wave equation is simplified using local homogeneity and incompressibility assumptions. This causes a loss of accuracy and therefore imaging artifacts in the resulting elasticity images. In this paper we present a new curl-based finite element method inversion technique that does not rely upon these simplifying assumptions. As done in previous research, we use the curl operator to eliminate the dilatational term in the wave equation, but we do not make the assumption of local homogeneity. We evaluate our approach using simulation data from a virtual tissue phantom assuming time harmonic motion and linear, isotropic, elastic behavior of the tissue. We show that our reconstruction results are superior to those obtained using previous curl-based methods with homogeneity assumption. We also show that with our approach, in the 2-D case, multi-frequency measurements provide better results than single-frequency measurements. Experimental results from magnetic resonance elastography of a CIRS elastography phantom confirm our simulation results and further demonstrate, in a quantitative and repeatable manner, that our method is accurate and robust.

Purpose Magnetic Resonance Elastography (MRE) is a method to probe the mechanical properties of tissue and has been shown to be capable of diagnosing cancerous tissue [1]. In this work, dynamic 7T MRE was performed on ex vivo prostate specimens. Multiple frequency excitation was use to determine whether the frequency dependence of the mechanical properties of tissue can be used to improve the accuracy of cancer detection. The results are compared to whole-mount histopathology. Previously, MRE was performed on prostate cancer specimens using quasi-static methods at 7T [2] and dynamic single tone excitation (350Hz) at 1.5T [3].

We consider the inverse problem of continuum mechanics with the tissue deformation described by a mixed displacement–pressure finite element formulation. The mixed formulation is used to model nearly incompressible materials by simultaneously solving for both elasticity and pressure distributions. To improve numerical conditioning, a common solution to this problem is to use regularization to constrain the solutions of the inverse problem. We present a sparsity regularization technique that uses the discrete cosine transform to transform the elasticity and pressure fields to a sparse domain in which a smaller number of unknowns is required to represent the original field. We evaluate the approach by solving the dynamic elastography problem for synthetic data using such a mixed finite element technique, assuming time harmonic motion, and linear, isotropic and elastic behavior for the tissue. We compare our simulation results to those obtained using the more common Tikhonov regularization. We show that the sparsity regularization is less dependent on boundary conditions, less influenced by noise, requires no parameter tuning and is computationally faster. The algorithm has been tested on magnetic resonance elastography data captured from a CIRS elastography phantom with similar results as the simulation.

PRELIMINARY RESULTS Ramin Sahebjavaher, Philippe Garteiser, Ralph Sinkus, Louis O. Gagnon, Ali Baghani, Silvia Chang, Simon Chatelin, Edward C. Jones, Chris Nguan, Larry Goldenberg, Piortr Kozlowski, Mehdi Moradi, and Septimiu Salcudean Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, Hôpital Beaujon, Centre de Recherche Biomédicale Bichat Beaujon (CRB3), Paris, France, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada, Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada, The Prostate Centre, Vancouver General Hospital, Vancouver, British Columbia, Canada, Department of Radiology, Harvard Medical School, Cambridge, MA, United States

In this article an ultrasound elastography technology is reported which provides quantitative images of tissue elasticity from deep soft tissue. The technique is analogous to Magnetic Resonance Elastography in the use of external mechanical vibrations which can penetrate deep tissue. Multifrequency steady-state mechanical vibrations are applied to the tissue at the skin and tissue displacements are measured by a conventional ultrasound system. Absolute values of tissue elasticity are computed in real-time for each frequency and displayed to the physician. The quantitative elasticity images produced by the technology are validated with magnetic resonance elastography images as the gold standard on standard elasticity phantoms. Preliminary in-vivo data from healthy volunteers are presented which show the potential of the technology for clinical use. The system is currently being used in different clinical studies to image kidney fibrosis, liver fibrosis, and prostate cancer.

