3D prostate elastography: algorithm, simulations and experiments

A quantitative sonoelastography evaluation of ocular and periocular elasticity after intravitreal ranibizumab injection

PURPOSE

We evaluated changes in ocular and periocular elasticity by ultrasound (US) elastography in intravitreal ranibizumab-treated eyes and the healthy fellow eyes of patients with neovascular AMD.

METHODS

The study was performed on 52 eyes of 26 volunteers who ranged in age from 59 to 89 (mean 72±7.78) years old. The study group consisted of the patients with neovascular AMD treated with intravitreal ranibizumab. The fellow eyes (without choroidal neovascularization) of the study group were selected as the control group. All patients were examined with sonoelastography before intravitreal injection and at 1day, 1week, and 1month after intravitreal injection. All images were acquired with a Toshiba Aplio 500 ultrasound system (Tokyo, Japan) including software with a combined autocorrelation method and a multifrequency linear probe. The elastography values of the anterior vitreous (AV), posterior vitreous (PV), retina-choroid-sclera complex (RCS), retrobulbar fat tissue (RF), optic nerve head (ONH) and retrobulbar optic nerve (RON) were measured in each eye.

RESULTS

There were 13 male (50%) and 13 female (50%) participants in our study. Anterior vitreous, posterior vitreous, RCS, retrobulbar fat tissue, ONH, and RON US elastography values were similar in both groups (P˃0.05 for all). On the other hand, there was a positive correlation between the difference between baseline and 1-month PV sonoelastography values and age (r=0.47, P=0.035).

CONCLUSION

A single dose intravitreal Ranibizumab (Lucentis®, Genentech, USA) injection does not alter the elasticity of ocular and periocular structures.

Cavernous nerve mapping methods for radical prostatectomy

INTRODUCTION

Preserving the cavernous nerves, the main autonomic nerve supply of the penis, is a major challenge of radical prostatectomy. Cavernous nerve injury during radical prostatectomy predominantly accounts for post-radical prostatectomy erectile dysfunction. The cavernous nerve is a bilateral structure that branches in a weblike distribution over the prostate surface and varies anatomically in individuals, such that standard nerve-sparing methods do not sufficiently sustain penile erection ability. As a consequence, researchers have focused on developing personalized cavernous nerve mapping methods applied to the surgical procedure aiming to improve postoperative sexual function outcomes.

OBJECTIVES

We provide an updated overview of preclinical and clinical data of cavernous nerve mapping methods, emphasizing their strengths, limitations, and future directions.

METHODS

A literature review was performed via Scopus, PubMed, and Google Scholar for studies that describe cavernous nerve mapping/localization.

RESULTS

Several cavernous nerve mapping methods have been investigated based on various properties of the nerve structures including stimulation techniques, spectroscopy/imaging techniques, and assorted combinations of these methods. More recent methods have portrayed the course of the main cavernous nerve as well as its branches based on real-time mapping, high-resolution imaging, and functional imaging. However, each of these methods has distinctive limitations, including low spatial accuracy, lack of standardization for stimulation and response measurement, superficial imaging depth, toxicity risk, and lack of suitability for intraoperative use.

CONCLUSION

While various cavernous nerve mapping methods have provided improvements in identification and preservation of the cavernous nerve during radical prostatectomy, no method has been implemented in clinical practice due to their distinctive limitations. To overcome the limitations of existing cavernous nerve mapping methods, the development of new imaging techniques and mapping methods is in progress. There is a need for further research in this area to improve sexual function outcomes and quality of life after radical prostatectomy.

Accelerating 3-D GPU-based Motion Tracking for Ultrasound Strain Elastography Using Sum-Tables: Analysis and Initial Results

