3D Myocardial Elastography In Vivo

Assessment of spinal cord injury using ultrasound elastography in a rabbit model in vivo

The effect of the mechanical micro-environment on spinal cord injury (SCI) and treatment effectiveness remains unclear. Currently, there are limited imaging methods that can directly assess the localized mechanical behavior of spinal cords in vivo. In this study, we apply new ultrasound elastography (USE) techniques to assess SCI in vivo at the site of the injury and at the time of one week post injury, in a rabbit animal model. Eleven rabbits underwent laminectomy procedures. Among them, spinal cords of five rabbits were injured during the procedure. The other six rabbits were used as control. Two neurological statuses were achieved: non-paralysis and paralysis. Ultrasound data were collected one week post-surgery and processed to compute strain ratios. Histologic analysis, mechanical testing, magnetic resonance imaging (MRI), computerized tomography and MRI diffusion tensor imaging (DTI) were performed to validate USE results. Strain ratios computed via USE were found to be significantly different in paralyzed versus non-paralyzed rabbits. The myelomalacia histologic score and spinal cord Young's modulus evaluated in selected animals were in good qualitative agreement with USE assessment. It is feasible to use USE to assess changes in the spinal cord of the presented animal model. In the future, with more experimental data available, USE may provide new quantitative tools for improving SCI diagnosis and prognosis.

Doppler and Pair-Wise Optical Flow Constrained 3D Motion Compensation for 3D Ultrasound Imaging

Volumetric (3D) ultrasound imaging using a 2D matrix array probe is increasingly developed for various clinical procedures. However, 3D ultrasound imaging suffers from motion artifacts due to tissue motions and a relatively low frame rate. Current Doppler-based motion compensation (MoCo) methods only allow 1D compensation in the in-range dimension. In this work, we propose a new 3D-MoCo framework that combines 3D velocity field estimation and a two-step compensation strategy for 3D diverging wave compounding imaging. Specifically, our framework explores two constraints of a round-trip scan sequence of 3D diverging waves, i.e., Doppler and pair-wise optical flow, to formulate the estimation of the 3D velocity fields as a global optimization problem, which is further regularized by the divergence-free and first-order smoothness. The two-step compensation strategy is to first compensate for the 1D displacements in the in-range dimension and then the 2D displacements in the two mutually orthogonal cross-range dimensions. Systematical in-silico experiments were conducted to validate the effectiveness of our proposed 3D-MoCo method. The results demonstrate that our 3D-MoCo method achieves higher image contrast, higher structural similarity, and better speckle patterns than the corresponding 1D-MoCo method. Particularly, the 2D cross-range compensation is effective for fully recovering image quality.

In Vivo Longitudinal Monitoring of Cardiac Remodeling in Murine Ischemia Models With Adaptive Bayesian Regularized Cardiac Strain Imaging: Validation Against Histology

Adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) uses raw radiofrequency signals to estimate myocardial wall contractility as a surrogate measure of relative tissue elasticity incorporating regularization in the Bayesian sense. We determined the feasibility of using ABR-CSI -derived strain for in vivo longitudinal monitoring of cardiac remodeling in a murine ischemic injury model (myocardial infarction [MI] and ischemia-reperfusion [IR]) and validated the findings against ground truth histology. We randomly stratified 30 BALB/CJ mice (17 females, 13 males, median age = 10 wk) into three surgical groups (MI = 10, IR = 12, sham = 8) and imaged pre-surgery (baseline) and 1, 2, 7 and 14 d post-surgery using a pre-clinical high-frequency ultrasound system (VisualSonics Vevo 2100). We then used ABR-CSI to estimate end-systolic and peak radial (er) and longitudinal (el) strain estimates. ABR-CSI was found to have the ability to serially monitor non-uniform cardiac remodeling associated with murine MI and IR non-invasively through temporal variation of strain estimates post-surgery. Furthermore, radial end-systole (ES) strain images and segmental strain curves exhibited improved discrimination among infarct, border and remote regions around the myocardium compared with longitudinal strain results. For example, the MI group had significantly lower (Friedman's with Bonferroni-Dunn test, p = 0.002) ES er values in the anterior middle (infarcted) region at day 14 (n = 9, 9.23 ± 7.39%) compared with the BL group (n = 9, 44.32 ± 5.49). In contrast, anterior basal (remote region) mean ES er values did not differ significantly (non-significant Friedman's test, χ2 = 8.93, p = 0.06) at day 14 (n = 6, 33.05 ± 6.99%) compared with baseline (n = 6, 34.02 ± 6.75%). Histology slides stained with Masson's trichrome (MT) together with a machine learning model (random forest classifier) were used to derive the ground truth cardiac fibrosis parameter termed histology percentage of myocardial fibrosis (PMF). Both radial and longitudinal strain were found to have strong statistically significant correlations with the PMF parameter. However, radial strain had a higher Spearman's correlation value (εresρ = -0.67, n = 172, p < 0.001) compared with longitudinal strain (εlesρ = -0.60, n = 172, p < 0.001). Overall, the results of this study indicate that ABR-CSI can reliably perform non-invasive detection of infarcted and remote myocardium in small animal studies.

