Direct phase-based strain estimator for ultrasound tissue elasticity imaging

Quantitative assessment of the cardiac tissue mechanical property or contractility is essential for the prognosis and treatment of various cardiac diseases such as myocardial infarction, pulmonary hypertension, and heart failure. Current evaluation methods are either invasive or limited, mainly due to complex 3-dimensional (3D) geometry and deformation of a heart. 2D imaging techniques assume erroneous planar geometry and deformations, while available 3D imaging techniques have limited functional assessment. Correlation-based 3D ultrasound (US) elasticity imaging (UEI) provides both anatomical and functional information such as mechanical property change of the cardiac walls, which is important for diagnosis and monitoring of the treatment. Using finite element (FE) techniques, one and two ellipsoid chamber cardiac mechanical models were developed, and combined with 3D US radio frequency (RF) data generation program. 3D UEI on the synthesized 3D US volume images were quantitatively analyzed and compared with 2D UEI.

Ultrasound (US) elasticity imaging is an extension of the ancient art of palpation and of earlier US methods for viewing tissue stiffness such as echopalpation. Elasticity images consist of either an image of strain in response to force or an image of estimated elastic modulus. There are 3 main types of US elasticity imaging: elastography that tracks tissue movement during compression to obtain an estimate of strain, sonoelastography that uses color Doppler to generate an image of tissue movement in response to external vibrations, and tracking of shear wave propagation through tissue to obtain the elastic modulus. Other modalities may be used for elasticity imaging, the most powerful being magnetic resonance elastography. With 4 commercial US scanners already offering elastography and more to follow, US-based methods may be the most widely used for the near future. Elasticity imaging is possible for nearly every tissue. Breast mass elastography has potential for enhancing the specificity of US and mammography for cancer detection. Lesions in the thyroid, prostate gland, pancreas, and lymph nodes have been successfully imaged using elastography. Evaluation of diffuse disease including cirrhosis and transplant rejection is also possible using both imaging and nonimaging methods. Vascular imaging including myocardium, blood vessel wall, plaque, and venous thrombi has also shown great potential. Elasticity imaging may also be important in assessing the progress of ablation therapy. Recent work in assessing porous materials using elastography suggests that the technique may be useful in monitoring the severity of lymphedema.

Intra-operative ultrasound elasticity imaging for monitoring of hepatic tumour thermal ablation

Ultrasound elasticity imaging is a promising method that may eventually allow early detection of many tissue pathologies. However, before elasticity imaging can be applied to its numerous potential clinical applications, the quantitative accuracy of tissue elasticity measurements must be established. Simple 1-D ultrasound elasticity measurements were performed on muscle and liver and compared with independent and established mechanical measurements to investigate both the accuracy and consistency of ultrasound elasticity measurements. In addition, some interesting properties of soft tissue and aspects of the measurement process which should be considered in elasticity measurements are discussed.

Existing physical model-based imaging methods for ultrasound elasticity reconstruction utilize fixed variational regularizers that may not be appropriate for the application of interest or may not capture complex spatial prior information about the underlying tissues. On the other hand, end-to-end learning-based methods count solely on the training data, not taking advantage of the governing physical laws of the imaging system. Integrating learning-based priors with physical forward models for ultrasound elasticity imaging, we present a joint reconstruction framework which guarantees that learning driven reconstructions are consistent with the underlying physics. For solving the elasticity inverse problem as a regularized optimization problem, we propose a plug-and-play (PnP) reconstruction approach in which each iteration of the elasticity image estimation process involves separate updates incorporating data fidelity and learning-based regularization. In this methodology, the data fidelity term is developed using a statistical linear algebraic model of quasi-static equilibrium equation revealing the relationship of the observed displacement fields to the unobserved elastic modulus. The regularizer comprises a convolutional neural network (CNN) based denoiser that captures the learned prior structure of the underlying tissues. Preliminary simulation results demonstrate the robustness and effectiveness of the proposed approach with limited training datasets and noisy displacement measurements.

