Radio-frequency Frames Research Articles

Incorporating Gradient Similarity for Robust Time Delay Estimation in Ultrasound Elastography.

Energy-based ultrasound elastography techniques minimize a regularized cost function consisting of data and continuity terms to obtain local displacement estimates based on the local time-delay estimation (TDE) between radio frequency (RF) frames. The data term associated with the existing techniques takes only the amplitude similarity into account and hence is not sufficiently robust to the outlier samples present in the RF frames under consideration. This drawback creates noticeable artifacts in the strain image. To resolve this issue, we propose to formulate the data function as a linear combination of the amplitude and gradient similarity constraints. We estimate the adaptive weight concerning each similarity term following an iterative scheme. Finally, we optimize the nonlinear cost function in an efficient manner to convert the problem to a sparse system of linear equations which are solved for millions of variables. We call our technique rGLUE: robust data term in GLobal Ultrasound Elastography. rGLUE has been validated using simulation, phantom, in vivo liver, and breast datasets. In all our experiments, rGLUE substantially outperforms the recent elastography methods both visually and quantitatively. For simulated, phantom, and in vivo datasets, respectively, rGLUE achieves 107%, 18%, and 23% improvements of signal-to-noise ratio (SNR) and 61%, 19%, and 25% improvements of contrast-to-noise ratio (CNR) over global ultrasound elastography (GLUE), a recently published elastography algorithm.

Fast Strain Estimation and Frame Selection in Ultrasound Elastography Using Machine Learning.

Ultrasound elastography aims to determine the mechanical properties of the tissue by monitoring tissue deformation due to internal or external forces. Tissue deformations are estimated from ultrasound radio frequency (RF) signals and are often referred to as time delay estimation (TDE). Given two RF frames I1 and I2 , we can compute a displacement image, which shows the change in the position of each sample in I1 to a new position in I2 . Two important challenges in TDE include high computational complexity and the difficulty in choosing suitable RF frames. Selecting suitable frames is of high importance because many pairs of RF frames either do not have acceptable deformation for extracting informative strain images or are decorrelated and deformation cannot be reliably estimated. Herein, we introduce a method that learns 12 displacement modes in quasi-static elastography by performing principal component analysis (PCA) on displacement fields of a large training database. In the inference stage, we use dynamic programming (DP) to compute an initial displacement estimate of around 1% of the samples and then decompose this sparse displacement into a linear combination of the 12 displacement modes. Our method assumes that the displacement of the whole image could also be described by this linear combination of principal components. We then use the GLobal Ultrasound Elastography (GLUE) method to fine-tune the result yielding the exact displacement image. Our method, which we call PCA-GLUE, is more than 10× faster than DP in calculating the initial displacement map while giving the same result. This is due to converting the problem of estimating millions of variables in DP into a much simpler problem of only 12 unknown weights of the principal components. Our second contribution in this article is determining the suitability of the frame pair I1 and I2 for strain estimation, which we achieve by using the weight vector that we calculated for PCA-GLUE as an input to a multilayer perceptron (MLP) classifier. We validate PCA-GLUE using simulation, phantom, and in vivo data. Our classifier takes only 1.5 ms during the testing phase and has an F1-measure of more than 92% when tested on 1430 instances collected from both phantom and in vivo data sets.

Compressive sensing theory and neighborhood spatial‐temporal information for frame rate improvement of dynamic ultrasonic imaging

AbstractThe frame rate improvement is an essential issue in dynamic ultrasonic imaging for better displaying rapid heart movements. In this study, a new technique using the compressive sensing (CS) theory was introduced for the frame rate improvement of two‐dimensional (2D) and three‐dimensional (3D) dynamic ultrasonic imaging. In the suggested procedure, a fewer radio frequency (RF) lines were received. Subsequently, the CS theory by the recommended approach was used to reconstruct the nonacquired RF lines. The suggested process uses the temporal and spatial information in the neighborhood samples of the desired sample in RF frame sequences. We utilized the dictionary learning technique to construct the sparsifying over‐complete dictionary. Here, we used the 2D in vivo carotid artery data and the 3D simulated echocardiography for the quality assessment of the suggested approach. According to the qualitative and quantitative results, reconstructions in the suggested approach are more precise, and the reconstruction errors are much lower than the conventional techniques. The tissues' structure in reconstructed videos by the suggested approach is preserved to be applicable for medical diagnosis goals. The frame rate can be improved by a factor of 10 with suitable quality for medical diagnosis goals. The implementation of the suggested approach does not require any more hardware or alternation in the devices' available hardware. The frame rate can be improved by only implementing effective programming on the ultrasound systems.