Murine cardiac fibrosis localization using adaptive Bayesian cardiac strain imaging in vivo

An adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) algorithm for in vivo murine myocardial function assessment is presented. We report on 31 BALB/CJ mice (n = 17 females, n = 14 males), randomly stratified into three surgical groups: myocardial infarction (MI, n = 10), ischemia–reperfusion (IR, n = 13) and control (sham, n = 8) imaged pre-surgery (baseline- BL), and 1, 2, 7 and 14 days post-surgery using a high frequency ultrasound imaging system (Vevo 2100). End-systole (ES) radial and longitudinal strain images were used to generate cardiac fibrosis maps using binary thresholding. Percentage fibrotic myocardium (PFM) computed from regional fibrosis maps demonstrated statistically significant differences post-surgery in scar regions. For example, the MI group had significantly higher PFM_Radial (%) values in the anterior mid region (p = 0.006) at Day 14 (n = 8, 42.30 ± 14.57) compared to BL (n = 12, 1.32 ± 0.85). A random forest classifier automatically detected fibrotic regions from ground truth Masson’s trichrome stained histopathology whole slide images. Both PFM_Radial (r = 0.70) and PFM_Longitudinal (r = 0.60) results demonstrated strong, positive correlation with PFM_{Histopathology} (p < 0.001).

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.

Deformability of ascending thoracic aorta aneurysms assessed using ultrafast ultrasound and a principal strain estimator: In vitro evaluation and in vivo feasibility

BACKGROUND

Noninvasive vascular strain imaging under conventional line-by-line scanning has a low frame rate and lateral resolution, and depends on the coordinate system. It is thus affected by high deformations due to image decorrelation between frames.

PURPOSE

To develop an ultrafast time-ensemble regularized tissue-Doppler optical-flow principal strain estimator for aorta deformability assessment in a long-axis view.

METHODS

This approach alleviated the impact of lateral resolution using image compounding and that of the coordinate system dependency using principal strain. Accuracy and feasibility were evaluated in two aorta-mimicking phantoms first, and then in four age-matched individuals with either a normal aorta or a pathological ascending thoracic aorta aneurysm (TAA).

RESULTS

Instantaneous aortic maximum and minimum principal strain maps and regional accumulated strains during each cardiac cycle were estimated at systolic and diastolic phases to characterize the normal aorta and TAA. In vitro, principal strain results matched sonomicrometry measurements. In vivo, a significant decrease in maximum and minimum principal strains was observed in TAA cases, whose range was respectively 7.9 ± 6.4% and 8.2 ± 2.6% smaller than in normal aortas.

CONCLUSIONS

The proposed principal strain estimator showed an ability to potentially assess TAA deformability, which may provide an individualized and reliable evaluation method for TAA rupture risk assessment. This article is protected by copyright. All rights reserved.

Wave-based optical coherence elastography: The 10-year perspective

After 10 years of progress and innovation, optical coherence elastography (OCE) based on the propagation of mechanical waves has become one of the major and the most studied OCE branches, producing a fundamental impact in the quantitative and nondestructive biomechanical characterization of tissues. Preceding previous progress made in ultrasound and magnetic resonance elastography; wave-based OCE has pushed to the limit the advance of three major pillars: (1) implementation of novel wave excitation methods in tissues, (2) understanding new types of mechanical waves in complex boundary conditions by proposing advance analytical and numerical models, and (3) the development of novel estimators capable of retrieving quantitative 2D/3D biomechanical information of tissues. This remarkable progress promoted a major advance in answering basic science questions and the improvement of medical disease diagnosis and treatment monitoring in several types of tissues leading, ultimately, to the first attempts of clinical trials and translational research aiming to have wave-based OCE working in clinical environments. This paper summarizes the fundamental up-to-date principles and categories of wave-based OCE, revises the timeline and the state-of-the-art techniques and applications lying in those categories, and concludes with a discussion on the current challenges and future directions, including clinical translation research.