In this study, a real-time compression based ultrasound elasticity imaging prototype was developed and evaluated for liver radio-frequency ablation (RFA) assessment under ex vivo and in vivo conditions. The prototype was implemented on a commercial ultrasound system (iU22, Philips Healthcare) for an L12-5 linear transducer and a C5-1 curvilinear transducer. Under the ex vivo condition, two bovine liver samples were used for L12-5 and C5-1 respectively. Under the in vivo condition, a pig was anesthetized and mechanically ventilated. Ultrasound elasticity imaging experiments were performed during breath-hold in order to reduce respiratory motion artifacts. Post-RFA strain images were compared against several imaging modalities including MRI, contrast-enhanced CT and gross pathology. For the ex vivo case, a Rita Starburst probe (AngioDynamics, Queensbury, NY) was used to perform RFA and induce tissue deformation for strain imaging. Real-time strain images were generated pre- and post-RFA. After the ablation, the liver was imaged by a Panorama 1-T MRI system (Philips Healthcare), then it was dissected along the approximate ultrasound imaging plane for lesion dimension measurement using a caliper. The post-RFA strain images depicted an ablation zone with increased stiffness that was well correlated with the physiological changes observed in the T1-weighted MR image and gross pathology. For the second ex vivo liver sample, the strain image revealed an ablation zone of 4.90 cm ? 2.85 cm, and the MR image and gross pathology showed a zone of 4.56 cm ? 3.24 cm and of 4.91 cm ? 3.65 cm, respectively. For the in vivo study, three different commercial RFA needles were employed: the Covidien (Mansfield, MA) CoolTip single prong and triple-cluster probes, and the Rita Starburst probe. The animal underwent contrast-enhanced CT imaging immediately after RFA. It was then sacrificed and the ablated liver lobes were dissected for ex vivo MRI. All three imaging modalities showed comparable measurement of lesion dimensions. The triple-cluster Covidien probe and the Rita probe with expanding tines seemed to perform better with elasticity assessment than the Covidien single prong probe. Preliminary results from this study demonstrate that real-time ultrasound strain imaging is potentially a valuable tool for assessing liver RFA. Further technical development of this prototype will advance toward real-time clinical use.

Non-invasively monitoring the mechanical property change of the engineered tissue constructs in vivo may help evaluate and feedback tissue scaffold design. In this paper, ultrasound elasticity imaging (UEI) was applied to detect mechanical property changes of the implanted polyurethane tissue constructs on a rat abdominal defect. Bi-axial mechanical measurements on the excised tissue/scaffold constructs were performed for comparison with the UEI results. An increase in overall stiffness along with tissue ingrowth was observed in 4 and 8weeks using both UEI and direct mechanical testing. While, pure scaffold embedded in 10% gelatin showed decrease in stiffness with degradation. Histopathology confirmed tissue ingrowth such as collagens.

Ultrasound elasticity imaging has been developed over the last decade to estimate tissue stiffness. Shear wave elasticity imaging (SWEI) quantifies tissue stiffness by measuring the speed of propagating shear waves following acoustic radiation force excitation. This work presents the sequencing and data processing protocols of SWEI using a Verasonics system. The selection of the sequence parameters in a Verasonics programming script is discussed in detail. The data processing pipeline to calculate group shear wave speed (SWS), including tissue motion estimation, data filtering, and SWS estimation is demonstrated. In addition, the procedures for calibration of beam position, scanner timing, and transducer face heating are provided to avoid SWS measurement bias and transducer damage.

Tissue engineers are greatly interested in non- invasively evaluating the extent of cell growth, scaffold degradation, and tissue development both in vitro and in vivo as a function of time. Current evaluation methods such as cell histology and direct mechanical measurements can only provide static snapshots using different specimens at different time points. These measurements introduce specimen to specimen and animal to animal variation. MRI and CT can monitor scaffold degradation and tissue growth in the same specimen over time, but provide only morphological information. Ultrasound Elasticity Imaging based on phase sensitive speckle tracking can characterize the internal structural and compositional change at a high resolution of a few hundreds of microns. In this study, ultrasound elasticity imaging was applied to poly (1, 8 octanediol-co-citrate) (POC) scaffold embedded in a gelatin phantom at different stages of chemically induced degradation and compared with direct mechanical measurements. Although ultrasound strain imaging measures the mechanical property change of the scaffold as degradation progresses, further investigation on absolute elastic modulus estimate is needed. Novel elastic modulus reconstruction algorithm was applied to the displacement estimates from speckle tracking. The reconstructed elastic modulus compared well with direct mechanical measurements.