Now, with the availability of 3-D ultrasound data, a lot of research efforts are being devoted to developing 3-D ultrasound strain elastography (USE) systems. Because 3-D motion tracking, a core component in any 3-D USE system, is computationally intensive, a lot of efforts are under way to accelerate 3-D motion tracking. In the literature, the concept of Sum-Table has been used in a serial computing environment to reduce the burden of computing signal correlation, which is the single most computationally intensive component in 3-D motion tracking. In this study, parallel programming using graphics processing units (GPU) is used in conjunction with the concept of Sum-Table to improve the computational efficiency of 3-D motion tracking. To our knowledge, sum-tables have not been used in a GPU environment for 3-D motion tracking. Our main objective here is to investigate the feasibility of using sum-table-based normalized correlation coefficient (ST-NCC) method for the above-mentioned GPU-accelerated 3-D USE. More specifically, two different implementations of ST-NCC methods proposed by Lewis et al. and Luo-Konofagou are compared against each other. During the performance comparison, the conventional method for calculating the normalized correlation coefficient (NCC) was used as the baseline. All three methods were implemented using compute unified device architecture (CUDA; Version 9.0, Nvidia Inc., CA, USA) and tested on a professional GeForce GTX TITAN X card (Nvidia Inc., CA, USA). Using 3-D ultrasound data acquired during a tissue-mimicking phantom experiment, both displacement tracking accuracy and computational efficiency were evaluated for the above-mentioned three different methods. Based on data investigated, we found that under the GPU platform, Lou-Konofaguo method can still improve the computational efficiency (17–46%), as compared to the classic NCC method implemented into the same GPU platform. However, the Lewis method does not improve the computational efficiency in some configuration or improves the computational efficiency at a lower rate (7–23%) under the GPU parallel computing environment. Comparable displacement tracking accuracy was obtained by both methods.

Electromagnetic tracking-based freehand 3D quasi-static elastography with 1D linear array: a phantom study

Recent developments in hardware and scanning protocols have advanced conventional 2D quasi-static elastography to 3D level, which provides an intuitive visualization of lesions. A 2D linear array or scanning mechanism is typically required for 3D quasi-static elastography, requiring expensive and specifically designed hardware. In this study, we propose a novel method based on a commercial electromagnetic tracking system for freehand 3D quasi-static elastography with 1D linear array. Phantom experiments are performed to validate the feasibility of the proposed method. During data acquisition, the probe contacts the surface of an elasticity phantom and moves in the elevational direction, while applying sinusoidal-like axial compression to the phantom. For each frame of ultrasound data, the 3D coordinates and orientations of the probe are obtained from an electromagnetic tracking system. A correlation-based algorithm is adopted to obtain a series of axial strain images. Volumetric strain data are reconstructed by using the recorded 3D coordinates and orientations of the probe corresponding to each strain image. The diameters of inclusions are then obtained from the slice plots of the volumetric strain data. The volumes of inclusions are estimated from the isosurface plots. The experimental result shows that the volume estimation of the inclusions has good accuracy, with errors within 2%, while the diameters of the inclusions estimated from three orthogonal planes have larger errors up to 18%. In conclusion, the present framework would promise a reliable and effective solution for freehand 3D quasi-static elastography with 1D linear array.

A novel 3D printed mechanical actuator using centrifugal force for magnetic resonance elastography: Initial results in an anthropomorphic prostate phantom

This work demonstrates a new method for the generation of mechanical shear wave during magnetic resonance elastography (MRE) that creates greater forces at higher vibrational frequencies as opposed to conventionally used pneumatic transducers. We developed an MR-compatible pneumatic turbine with an eccentric mass that creates a sinusoidal centrifugal force. The turbine was assessed with respect to its technical parameters and evaluated for MRE on a custom-made anthropomorphic prostate phantom. The silicone-based tissue-mimicking materials of the phantom were selected with regard to their complex shear moduli examined by rheometric testing. The tissue-mimicking materials closely matched human soft tissue elasticity values with a complex shear modulus ranging from 3.21 kPa to 7.29 kPa. We acquired MRE images on this phantom at 3 T with actuation frequencies of 50, 60 Hz, 70 Hz, and 80 Hz. The turbine generated vibrational wave amplitudes sufficiently large to entirely penetrate the phantoms during the feasibility study. Increased wave length in the stiffer inclusions compared to softer background material were detected. Our initial results suggest that silicone-based phantoms are useful for the evaluation of elasticities during MRE. Furthermore, our turbine seems suitable for the mechanical assessment of soft tissue during MRE.

A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography

Our primary objective of this paper was to extend a previously published 2-D coupled subsample tracking algorithm for 3-D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3-D coupled subsample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking phantom and in vivo breast ultrasound data. The performance of this 3-D subsample tracking algorithm was compared with the conventional 3-D quadratic subsample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3-D subsample estimation algorithm can provide high-quality strain data (i.e., high correlation between the predeformation and the motion-compensated postdeformation radio frequency echo data and high contrast-to-noise ratio strain images), as compared with the conventional 3-D quadratic subsample algorithm. Using the GPU implementation of the 3-D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 s per volume [2.5 cm ×2.5 cm ×2.5 cm]).