Dynamic Myocardial Ultrasound Localization Angiography

Dynamic Myocardial Ultrasound Localization Angiography (MULA) is an ultrasound-based imaging modality destined to enhance the diagnosis and treatment monitoring of coronary pathologies. Current diagnosis methods of coronary artery disease focus on the observation of vessel narrowing in the coronary vasculature to assess the organ's condition. However, we would strongly benefit from mapping and measuring flow from intramyocardial arterioles and capillaries as they are the direct vehicle of the myocardium blood income. With the advent of ultrafast ultrasound scanners, imaging modalities based on the localization and tracking of injected microbubbles allow for the subwavelength resolution imaging of an organ's vasculature. Yet, the application of these vascular imaging modalities relies on an accumulation of cine loops of a region of interest undergoing no or minimal tissue motion. This work introduces the MULA framework that combines 1) the mapping of the dynamics of the microvascular flow using an ultrasound sequence triggered by the electrocardiogram with a 2) novel Lagrangian beamformer based on non-rigid motion registration algorithm to form images directly in the myocardium's material coordinates and thus correcting for the large myocardial motion and deformation. Specifically, we show that this framework enables the non-invasive imaging of the angioarchitecture and dynamics of intramyocardial flow in vessels as small as a few tens of microns in the rat's beating heart in vivo.

4D Ultrafast Ultrasound Imaging of Naturally Occurring Shear Waves in the Human Heart

The objectives were to develop a novel three-dimensional technology for imaging naturally occurring shear wave (SW) propagation, demonstrate feasibility on human volunteers and quantify SW velocity in different propagation directions. Imaging of natural SWs generated by valve closures has emerged to obtain a direct measurement of cardiac stiffness. Recently, natural SW velocity was assessed in two dimensions on parasternal long axis view under the assumption of a propagation direction along the septum. However, in this approach the source localization and the complex three-dimensional propagation wave path was neglected making the speed estimation unreliable. High volume rate transthoracic acquisitions of the human left ventricle (1100 volume/s) was performed with a 4D ultrafast echocardiographic scanner. Four-dimensional tissue velocity cineloops enabled visualization of aortic and mitral valve closure waves. Energy and time of flight mapping allowed propagation path visualization and source localization, respectively. Velocities were quantified along different directions. Aortic and mitral valve closure SW velocities were assessed for the three volunteers with low standard deviation. Anisotropic propagation was also found suggesting the necessity of using a three-dimensional imaging approach. Different velocities were estimated for the three directions for the aortic (3.4± 0.1 m/s, 3.5± 0.3 m/s, 5.4± 0.7 m/s) and the mitral (2.8± 0.5 m/s, 2.9± 0.3 m/s, 4.6± 0.7 m/s) valve SWs. 4D ultrafast ultrasound alleviates the limitations of 2D ultrafast ultrasound for cardiac SW imaging based on natural SW propagations and enables a comprehensive measurement of cardiac stiffness. This technique could provide stiffness mapping of the left ventricle.

Radial Motion Estimation of Myocardium in Rats with Myocardial Infarction: A Hybrid Method of FNCCGLAM and Polar Transformation

Ultrasound elastography is a novel approach of evaluating regional myocardial systolic function and detecting infarcted area. This study aims to evaluate the radial motion of myocardial infarction (MI) area in left ventricular parasternal short axis (PSAX) view using a hybrid method of fast normalized cross-correlation and global analytic minimization (FNCCGLAM) and polar transformation. Fifteen rats were randomly selected for sham group, MI group and ischemia-reperfusion (IR) group (N = 5 for each group). The ultrasound radiofrequency data of the PSAX view of rat heart were acquired. After polar transformation of the data, the infarcted myocardium with the change of mechanical property was tracked over one myocardial systolic phase by the proposed method in comparison with fast normalized cross-correlation (FNCC) and dynamic programming analytic minimization (DPAM). To obtain a clear visualization of the myocardium, the inverse polar transformation was performed. The results indicated that the use of FNCCGLAM refined the myocardial displacements to obtain high-quality myocardial elastographic map with a higher contrast-to-noise ratio and dynamically tracked the infarcted myocardial segment with a higher success rate in comparison with FNCC and DPAM. It was found that the radial systolic motion of the infarcted anterior segment in the MI group reduced significantly (p < 0.05) in comparison with the sham group, while the systolic function of that myocardial segment in the IR group recovered at some extent. The results in this study suggest that FNCCGLAM is superior to FNCC and DPAM with the improved accuracy and robustness of motion estimation and has potentials as displacement estimator in ultrasound elastography.