Time domain finite difference simulations are used extensively to simulate wave propagation. They approximate the wave field on a discrete domain with a grid spacing that is typically on the order of a tenth of a wavelength. The smallest displacements that can be modeled by this type of simulation are thus limited to discrete values that are integer multiples of the grid spacing. This paper presents a method to represent continuous and subresolution displacements by varying the impedance of individual elements in a multielement scatterer. It is demonstrated that this method removes the limitations imposed by the discrete grid spacing by generating a continuum of displacements as measured by the backscattered signal. The method is first validated on an ideal perfect correlation case with a single scatterer. It is subsequently applied to a more complex case with a field of scatterers that model an acoustic radiation force-induced displacement used in ultrasound elasticity imaging. A custom finite difference simulation tool is used to simulate propagation from ultrasound imaging pulses in the scatterer field. These simulated transmit-receive events are then beamformed into images, which are tracked with a correlation-based algorithm to determine the displacement. A linear predictive model is developed to analytically describe the relationship between element impedance and backscattered phase shift. The error between model and simulation is λ/ 1364 , where λ is the acoustical wavelength. An iterative method is also presented that reduces the simulation error to λ/ 5556 over one iteration. The proposed technique therefore offers a computationally efficient method to model continuous subresolution displacements of a scattering medium in ultrasound imaging. This method has applications that include ultrasound elastography, blood flow, and motion tracking. This method also extends generally to finite difference simulations of wave propagation, such as electromagnetic or seismic waves.

To evaluate the efficacies of conventional ultrasound (US), US elasticity imaging (EI), and acoustic radiation force impulse (ARFI) elastography in breast malignancy diagnosis. We included 315 women (mean age, 44 years; range, 18-81 years) with 336 pathologically proven breast lesions in this retrospective study. All lesions underwent conventional US, EI, and ARFI (including virtual touch tissue imaging [VTI], virtual touch tissue quantification [VTQ], and virtual touch tissue imaging and quantification [VTIQ]) elastography. Multivariate logistic regression analysis was performed to assess 12 independent variables for malignancy prediction. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. Irregular lesion shape was the strongest independent predictor for breast malignancy, followed by poorly defined margins, taller than wide dimensions, posterior echo attention, VTIQ, and VTI boundaries (P < 0.05). Area under the ROC curve (AUC) for VTIQ was higher than other significant independent variables. With the best cut-off value of 3.74 m/s, the AUC, sensitivity, and specificity were 0.93 (95% CI: 0.90, 0.96), 90.1%, and 91.1%, respectively. ARFI elastography is a promising method in breast malignancy prediction, with good diagnostic performance. For patients requiring surgery, the combination of various methods can provide better diagnostic results and may help to reduce unnecessary biopsy or surgery.