Automatic Frame Selection using CNN in Ultrasound Elastography.

Ultrasound elastography is used to estimate the mechanical properties of the tissue by monitoring its response to an internal or external force. Different levels of deformation are obtained from different tissue types depending on their mechanical properties, where stiffer tissues deform less. Given two radio frequency (RF) frames collected before and after some deformation, we estimate displacement and strain images by comparing the RF frames. The quality of the strain image is dependent on the type of motion that occurs during deformation. In-plane axial motion results in high-quality strain images, whereas out-of-plane motion results in low-quality strain images. In this paper, we introduce a new method using a convolutional neural network (CNN) to determine the suitability of a pair of RF frames for elastography in only 5.4 ms. Our method could also be used to automatically choose the best pair of RF frames, yielding a high-quality strain image. The CNN was trained on 3,818 pairs of RF frames, while testing was done on 986 new unseen pairs, achieving an accuracy of more than 91%. The RF frames were collected from both phantom and in vivo data.

Global Tracking of Myocardial Motion in Ultrasound Sequence Images: A Feasibility Study.

The assessment of myocardial motion plays a promising role in the evaluation of cardiac function. This study aims to propose a novel framework of global estimation of the myocardial motion using radio-frequency (RF) data. The framework consists of B-mode image reconstruction, displacement estimation, myocardium extraction, and image fusion. The RF data of murine heart in parasternal long-axis (PLAX) view were collected for B-mode image reconstruction and displacement estimation. The vectorized normalized cross-correlation (VNCC) approach was proposed to globally estimate the displacements of the RF frames, while a sum-table based normalized cross-correlation (STNCC) was performed as reference algorithm. The bimodal fusion images were obtained to visualize the motion and anatomical structure of myocardium by an improved fast mapping algorithm (IFMA). In comparison with STNCC, the computation time of displacement using VNCC reduced by approximate 10s. The myocardial motions of anterior wall and posterior wall during one cardiac cycle were similarly tracked by VNCC as that of STNCC. The averaged absolute error in displacement between the two methods ranges from 1 to 3μm. The obtained myocardial elastographic images using VNCC intuitively present the morphological and mechanical changes during the contraction period of left ventricle. The results demonstrate that the proposed framework is an efficient tool for the estimation of myocardial motion reflecting cardiac systolic function. This approach has potentials to provide visualized information of myocardium for diagnosis and prognosis of cardiovascular diseases (CVDs).

Estimation of Strain Elastography from Ultrasound Radio-Frequency Data by Utilizing Analytic Gradient of the Similarity Metric

Most strain imaging techniques follow a pipeline strategy: in the first step, tissue displacement is estimated from radio-frequency (RF) frames, and in the second step, a spatial derivative operation is applied. There are two main issues that arise from this framework. First, the gradient operation amplifies noise, and therefore, smoothing techniques have to be adopted. Second, strain estimation does not exploit the original RF data. It rather relies solely on the noisy displacement field. In this paper, a novel technique is proposed that utilizes both the displacement field and the RF frames to accurately obtain the strain estimates. The normalized cross correlation (NCC) metric between two corresponding windows around the samples of the pre- and post-compressed images is employed to generate a dissimilarity measurement. The derivative of NCC with respect to the strain is analytically derived using the chain rule. This allows an efficient minimization of the dissimilarity metric with respect to the strain using the gradient descent optimization technique. The effectiveness of the proposed method is investigated through simulation data, phantom experiments, and in vivo patient data. The experimental results show that exploiting the information in RF data significantly improves the strain estimates.

Detection of tissue coagulation by decorrelation of ultrasonic echo signals in cavitation-enhanced high-intensity focused ultrasound treatment.