Noninvasive localization of cardiac arrhythmias using electromechanical wave imaging

Cardiac arrhythmias are a major cause of morbidity and mortality worldwide. The 12-lead electrocardiogram (ECG) is the current noninvasive clinical tool used to diagnose and localize cardiac arrhythmias. However, it has limited accuracy and is subject to operator bias. Here, we present electromechanical wave imaging (EWI), a high-frame rate ultrasound technique that can noninvasively map with high accuracy the electromechanical activation of atrial and ventricular arrhythmias in adult patients. This study evaluates the accuracy of EWI for localization of various arrhythmias in all four chambers of the heart before catheter ablation. Fifty-five patients with an accessory pathway (AP) with Wolff-Parkinson-White (WPW) syndrome, premature ventricular complexes (PVCs), atrial tachycardia (AT), or atrial flutter (AFL) underwent transthoracic EWI and 12-lead ECG. Three-dimensional (3D) rendered EWI isochrones and 12-lead ECG predictions by six electrophysiologists were applied to a standardized segmented cardiac model and subsequently compared to the region of successful ablation on 3D electroanatomical maps generated by invasive catheter mapping. There was significant interobserver variability among 12-lead ECG reads by expert electrophysiologists. EWI correctly predicted 96% of arrhythmia locations as compared with 71% for 12-lead ECG analyses [unadjusted for arrhythmia type: odds ratio (OR), 11.8; 95% confidence interval (CI), 2.2 to 63.2; P = 0.004; adjusted for arrhythmia type: OR, 12.1; 95% CI, 2.3 to 63.2; P = 0.003]. This double-blinded clinical study demonstrates that EWI can localize atrial and ventricular arrhythmias including WPW, PVC, AT, and AFL. EWI when used with ECG may allow for improved treatment for patients with arrhythmias.

Physics-guided machine learning for 3-D quantitative quasi-static elasticity imaging

We present a 3D extension of the Autoprogressive Method (AutoP) for quantitative quasi-static ultrasonic elastography (QUSE) based on sparse sampling of force-displacement measurements. Compared to current model-based inverse methods, our approach requires neither geometric nor constitutive model assumptions. We build upon our previous report for 2D QUSE and demonstrate the feasibility of recovering the 3D linear-elastic material property distribution of gelatin phantoms under compressive loads. Measurements of boundary geometry, applied surface forces, and axial displacements enter into AutoP where a Cartesian neural network constitutive model (CaNNCM) interacts with finite element analyses to learn physically consistent material properties with no prior constitutive model assumption. We introduce a new regularization term uniquely suited to AutoP that improves the ability of CaNNCMs to extract information about spatial stress distributions from measurement data. Results of our study demonstrate that acquiring multiple sets of force-displacement measurements by moving the US probe to different locations on the phantom surface not only provides AutoP with the necessary information for a CaNNCM to learn the 3D material property distribution, but may significantly improve the accuracy of the Young's modulus estimates. Furthermore, we investigate the trade-offs of decreasing the contact area between the US transducer and phantom surface in an effort to increase sensitivity to surface force variations without additional instrumentation. Each of these modifications improves the ability of CaNNCMs trained in AutoP to learn the spatial distribution of Young's modulus from force-displacement measurements.

High Frame Rate Ultrasound for Electromechanical Wave Imaging to Differentiate Endocardial From Epicardial Myocardial Activation

Differentiation between epicardial and endocardial ventricular activation remains a challenge despite the latest technologies available. The aim of the present study was to develop a new tool method, based on electromechanical wave imaging (EWI), to improve arrhythmogenic substrate activation analysis. Experiments were conducted on left ventricles (LVs) of four isolated working mode swine hearts. The protocol aimed at demonstrating that different patterns of mechanical activation could be observed whether the ventricle was in sinus rhythm, paced from the epicardium or from the endocardium. A total of 72 EWI acquisitions were recorded on the anterior, lateral and posterior segments of the LV. A total of 54 loop records were blindly assigned to two readers. EWI sequences interpretations were correct in 89% of cases. The overall agreement rate between the two readers was 83%. When in a paced ventricle, the origin of the wave front was focal and originated from the endocardium or the epicardium. In sinus rhythm, wave front was global and activated within the entire endocardium toward the epicardium at a speed of 1.7 ± 0.28 m·s^-1. Wave front speeds were respectively measured when the endocardium or the epicardium were paced at a speed of 1.1 ± 0.35 m·s^-1 versus 1.3 ± 0.34 m·s^-1 (p = NS). EWI activation mapping allows activation localization within the LV wall and calculation of the wave front propagation speed through the muscle. In the future, this technology could help localize activation within the LV thickness during complex ablation procedures.