Novel methods for mapping the cavernous nerves during radical prostatectomy

The cavernous nerves, which course along the surface of the prostate gland, are responsible for erectile function. During radical prostatectomy, urologists are challenged in preserving these nerves and their function. Cavernous nerves are microscopic and show variable location in different patients; therefore, postoperative sexual potency rates are widely variable following radical prostatectomy. A variety of technologies, including electrical and optical nerve stimulation, dye-based optical fluorescence and microscopy, spectroscopy, ultrasound and magnetic resonance imaging have all been used to study cavernous nerve anatomy and physiology, and some of these methods are also potential intraoperative methods for identifying and preserving cavernous nerves. However, all of these technologies have inherent limitations, including slow or inconsistent nerve responses, poor image resolution, shallow image depth, slow image acquisition times and/or safety concerns. New and emerging technologies, as well as multimodal approaches combining existing methods, hold promise for improved postoperative sexual outcomes and patient quality of life following radical prostatectomy.

Three-dimensional sheaf of ultrasound planes reconstruction (SOUPR) of ablated volumes

This paper presents an algorithm for 3-D reconstruction of tumor ablations using ultrasound shear wave imaging with electrode vibration elastography. Radio-frequency ultrasound data frames are acquired over imaging planes that form a subset of a sheaf of planes sharing a common axis of intersection. Shear wave velocity is estimated separately on each imaging plane using a piecewise linear function fitting technique with a fast optimization routine. An interpolation algorithm then computes velocity maps on a fine grid over a set of C-planes that are perpendicular to the axis of the sheaf. A full 3-D rendering of the ablation can then be created from this stack of C-planes; hence the name "Sheaf Of Ultrasound Planes Reconstruction" or SOUPR. The algorithm is evaluated through numerical simulations and also using data acquired from a tissue mimicking phantom. Reconstruction quality is gauged using contrast and contrast-to-noise ratio measurements and changes in quality from using increasing number of planes in the sheaf are quantified. The highest contrast of 5 dB is seen between the stiffest and softest regions of the phantom. Under certain idealizing assumptions on the true shape of the ablation, good reconstruction quality while maintaining fast processing rate can be obtained with as few as six imaging planes suggesting that the method is suited for parsimonious data acquisitions with very few sparsely chosen imaging planes.

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

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

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

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

Methods for robust in vivo strain estimation in the carotid artery

A hierarchical block-matching motion tracking algorithm for strain imaging is presented. Displacements are estimated with improved robustness and precision by utilizing a Bayesian regularization algorithm and an unbiased subsample interpolation technique. A modified least-squares strain estimator is proposed to estimate strain images from a noisy displacement input while addressing the motion discontinuity at the wall-lumen boundary. Methods to track deformation over the cardiac cycle incorporate a dynamic frame skip criterion to process data frames with sufficient deformation to produce high signal-to-noise displacement and strain images. Algorithms to accumulate displacement and/or strain on particles in a region of interest over the cardiac cycle are described. New methods to visualize and characterize the deformation measured with the full 2D strain tensor are presented. Initial results from patients imaged prior to carotid endarterectomy suggest that strain imaging detects conditions that are traditionally considered high risk including soft plaque composition, unstable morphology, abnormal hemodynamics and shear of plaque against tethering tissue can be exacerbated by neoangiogenesis. For example, a maximum absolute principal strain exceeding 0.2 is observed near calcified regions adjacent to turbulent flow, protrusion of the plaque into the arterial lumen and regions of low echogenicity associated with soft plaques. Non-invasive carotid strain imaging is therefore a potentially useful tool for detecting unstable carotid plaque.

The singular value filter: a general filter design strategy for PCA-based signal separation in medical ultrasound imaging

A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, which we refer to as the blind source separation (BSS) method, as well as a simple frequency-based finite impulse response (FIR) filter used as a baseline for comparison. The performance of each filter was quantified in simulated lesion images as well as experimental cardiac ultrasound data. SVF was demonstrated in both simulation and experimental results, over a wide range of imaging conditions, to outperform the BSS and FIR filtering methods in terms of contrast-to-noise ratio (CNR) and motion tracking performance. In experimental mouse heart data, SVF provided excellent artifact suppression with an average CNR improvement of 1.8 dB with over 40% reduction in displacement tracking error. It was further demonstrated from simulation and experimental results that SVF provided superior clutter rejection, as reflected in larger CNR values, when filtering was achieved using complex pulse-echo received data and non-binary filter coefficients.