Biomechanical models of the prostate have a number of potential applications in the diagnosis and management of prostate cancer. Most importantly, it has been shown in several studies that cancerous prostate tissue has different viscoelastic properties than normal prostate tissue: it is typically stiffer (higher storage modulus) and more viscous (higher loss modulus). If a strong correlation can be obtained between malignant tissue and its viscoelastic properties, then all commonly practiced prostate cancer procedures—biopsies, surgery and radiation treatment—can be improved by elasticity imaging. The elastic properties of the prostate and peri-prostatic tissue can also be used in procedure planning, even if such elastic properties do not show strong correlation to cancer. This chapter starts with an introduction to the prostate anatomy, prostate cancer, and a description of the most common procedures and their clinical needs. It continues by presenting the potential impact of elasticity imaging on these procedures. A brief survey of elastography techniques is presented next, with a sampling of some prostate elastography results to date. We describe two of the systems that we developed for the acquisition of prostate ultrasound and magnetic resonance elastography images and summarize our results to date. We show that these elasticity images can be used for prostate segmentation and cross-modality image registration. Furthermore, we show how prostate region deformation models can be used in the development of a prostate brachytherapy simulator which can also be used in the planning of needle insertions that account for deformation.

Introduction Tissue motion can be phase-encoded using motion sensitizing gradients (MSG) synchronized to an externally applied excitation. Conventional methods result in extended scan time for quality phase images. For practical scan times, many researchers have thus been relying on 1D or 2D motionencoding in limited number of slices. Here, we introduce a rapid multi-slice pulse sequence capable of 3D motion-encoding that is also suitable for encoding motion with multiple frequency components. Methods Bipolar trapezoidal MSGs were superimposed on a steady-state FFE pulse sequence. The duration of each shot was adjusted such that an integer multiple of shots fit within a vibration cycle T0. Thus, the duration of the MSG was only a fraction of the period of vibration (T0). For the acquisition, one k-line per slice was acquired, thereby maximizing the TR. After a dwell time, the same k-line was acquired for the next vibration phase (Figure 1). This was repeated to build up the k-space. In-vivo liver experiments were carried out at the inphase TE of 6.8ms and a TR of (4+1/8)·T0 = 147ms. The number of slices (eight) was at a multiple of shots per T0. Eight vibration phases were used to encode excitation at 28, 56 and 84hz. A reference scan was used to compensate for the electromagnetic transducer. An 802 matrix, 4mm3 isotropic voxels, reduced FOV and SENSE factor 2 was used. The entire acquisition of 59s was divided in four 15s breathholds. Results The magnitude images (on healthy liver) of the conventional SE-EPI motion-encoded sequence and the 3D steady-state FFE are shown in Figure 2. The magnitude images are dramatically improved in terms of artifacts and signal dropouts with the SS-FFE sequence. Results for the monoand multifrequency at 56hz are shown in Figure 3, where the waves are clearly visible and the shear moduli match (Table 1). This validates that the 3D SS-FFE sequence is well suited for multi-frequency MR rheology. Discussion and Conclusion A novel pulse sequence is introduced that strikes the balance between imaging speed, motionencoding efficiency and high quality phase images. This pulse sequence was experimentally validated as capable of acquiring full 3D motion-encoding in a volume in less than a minute, and as suitable for monoand multifrequency MR rheology experiments. References R. Muthupillai et al., Nat Med, vol. 2, May. 1996, p. 601-603. J. Rump et al., MRM, vol. 57, 2007, p. 388-395.

In this paper, a novel approach to the problem of elasticity reconstruction is introduced. In this approach, the solution of the wave equation is expanded as a sum of waves travelling in different directions sharing a common wave number. In particular, the solutions for the scalar and vector potentials which are related to the dilatational and shear components of the displacement respectively are expanded as sums of travelling waves. This solution is then used as a model and fitted to the measured displacements. The value of the shear wave number which yields the best fit is then used to find the elasticity at each spatial point. The main advantage of this method over direct inversion methods is that, instead of taking the derivatives of noisy measurement data, the derivatives are taken on the analytical model. This improves the results of the inversion. The dilatational and shear components of the displacement can also be computed as a byproduct of the method, without taking any derivatives. Experimental results show the effectiveness of this technique in magnetic resonance elastography. Comparisons are made with other state-of-the-art techniques.