Hierarchical Motion Estimation With Bayesian Regularization in Cardiac Elastography: Simulation and In Vivo Validation

Cardiac elastography (CE) is an ultrasound-based technique utilizing radio-frequency (RF) signals for assessing global and regional myocardial function. In this work, a complete strain estimation pipeline for incorporating a Bayesian regularization-based hierarchical block-matching algorithm, with Lagrangian motion description and myocardial polar strain estimation is presented. The proposed regularization approach is validated using finite-element analysis (FEA) simulations of a canine cardiac deformation model that is incorporated into an ultrasound simulation program. Interframe displacements are initially estimated using a hierarchical motion estimation framework. Incremental displacements are then accumulated under a Lagrangian description of cardiac motion from end-diastole (ED) to end-systole (ES). In-plane Lagrangian finite strain tensors are then derived from the accumulated displacements. Cartesian to cardiac coordinate transformation is utilized to calculate radial and longitudinal strains for ease of interpretation. Benefits of regularization are demonstrated by comparing the same hierarchical block-matching algorithm with and without regularization. Application of Bayesian regularization in the canine FEA model provided improved ES radial and longitudinal strain estimation with statistically significant ( ) error reduction of 48.88% and 50.16%, respectively. Bayesian regularization also improved the quality of temporal radial and longitudinal strain curves with error reductions of 78.38% and 86.67% ( ), respectively. Qualitative and quantitative improvements were also visualized for in vivo results on a healthy murine model after Bayesian regularization. Radial strain elastographic signal-to-noise ratio (SNR_e) increased from 3.83 to 4.76 dB, while longitudinal strain SNR_e increased from 2.29 to 4.58 dB with regularization.

4D simultaneous tissue and blood flow Doppler imaging: revisiting cardiac Doppler index with single heart beat 4D ultrafast echocardiography

The goal of this study was to demonstrate the feasibility of semi-automatic evaluation of cardiac Doppler indices in a single heartbeat in human hearts by performing 4D ultrafast echocardiography with a dedicated sequence of 4D simultaneous tissue and blood flow Doppler imaging. 4D echocardiography has the potential to improve the quantification of major cardiac indices by providing more reproducible and less user dependent measurements such as the quantification of left ventricle (LV) volume. The evaluation of Doppler indices, however, did not benefit yet from 4D echocardiography because of limited volume rates achieved in conventional volumetric color Doppler imaging but also because spectral Doppler estimation is still restricted to a single location. High volume rate (5200 volume s^-1) transthoracic simultaneous tissue and blood flow Doppler acquisitions of three human LV were performed using a 4D ultrafast echocardiography scanner prototype during a single heartbeat. 4D color flow, 4D tissue Doppler cineloops and spectral Doppler at each voxel were computed. LV outflow tract, mitral inflow and basal inferoseptal locations were automatically detected. Doppler indices were derived at these locations and were compared against clinical 2D echocardiography. Blood flow Doppler indices E (early filling), A (atrial filling), E/A ratio, S (systolic ejection) and cardiac output were assessed on the three volunteers. Simultaneous tissue Doppler indices e' (mitral annular velocity peak), a' (late velocity peak), e'/a' ratio, s' (systolic annular velocity peak), E/e' ratio were also estimated. Standard deviations on three independent acquisitions were averaged over the indices and was found to be inferior to 4% and 8.5% for Doppler flow and tissue Doppler indices, respectively. Comparison against clinical 2D echocardiography gave a p  value larger than 0.05 in average indicating no significant differences. 4D ultrafast echocardiography can quantify the major cardiac Doppler indices in a single heart beat acquisition.