BackgroundA noninvasive technique to monitor thermal lesion formation is necessary to ensure the accuracy and safety of high-intensity focused ultrasound (HIFU) treatment. The purpose of this study is to ultrasonically detect the tissue change due to thermal coagulation in the HIFU treatment enhanced by cavitation microbubbles.MethodsAn ultrasound imaging probe transmitted plane waves at a center frequency of 4.5 MHz. Ultrasonic radio-frequency (RF) echo signals during HIFU exposure at a frequency of 1.2 MHz were acquired. Cross-correlation coefficients were calculated between in-phase and quadrature (IQ) data of two B-mode images with an interval time of 50 and 500 ms for the estimation of the region of cavitation and coagulation, respectively. Pathological examination of the coagulated tissue was also performed to compare with the corresponding ultrasonically detected coagulation region.ResultsThe distribution of minimum hold cross-correlation coefficient between two sets of IQ data with 50-ms intervals was compared with a pulse inversion (PI) image. The regions with low cross-correlation coefficients approximately corresponded to those with high brightness in the PI image. The regions with low cross-correlation coefficients in 500-ms intervals showed a good agreement with those with significant change in histology.ConclusionsThe results show that the regions of coagulation and cavitation could be ultrasonically detected as those with low cross-correlation coefficients between RF frames with certain intervals. This method will contribute to improve the safety and accuracy of the HIFU treatment enhanced by cavitation microbubbles.

Development of a Wireless and Near Real-Time 3D Ultrasound Strain Imaging System.

Ultrasound elastography is an important medical imaging tool for characterization of lesions. In this paper, we present a wireless and near real-time 3D ultrasound strain imaging system. It uses a 3D translating device to control a commercial linear ultrasound transducer to collect pre-compression and post-compression radio-frequency (RF) echo signal frames. The RF frames are wirelessly transferred to a high-performance server via a local area network (LAN). A dynamic programming strain estimation algorithm is implemented with the compute unified device architecture (CUDA) on the graphic processing unit (GPU) in the server to calculate the strain image after receiving a pre-compression RF frame and a post-compression RF frame at the same position. Each strain image is inserted into a strain volume which can be rendered in near real-time. We take full advantage of the translating device to precisely control the probe movement and compression. The GPU-based parallel computing techniques are designed to reduce the computation time. Phantom and in vivo experimental results demonstrate that our system can generate strain volumes with good quality and display an incrementally reconstructed volume image in near real-time.

Diagnosing Bladder Outlet Obstruction Using Non-invasive Decorrelation-Based Ultrasound Imaging: A Feasibility Study in Healthy Male Volunteers

A feasibility study on the applicability of an ultrasound decorrelation method to urinary flow imaging was carried out in 20 healthy male volunteers, to provide a basis for a non-invasive approach to diagnose bladder outlet obstruction. Each volunteer voided five times in a flow meter in standing position. During each voiding, ultrasound radiofrequency frames were acquired transperineally at different flow rates. The results indicated that the decrease in correlation (decorrelation) of ultrasound radiofrequency signals had no unique relation with flow rate, but decreased distinctively with urinary flow velocity. In most of the healthy volunteers, the decorrelation was small because of the low flow velocity. However, because of the different flow velocities in volunteers, the variation in slope between volunteers was statistically significant. Therefore, it is probably possible to use the decorrelation method to differentiate between healthy persons and patients with obstruction.

Differentiation of Breast Lesions by Use of HyperSPACE: Hyper-Spectral Analysis for Characterization in Echography

Early diagnosis represents the cornerstone in breast cancer control. Ultrasound is still a valid tool because of its low invasiveness, reduced costs and reduced risk of harm, but better exploitation of its potential is necessary to extract information on tissue features. The proposed method, HyperSPACE (hyper-spectral analysis for characterization in echography), which processes the ultrasonic radiofrequency signal in an N-dimension spectral hyperspace to define several characteristic parameters of the tissue under investigation, was used with the aim of differentiating two types of breast lesion: infiltrating ductal carcinoma and fibroadenoma. The analyzed data set consisted of 2000 radiofrequency frames related to 200 sections of pathologic breast nodules: 104 infiltrating ductal carcinomas and 96 fibroadenomas. The algorithm was trained on single radiofrequency frames related to 50 sections (26 carcinomas, 24 fibroadenomas) to recognize the two pathologies considered, and all the radiofrequency frames related to the other 150 sections were classified, yielding a sensitivity of 92.2%, specificity of 93%, positive predictive value of 93.2% and negative predictive value of 91%. The results were compared with those of RULES (radiofrequency ultrasonic local estimators), a processing method set developed by our group and used by other researchers in clinical and laboratory environments.