To explore the effect of platelet-rich plasma (PRP) in treatment of Achilles tendinopathy in rabbits, and provide experimental evidence for the clinical application of PRP in treatment of Achilles tendinopathy. Forty-eight adult New Zealand white rabbits, weighing 2.5-3.0 kg, male or female, were randomly divided into model group (group A), model control group (group B), model+treatment control group (group C), model+treatment group (group D), with 12 in each group. The rabbits were injected with type Ⅰ collagenase to prepare Achilles tendinopathy models in groups A, C, and D, and with an equal dose of normal saline in group B. The blood from the central artery of rabbit ear was taken to preprare PRP by secondary centrifugation in group D. The results of platelet counts showed that PRP platelets reached 3 to 5 times the whole blood. After the model was prepared, the rabbits in groups C and D were injected with physiological saline and autologous PRP at the molding site respectively, once a week, 0.8 mL each time for 4 weeks. At 1 week after PRP injection, the relative hardness (expressed as HRD%) of Achilles tendon was evaluated by ultrasound elastic quantitative imaging detection technique; the maximum breaking load of Achilles tendon was measured by universal electronic tensile testing machine; the contents of collagen type Ⅰ and Ⅲ were determined by ELISA; and the morphology of Achilles tendon collagen fibers was observed by HE and Masson stainings. All animals survived during the experiment. The results of ultrasound elastic quantitative imaging and mechanical tests showed that the HRD% and the maximum breaking load were significantly lower in group A than in group B ( P<0.05) and in group C than in group D ( P<0.05). The results of ELISA showed that the content of collagen type Ⅰ was significantly lower in group A than in group B ( P<0.05) and in group C than in group D ( P<0.05); the content of collagen type Ⅲ was significantly higher in group A than in group B ( P<0.05) and in group D than in group C ( P<0.05). HE and Masson stainings showed that the Achilles tendon collagen fibers were irregularly curled and the structure was severely damaged in group A; the fibers were parallel and ordered, and the structure was complete in group B; the fibers were irregularly curled and structurally disordered in group C; the fibers were slightly curled and the structure was relatively complete in group D. A rabbit model of Achilles tendinopathy can be reconstructed by type Ⅰ collagenase injection. PRP treatment can increase the Achilles tendon hardness and maximum breaking load, up-regulate the expression level of collagen type Ⅰ and Ⅲ, improve the structure of Achilles tendon collagen fiber, and promote the repair in rabbit Achilles tendinopathy model.

The biomechanical properties of soft tissues vary with pathological phenomenon. Ultrasound elasticity imaging is a noninvasive method used to analyze the local biomechanical properties of soft tissues in clinical diagnosis. However, the echo signal-to-noise ratio (eSNR) is diminished because of the attenuation of ultrasonic energy by soft tissues. Therefore, to improve the quality of elastography, the eSNR and depth of ultrasound penetration must be increased using chirp-coded excitation. Moreover, the low axial resolution of ultrasound images generated by a chirp-coded pulse must be increased using an appropriate compression filter. The main aim of this study is to develop an ultrasound elasticity imaging system with chirp-coded excitation using a Tukey window for assessing the biomechanical properties of soft tissues. In this study, we propose an ultrasound elasticity imaging system equipped with a 7.5-MHz single-element transducer and polymethylpentene compression plate to measure strains in soft tissues. Soft tissue strains were analyzed using cross correlation (CC) and absolution difference (AD) algorithms. The optimal parameters of CC and AD algorithms used for the ultrasound elasticity imaging system with chirp-coded excitation were determined by measuring the elastographic signal-to-noise ratio (SNRe) of a homogeneous phantom. Moreover, chirp-coded excitation and short pulse excitation were used to measure the elasticity properties of the phantom. The elastographic qualities of the tissue-mimicking phantom were assessed in terms of Young’s modulus and elastographic contrast-to-noise ratio (CNRe). The results show that the developed ultrasound elasticity imaging system with chirp-coded excitation modulated by a Tukey window can acquire accurate, high-quality elastography images.

Ultrasound elasticity imaging (UEI) shows promise as a new way for early detection of cancers by assessing the elastic characteristics of soft tissue. So far the commonly used approach involves solving the so-called inverse elasticity problem of recovering elastic parameters from displacement measurements. We propose a finite-element based nonlinear scheme to estimate the elasticity distribution of soft tissue from multi-compressed ultrasound radio-frequency (RF) data. An assisted-freehand ultrasound workstation has been developed for elasticity imaging. A composite probe was employed as the compression plate. The contact forces and torques were acquired at the same time of imaging. Displacements under different static loads are estimated from the RF data before and after deformation using cross-correlation technique. The confidence of displacement estimates is employed as a weighting factor in solving the objective function describing the inverse elasticity reconstruction problem. A split-and-merge strategy is employed over the image sequence in which strain images are used to provide a priori knowledge of the relative stiffness distribution of the tissue to constrain the inverse problem solution. The experimental study has allowed us to investigate the performance of our approach in the controlled environment of simulated and phantom data. For a simulated single inclusion model with 5% noise level the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -error between the target and reconstructed Young's modulus is found to be about 1%. In vivo validation of the proposed method has been carried out and some preliminary results illustrate the practicability and the effectiveness of the method

Elasticity Imaging 101