Advances in finite element simulations of elastosonography for breast lesion detection

Among the available tools for the early diagnosis of breast cancer, the elastographic technique based on ultrasounds has many advantages such as the noninvasive measure, the absence of ionizing effects, the high tolerability by patients, and the wide diffusion of the ecographic machines. However this diagnostic procedure is strongly affected by many subjective factors and is considered not reliable enough even to reduce the number of biopsies used to identify the nature of lesions. Therefore in the literature experimental and numerical simulations on physical and virtual phantoms are presented to test and validate procedures and algorithms and to interpret elastosonographic results. In this work, first a description of the elastographic technique and a review of the principal finite element (FE) models are provided and second diagnostic indexes employed to assess the nature of a lump mass are presented. As advances in FE simulations of elastosonography, axisymmetric phantom, and anthropomorphic models are described, which, with respect to the literature, include some features of breast mechanics. In particular deterministic analyses were used to compare the various details of virtual elastograms and also to investigate diagnostic indexes with respect to the regions where strains were considered. In order to improve the reliability of the elastosonographic procedure, univariate and multivariate sensitivity analyses, based on a probabilistic FE approach, were also performed to identify the parameters that mostly influence the deformation contrast between healthy and cancerous tissues. Moreover, synthetic indicators of the strain field, such as the strain contrast coefficient, were evaluated in different regions of interest in order to identify the most suitable for lesion type assessment. The deterministic analyses show that the malignant lesion is characterized by a uniform strain inside the inclusion due to the firmly bonding condition, while in the benign inclusion (loosely bonded) a strain gradient is observed independently from the elastic modulus contrast. The multivariate analyses reveal that the strain contrast depends linearly on the relative stiffness between the lesion and the healthy tissue and not linearly on the interface friction coefficient. The anthropomorphic model shows other interesting features, such as the layer or curvature effects, which introduce difficulties in selecting a reference region for strain assessment. The results show that a simple axisymmetric model with linear elastic material properties can be suitable to simulate the elastosonographic procedure although the breast curvature and layer distinction play a significant role in the strain assessment.

Three-dimensional cardiac strain imaging in healthy children using RF-data

In this study, a new radio-frequency (RF)-based, three-dimensional (3-D) strain imaging technique is introduced and applied to 3-D full volume ultrasound data of the heart of healthy children. Continuing advances in performance of transducers for 3-D ultrasound imaging have boosted research on 3-D strain imaging. In general, speckle tracking techniques are used for strain imaging. RF-based strain imaging has the potential to yield better performance than speckle- based methods because of the availability of phase information but such a system output is commercially not available. Furthermore, the relatively low frame rate of 3-D ultrasound data has limited broad application of RF-based cardiac strain imaging. In this study, the previously reported two-dimensional (2-D) strain methodology was extended to the third dimension. Three-dimensional RF-data were acquired in 13 healthy children, in the age range of 6-15 years, at a relatively low frame rate of 38-51 Hz. A 3-D, free-shape, coarse-to-fine displacement and strain estimation algorithm was applied to the RF-data. The heart was segmented using 3-D ellipsoid fitting. Strain was estimated in the radial (R), circumferential (C) and longitudinal directions (L). Our preliminary results reveal the applicability of the 3-D strain estimation technique on full volume 3-D RF-data. The technique enabled 3-D strain imaging of all three strain components. The average strains for all children were in the lateral wall R = 37 ± 10% (infero-lateral) and R = 32% ± 10% (antero-lateral), C = -9% ± 4% (antero-lateral) and C = -9% ± 4% (infero-lateral), L = -18% ± 6 % (antero-lateral) and L = -15% ± 4% (infero-lateral). In the septum, strains were found to be R = 24% ± 10% (antero-septal) and R = 13% ± 5% (infero-septal), C = -13% ± 5% (antero-septal) and -13% ± 5% (infero-septal) and L = -13% ± 3% (antero-septal) and L = -16% ± 5% (infero-septal). Strain in the anterior and inferior walls seemed underestimated, probably caused by the low (in-plane) resolution and poor image quality. The field-of-view as well as image quality were not always sufficient to image the entire left ventricle. It is concluded that 3-D strain imaging using RF-data is feasible, but validation with other modalities and with conventional 3-D speckle tracking techniques will be necessary.

Real-time quasi-static ultrasound elastography

Ultrasound elastography is a technique used for clinical imaging of tissue stiffness with a conventional ultrasound machine. It was first proposed two decades ago, but active research continues in this area to the present day. Numerous clinical applications have been investigated, mostly related to cancer imaging, and though these have yet to prove conclusive, the technique has seen increasing commercial and clinical interest. This paper presents a review of the most widely adopted, non-quantitative, techniques focusing on technical innovations rather than clinical applications. The review is not intended to be exhaustive, concentrating instead on placing the various techniques in context according to the authors' perspective of the field.