WE-E-134-11: Ultrasound Cardiac Strain Imaging of Left Ventricle Using Lagrangian Tracking

Purpose: Lagrangian description of myocardial tissue deformation is essential for accurate regional strain estimation of left ventricular wall over time. Failure to couple the estimated displacement and strain information with the correct myocardial tissue structure will lead to erroneous displacement and strain estimation. Methods: In this study, a method to obtain Lagrangian based deformation tracking is presented. Myocardial tissue is divided into a fixed number of pixels whose deformation is tracked over the cardiac cycle. An algorithm that utilizes a polar‐grid generated between the estimated endocardial and epicardial contours for the left ventricle in cardiac short axis images is proposed to ensure Lagrangian description. Displacement estimations from consecutive radiofrequency frames were then mapped onto the polar grid to obtain a distribution of the cumulated displacement that is mapped to the polar grid over time. Results: This method was validated against a finite element analysis (FEA) based canine heart model coupled to an ultrasound simulation program. Segmental analysis of the accumulated displacement and strain over cardiac cycles show excellent agreement between the ideal Results obtained directly from the FEA model and our Lagrangian approach for deformation mapping. Eulerian based estimation results on the other hand, show significant deviation from the ideal Results. A comparison of the displacement and strain estimated on parasternal short axis view on a healthy volunteer is also presented. Conclusion: Lagrangian deformation tracking using a polar grid demonstrates accurate results when validated against finite element cardiac model. In addition to the cardiac application, this approach can also be applied to transverse scans of arteries.

Linear and Nonlinear Elastic Modulus Imaging: An Application to Breast Cancer Diagnosis

We reconstruct the in vivo spatial distribution of linear and nonlinear elastic parameters in ten patients with benign (five) and malignant (five) tumors. The mechanical behavior of breast tissue is represented by a modified Veronda-Westmann model with one linear and one nonlinear elastic parameter. The spatial distribution of these elastic parameters is determined by solving an inverse problem within the region of interest (ROI). This inverse problem solution requires the knowledge of the displacement fields at small and large strains. The displacement fields are measured using a free-hand ultrasound strain imaging technique wherein, a linear array ultrasound transducer is positioned on the breast and radio frequency echo signals are recorded within the ROI while the tissue is slowly deformed with the transducer. Incremental displacement fields are determined from successive radio-frequency frames by employing cross-correlation techniques. The rectangular regions of interest were subjectively selected to obtain low noise displacement estimates and therefore were variables that ranged from 346 to 849.6 mm2 . It is observed that malignant tumors stiffen at a faster rate than benign tumors and based on this criterion nine out of ten tumors were correctly classified as being either benign or malignant.

Lagrangian displacement tracking using a polar grid between endocardial and epicardial contours for cardiac strain imaging.

Accurate cardiac deformation analysis for cardiac displacement and strain imaging over time requires Lagrangian description of deformation of myocardial tissue structures. Failure to couple the estimated displacement and strain information with the correct myocardial tissue structures will lead to erroneous result in the displacement and strain distribution over time. Lagrangian based tracking in this paper divides the tissue structure into a fixed number of pixels whose deformation is tracked over the cardiac cycle. An algorithm that utilizes a polar-grid generated between the estimated endocardial and epicardial contours for cardiac short axis images is proposed to ensure Lagrangian description of the pixels. Displacement estimates from consecutive radiofrequency frames were then mapped onto the polar grid to obtain a distribution of the actual displacement that is mapped to the polar grid over time. A finite element based canine heart model coupled with an ultrasound simulation program was used to verify this approach. Segmental analysis of the accumulated displacement and strain over a cardiac cycle demonstrate excellent agreement between the ideal result obtained directly from the finite element model and our Lagrangian approach to strain estimation. Traditional Eulerian based estimation results, on the other hand, show significant deviation from the ideal result. An in vivo comparison of the displacement and strain estimated using parasternal short axis views is also presented. Lagrangian displacement tracking using a polar grid provides accurate tracking of myocardial deformation demonstrated using both finite element and in vivo radiofrequency data acquired on a volunteer. In addition to the cardiac application, this approach can also be utilized for transverse scans of arteries, where a polar grid can be generated between the contours delineating the outer and inner wall of the vessels from the blood flowing though the vessel.

Noninvasive electromechanical wave imaging and conduction-relevant velocity estimation in vivo

Electromechanical wave imaging is a novel technique for the noninvasive mapping of conduction waves in the left ventricle through the combination of ECG gating, high frame rate ultrasound imaging and radio-frequency (RF)-based displacement estimation techniques. In this paper, we describe this new technique and characterize the origin and velocity of the wave under distinct pacing schemes. First, in vivo imaging (30 MHz) was performed on anesthetized, wild-type mice ( n = 12) at high frame rates in order to take advantage of the transient electromechanical coupling occurring in the myocardium. The RF signal acquisition in a long-axis echocardiographic view was gated between consecutive R-wave peaks of the mouse electrocardiogram (ECG) and yielded an ultra-high RF frame rate of 8000 frames/s (fps). The ultrasound RF signals in each frame were digitized at 160 MHz. Axial, frame-to-frame displacements were estimated using 1D cross-correlation (window size of 240 μm, overlap of 90%). Three pacing protocols were sequentially applied in each mouse: (1) sinus rhythm (SR), (2) right-atrial (RA) pacing and (3) right-ventricular (RV) pacing. Pacing was performed using an eight-electrode catheter placed into the right side of the heart with the capability of pacing from any adjacent bipole. During a cardiac cycle, several waves were depicted on the electromechanical wave images that propagated transmurally and/or from base to apex, or apex to base, depending on the type of pacing and the cardiac phase. Through comparison between the ciné-loops and their corresponding ECG obtained at different pacing protocols, we were able to identify and separate the electrically induced, or contraction, waves from the hemodynamic (or, blood-wall coupling) waves. In all cases, the contraction wave was best observed along the posterior wall starting at the S-wave of the ECG, which occurs after Purkinje fiber, and during myocardial, activation. The contraction wave was identified based on the fact that it changed direction only when the pacing origin changed, i.e., it propagated from the apex to the base at SR and RA pacing and from base to apex at RV pacing. This reversal in the wave propagation direction was found to be consistent in all mice scanned and the wave velocity values fell within the previously reported conduction wave range with statistically significant differences between SR/RA pacing (0.85 ± 0.22 m/s and 0.84 ± 0.20 m/s, respectively) and RV pacing (−0.52 ± 0.31 m/s; p < 0.0001). This study thus shows that imaging the electromechanical function of the heart noninvasively is feasible. It may therefore constitute a unique noninvasive method for conduction wave mapping of the entire left ventricle. Such a technology can be extended to 3D mapping and/or used for early detection of dyssynchrony, arrhythmias, left-bundle branch block, or other conduction abnormalities as well as diagnosis and treatment thereof.

Ultrasound simulation of real-time temperature estimation during radiofrequency ablation using finite element models