Complex principal components for robust motion estimation

Bias and variance errors in motion estimation result from electronic noise, decorrelation, aliasing, and inherent algorithm limitations. Unlike most error sources, decorrelation is coherent over time and has the same power spectrum as the signal. Thus, reducing decorrelation is impossible through frequency domain filtering or simple averaging and must be achieved through other methods. In this paper, we present a novel motion estimator, termed the principal component displacement estimator (PCDE), which takes advantage of the signal separation capabilities of principal component analysis (PCA) to reject decorrelation and noise. Furthermore, PCDE only requires the computation of a single principal component, enabling computational speed that is on the same order of magnitude or faster than the commonly used Loupas algorithm. Unlike prior PCA strategies, PCDE uses complex data to generate motion estimates using only a single principal component. The use of complex echo data is critical because it allows for separation of signal components based on motion, which is revealed through phase changes of the complex principal components. PCDE operates on the assumption that the signal component of interest is also the most energetic component in an ensemble of echo data. This assumption holds in most clinical ultrasound environments. However, in environments where electronic noise SNR is less than 0 dB or in blood flow data for which the wall signal dominates the signal from blood flow, the calculation of more than one PC is required to obtain the signal of interest. We simulated synthetic ultrasound data to assess the performance of PCDE over a wide range of imaging conditions and in the presence of decorrelation and additive noise. Under typical ultrasonic elasticity imaging conditions (0.98 signal correlation, 25 dB SNR, 1 sample shift), PCDE decreased estimation bias by more than 10% and standard deviation by more than 30% compared with the Loupas method and normalized cross-correlation with cosine fitting (NC CF). More modest gains were observed relative to spline-based time delay estimation (sTDE). PCDE was also tested on experimental elastography data. Compressions of approximately 1.5% were applied to a CIRS elastography phantom with embedded 10.4-mm-diameter lesions that had moduli contrasts of -9.2, -5.9, and 12.0 dB. The standard deviation of displacement estimates was reduced by at least 67% in homogeneous regions at 35 to 40 mm in depth with respect to estimates produced by Loupas, NC CF, and sTDE. Greater improvements in CNR and displacement standard deviation were observed at larger depths where speckle decorrelation and other noise sources were more significant.

Real-time ultrasound elastographic imaging of ocular and periocular tissues: a feasibility study

BACKGROUND AND OBJECTIVE

This study examines the value of ultrasound elastography for the examination of ocular and periocular structures.

SUBJECTS AND METHODS

Five patients, aged 22 to 75 years, who each had one blind eye were included. Patients underwent ultrasound elastography of their blind eye and periocular tissues using a 7-13 MHz probe. Strain grayscale and color-coded elastographic maps were recorded. In the former, a quantitative assessment of signal intensity (corresponding to elastic properties) for specific anatomical structures was performed.

RESULTS

Anterior vitreous displayed intermediate elasticity, whereas posterior vitreous displayed low elasticity. Medial and lateral rectus muscle elasticity was higher in primary position than in adduction or abduction.

CONCLUSION

The pattern of elastic imaging in the vitreous cavity could be attributed to posterior vitreous detachment, whereas that of medial and lateral rectus muscles may be related to the level of muscle fiber strain.

3-D ultrasonic strain imaging using freehand scanning and a mechanically-swept probe

This paper compares 2 approaches to 3-D ultrasonic axial strain imaging: a tracked ultrasound probe swept manually over a volume, and a mechanically-swept 3-D probe. We find that high-quality data are more easily obtained using the 3-D probe, but the freehand approach may be more practical in certain scanning situations.

Multilevel hybrid 2D strain imaging algorithm for ultrasound sector/phased arrays