Radiofrequency ablation is the most common minimally invasive therapy used in the United States to treat hepatocellular carcinoma and liver metastases. The ability to perform real-time temperature imaging while a patient is undergoing ablation therapy may help reduce the high recurrence rates following ablation therapy. Ultrasound echo signals undergo time shifts with increasing temperature due to sound speed and thermal expansion, which are tracked using both 1D cross correlation and 2D block matching based speckle tracking methods. In this paper, we present a quantitative evaluation of the accuracy and precision of temperature estimation using the above algorithms on both simulated and experimental data. A finite element analysis simulation of radiofrequency ablation of hepatic tissue was developed. Finite element analysis provides a method to obtain the exact temperature distribution along with a mapping of the tissue displacement due to thermal expansion. These local displacement maps were combined with the displacement due to speed of sound changes and utilized to generate ultrasound radiofrequency frames at specified time increments over the entire ablation procedure. These echo signals provide an ideal test-bed to evaluate the performance of both speckle tracking methods, since the estimated temperature results can be compared directly to the exact finite element solution. Our results indicate that the 1D cross-correlation (CC) method underestimates the cumulative displacement by 0.20 mm, while the underestimation with 2D block matching (BM) is about 0.14 mm after 360 s of ablation. The 1D method also overestimates the size of the ablated region by 5.4% when compared to 2.4% with the 2D method after 720 s of ablation. Hence 2D block matching provides better tracking of temperature variations when compared to the 1D cross-correlation method over the entire duration of the ablation procedure. In addition, results obtained using 1D cross-correlation diverge from the ideal finite element results after 7 min of ablation and for temperatures greater than 65 °C. In a similar manner, experimental results presented using a tissue-mimicking phantom also demonstrate that the maximum percent difference with 2D block matching was 5%, when compared to 31% with the 1D method over the 700 s heating duration on the phantom.

Theoretical Quality Assessment of Myocardial Elastography with In Vivo Validation

Myocardial elastography (ME), a radio frequency (RF)-based speckle tracking technique with one-dimensional (1-D) cross correlation and novel recorrelation methods in a 2-D search was proposed to estimate and fully image 2-D transmural deformation field and to detect abnormal cardiac function. A theoretical framework was first developed in order to evaluate the performance of 2-D myocardial elastography based on a previously developed 3-D finite-element model of the canine left ventricle. A normal (control) and an ischemic (left-circumflex, LCx) model, which more completely represented myocardial deformation than a kinematic model, were considered. A 2-D convolutional image formation model was first used to generate RF signals for quality assessment of ME in the normal and ischemic cases. A 3-D image formation model was further developed to investigate the effect of the out-of-plane motion on the 2-D, in-plane motion estimation. Both orthogonal, in-plane displacement components (i.e., lateral and axial) between consecutive RF frames were iteratively estimated. All the estimated incremental 2-D displacements from end-diastole (ED) to end-systole (ES) were then accumulated to acquire the cumulative 2-D displacements, which were further used to calculate the cumulative 2-D systolic finite strains. Furthermore, the cumulative systolic radial and circumferential strains, which were angle- and frame-rate independent, were obtained from the 2-D finite-strain components and imaged in full view to detect the ischemic region. We also explored the theoretical understanding of the limitations of our technique for the accurate depiction of disease and validated it in vivo against tagged magnetic resonance imaging (tMRI) in the case of a normal human myocardium in a 2-D short-axis (SA) echocardiographic view. The theoretical framework succeeded in demonstrating that the 2-D myocardial elastography technique was a reliable tool for the complete estimation and depiction of the in-plane myocardial deformation field as well as for accurate identification of pathological mechanical function using established finite-element, left-ventricular canine models. In a preliminary study, the 2-D myocardial elastography was shown capable of imaging myocardial deformation comparable to equivalent tMRI estimates in a clinical setting.

Myocardial Elastography at Both High Temporal and Spatial Resolution for the Detection of Infarcts

Myocardial elastography is a novel method for noninvasively assessing regional myocardial function, with the advantages of high spatial and temporal resolution and high signal-to-noise ratio (SNR). In this paper, in-vivo experiments were performed in anesthetized normal and infarcted mice (one day after left anterior descending coronary artery [LAD] ligation) using a high-resolution (30 MHz) ultrasound system (Vevo 770, VisualSonics Inc., Toronto, ON, Canada). Radiofrequency (RF) signals of the left ventricle (LV) in longitudinal (long-axis) view and the associated electrocardiogram (ECG) were simultaneously acquired. Using a retrospective ECG gating technique, 2-D full field-of-view RF frames were acquired at an extremely high frame rate (8 kHz) that resulted in high-quality incremental displacement and strain estimation of the myocardium. The incremental results were further accumulated to obtain the cumulative displacements and strains. Two-dimensional and M-mode displacement images and strain images (elastograms), as well as displacement and strain profiles as a function of time, were compared between normal and infarcted mice. Incremental results clearly depicted cardiac events including LV contraction, LV relaxation and isovolumetric phases in both normal and infarcted mice, and also evidently indicated reduced motion and deformation in the infarcted myocardium. The elastograms indicated that the infarcted regions underwent thinning during systole rather than thickening, as in the normal case. The cumulative elastograms were found to have higher elastographic SNR (SNR e) than the incremental elastograms ( e.g., 10.6 vs. 4.7 in a normal myocardium, and 6.0 vs. 2.4 in an infarcted myocardium). Finally, preliminary statistical results from nine normal ( m = 9) and seven infarcted ( n = 7) mice indicated the capability of the cumulative strain in differentiating infracted from normal myocardia. In conclusion, myocardial elastography could provide regional strain information at simultaneously high temporal (≥0.125 ms) and spatial (∼55 μm) resolution as well as high precision (∼0.05 μm displacement). This technique was thus capable of accurately characterizing normal myocardial function throughout an entire cardiac cycle, at the same high resolution, and detecting and localizing myocardial infarction in vivo. (E-mail: ek2191@columbia.edu)

Elastographic imaging of strain distribution in the anterior cruciate ligament and at the ligament–bone insertions

The anterior cruciate ligament (ACL) functions as a mechanical stabilizer in the tibiofemoral joint, and is the most commonly injured knee ligament. To improve the clinical outcome of tendon grafts used for ACL reconstructions, our long-term goal is to promote graft-bone integration via the regeneration of the native ligament-bone interface. An understanding of strain distribution at this interface is crucial for functional scaffold design and clinical evaluation. Experimental determination, however, has been difficult due to the small length scale of the insertion sites. This study utilizes ultrasound elastography to characterize the response of the ACL and ACL-bone interface under tension. Specifically, bovine tibiofemoral joints were mounted on a material testing system and loaded in tension while radiofrequency (RF) data were acquired at 5 MHz. Axial strain elastograms between RF frames and a reference frame were generated using crosscorrelation and recorrelation techniques. Elastographic analyses revealed that when the joint was loaded in tension, complex strains with both compressive and tensile components occurred at the tibial insertion, with higher strains found at the insertion sites. In addition, the displacement was greatest at the ACL proper and decreased in value gradually from ligament to bone, likely a reflection of the matrix organization at the ligament-bone interface. Our results indicate that elastography is a novel method that can be readily used to characterize the mechanical properties of the ACL and its insertions into bone.

Monitoring the formation of thermal lesions with heat-induced echo-strain imaging: A feasibility study

We investigated the feasibility of using echo-strain images to visualize the extent of high-intensity ultrasound (US)-induced thermal lesions during their formation. Echo-strain, defined as the relative deformation of the backscattered ultrasonic signal, is due to tissue expansion and to changes in the speed of sound during heating. First, a theoretical framework was developed to predict the influence of these effects on the echo signal. Then, a simulation tool was developed to create simulated echo-strain images in thermal lesions. Finally, experimental echo-strain images were acquired in 10 porcine liver samples in vitro for various exposure durations and ultrasonic intensities (resulting in lesions that extended 3 to 8 mm deep from the surface). For this purpose, radiofrequency (RF) frames were acquired at 8 frames per s while heating. For each consecutive pair of RF frames, an echo-strain image was calculated using standard elastographic processing. The echo-strain images were cumulated and displayed. The experimental echo-strain images were compared with gross pathology. The (isoechoic) lesions were visible both in simulated and in experimental cumulated echo-strain images as apparent expansion areas (tensile echo-strain), whereas surrounding tissues exhibited apparent compression. The tensile echo-strain area underestimated the lesion in simulations, but was representative of the lesion in experiments. High correspondence was found between the lesion depth measured from experimental cumulative echo-strain images ( y) and from gross pathology ( x) (Pearson’s correlation = 0.90, linear regression y = x−0.1 mm, residual error = 0 ± 0.9 mm). We hypothesized that significant tissue expansion made the thermal lesions highly visible in the experimental echo-strain images. In two cases, the ultrasonic intensity was too low to induce a lesion, and the corresponding experimental echo-strain images showed no visible lesion. We conclude that cumulative echo-strain images have the potential to monitor the formation of high-intensity US-induced thermal lesions. (E-mail: Souchon@lyon.inserm.fr)