Two-dimensional (2D) cross-correlation algorithms are necessary to estimate local displacement vector information for strain imaging. However, most of the current two-dimensional cross-correlation algorithms were developed for linear array transducers. Although sector and phased array transducers are routinely used for clinical imaging of abdominal and cardiac applications, strain imaging for these applications has been performed using one-dimensional (1D) cross-correlation analysis. However, one-dimensional cross-correlation algorithms are unable to provide accurate and precise strain estimation along all the angular insonification directions which can range from -45 degrees to 45 degrees with sector and phased array transducers. In addition, since sector and phased array based images have larger separations between beam lines as the pulse propagates deeper into tissue, signal decorrelation artifacts with deformation or tissue motion are more pronounced. In this article, the authors propose a multilevel two-dimensional hybrid algorithm for ultrasound sector and phased array data that demonstrate improved tracking and estimation performance when compared to the traditional 1D cross-correlation or 2D cross-correlation based methods. Experimental results demonstrate that the signal-to-noise and contrast-to-noise ratio estimates improve significantly for smaller window lengths for the hybrid method when compared to the currently used one-dimensional or two-dimensional cross-correlation algorithms. Strain imaging results on ex vivo thermal lesions created in liver tissue and in vivo on cardiac short-axis views demonstrate the improved image quality obtained with this method.

Quasi-Static Ultrasound Elastography

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

The general properties including accuracy and resolution of linear filtering methods for strain estimation

The vast majority of strain imaging systems applies linear filtering to estimate strain from displacement data. Methods such as piecewise-linear least squares regression and staggered strain estimation have come to be widely known and applied, but the properties of these estimators have rarely (or never) been compared quantitatively. Given their tractable properties, careful analysis of linear filters allows us to make numerous observations that are simple, yet valuable. We consider accuracy and resolving power, which raises the question of whether any particular filter offers the best possible accuracy at a given resolution. Our surprising results provide insight at two levels: They highlight general considerations affecting the type of filter that is appropriate for practical applications, and indicate promising avenues for further research.

Correlation analysis of three-dimensional strain imaging using ultrasound two-dimensional array transducers

Two-dimensional (2D) transducer arrays represent a promising solution for implementing real time three-dimensional (3D) ultrasound elastography. 2D arrays enable electronic steering and focusing of ultrasound beams throughout a 3D volume along with improved slice thickness performance when compared to one-dimensional (1D) transducer arrays. Therefore, signal decorrelation caused by tissue motion in the elevational (out-of-plane) direction needs to be considered. In this paper, a closed form expression is derived for the correlation coefficient between pre- and postdeformation ultrasonic radio frequency signals. Signal decorrelation due to 3D motion of scatterers within the ultrasonic beam has been considered. Computer simulations are performed to corroborate the theoretical results. Strain images of a spherical inclusion phantom generated using 1D and 2D array transducers are obtained using a frequency domain simulation model. Quantitative image quality parameters, such as the signal-to-noise and contrast-to-noise ratios obtained using 1D, 2D, and 3D motion tracking algorithms, are compared to evaluate the performance with the 3D strain imaging system. The effect of the aperture size for 2D arrays and other factors that affect signal decorrelation are also discussed.

Automatic active model initialization via Poisson inverse gradient

Active models have been widely used in image processing applications. A crucial stage that affects the ultimate active model performance is initialization. This paper proposes a novel automatic initialization approach for parametric active models in both 2-D and 3-D. The PIG initialization method exploits a novel technique that essentially estimates the external energy field from the external force field and determines the most likely initial segmentation. Examples and comparisons with two state-of-the- art automatic initialization methods are presented to illustrate the advantages of this innovation, including the ability to choose the number of active models deployed, rapid convergence, accommodation of broken edges, superior noise robustness, and segmentation accuracy.

On the differences between two-dimensional and three-dimensional simulations for assessing elastographic image quality: a simulation study

In this work, we introduced an elastographic simulation framework, which estimates upper bounds on elastographic image quality by accounting for three-dimensional (3D) tissue motion and the 3D nature of the ultrasound beam. For the boundary conditions and the range of applied strains considered in this study, it was observed that for applied strains smaller than 0.7%, fast two-dimensional (2D) simulations and 3D simulations predicted similar upper bounds on elastographic signal-to-noise (SNR(e)) and contrast-to-noise ratios (CNR(e)); however, for applied strains greater than 0.7%, the predictions by 2D simulations grossly overestimated the achievable results when compared with upper bound results from 3D simulations. It was also found that linear increments in the elevational-to-lateral beamwidth ratio (beam ratio) resulted in nonlinear degradation in the achievable upper bounds on elastographic signal-to-noise ratio. For the modulus contrast ratio of ten between the target and the background, the peak difference in the prediction of contrast-to-noise by 2D and 3D simulations was approximately 10 dB, whereas, for modulus contrast ratio of 1.5, the peak difference increased to approximately 30 dB. No significant difference was observed between the spatial resolution predicted by 2D and 3D simulations; however, increase in beam ratio resulted in decrease in target detectability, especially at lower modulus contrast ratios.