Compressed sensing reconstruction of synthetic transmit aperture dataset for volumetric diverging wave imaging

A high volume rate and high performance ultrasound imaging method based on a matrix array is proposed by using compressed sensing (CS) to reconstruct the complete dataset of synthetic transmit aperture (STA) from three-dimensional (3D) diverging wave transmissions (i.e. 3D CS-STA). Hereto, a series of apodized 3D diverging waves are transmitted from a fixed virtual source, with the ith row of a Hadamard matrix taken as the apodization coefficients in the ith transmit event. Then CS is used to reconstruct the complete dataset, based on the linear relationship between the backscattered echoes and the complete dataset of 3D STA. Finally, standard STA beamforming is applied on the reconstructed complete dataset to obtain the volumetric image. Four layouts of element numbering for apodizations and transmit numbers of 16, 32 and 64 are investigated through computer simulations and phantom experiments. Furthermore, the proposed 3D CS-STA setups are compared with 3D single-line-transmit (SLT) and 3D diverging wave compounding (DWC). The results show that, (i) 3D CS-STA has competitive lateral resolutions to 3D STA, and their contrast ratios (CRs) and contrast-to-noise ratios (CNRs) approach to those of 3D STA as the number of transmit events increases in noise-free condition. (ii) the tested 3D CS-STA setups show good robustness in complete dataset reconstruction in the presence of different levels of noise. (iii) 3D CS-STA outperforms 3D SLT and 3D DWC. More specifically, the 3D CS-STA setup with 64 transmit events and the Random layout achieves ~31% improvement in lateral resolution, ~14% improvement in ratio of the estimated-to-true cystic areas, a higher volume rate, and competitive CR/CNR when compared with 3D DWC. The results demonstrate that 3D CS-STA has great potential of providing high quality volumetric image with a higher volume rate.

A Model-Based Approach to Investigate the Effect of a Long Bone Fracture on Ultrasound Strain Elastography

The mechanical behavior of long bones and fractures has been under investigation for many decades due to its complexity and clinical relevance. In this paper, we report a new subject-specific methodology to predict and analyze the mechanical behavior of the soft tissue at a bone interface with the intent of identifying the presence and location of bone abnormalities with high accuracy, spatial resolution, and contrast. The proposed methodology was tested on both intact and fractured rabbit femur samples with finite element-based 3-D simulations, created from actual femur computed tomography data, and ultrasound elastography experiments. The results included in this study demonstrate that elastographic strains at the bone/soft tissue interface can be used to differentiate fractured femurs from the intact ones on a distribution level. These results also demonstrate that coronal plane axial shear strain creates a unique contrast mechanism that can be used to reliably detect fractures (both complete and incomplete) in long bones. Kruskal-Wallis test further demonstrates that the contrast measure for the fracture group (simulation: 2.1286±0.2206; experiment: 2.7034 ± 1.0672) is significantly different from that for the intact group (simulation: 0 ± 0; experiment: 1.1540±0.6909) when using coronal plane axial shear strain elastography ( < 0.01). We conclude that: 1) elastography techniques can be used to accurately identify the presence and location of fractures in a long bone and 2) the proposed model-based approach can be used to predict and analyze strains at a bone fracture site and to better interpret experimental elastographic data.

Real-Time High-Frame-Rate Cardiac B-Mode and Tissue Doppler Imaging Based on Multiline Transmission and Multiline Acquisition

Cardiovascular diseases, the leading cause of death in the world, are often associated with the dysfunction of the left ventricle. Even if, in clinical practice, the myocardial function is often assessed through visual wall motion scoring on B-mode images, quantitative techniques have been introduced, e.g., ultrasound tissue Doppler imaging (TDI). However, this technique suffers from the limited frame rate of currently available imaging techniques that needs to be balanced with the field of view. High-frame-rate (HFR) cardiac imaging has been recently tested off-line by simultaneously transmitting multiple focused beams into different directions and acquiring raw channel data into a PC. Several image lines were then reconstructed from the echoes of each transmission (TX) event. The same approach has been used to increase the TDI frame rate without restricting the field of view. This paper demonstrates the real-time feasibility of multiline TX and acquisition methods for both HFR cardiac B-mode and TDI. These approaches have been implemented on the ULA-OP 256 research scanner, by taking care that the related resources were optimally exploited for these new applications. The obtainable performance in terms of image quality and frame rate has also been investigated. Experiments performed with a 128-element phased array probe show, for the first time, that real-time B-mode imaging is feasible at up to 1150 Hz without significant reduction in image quality or field of view. The implementation of a real-time TDI algorithm allowed obtaining TDI images with a frame rate of 288 Hz for a 90°-wide field of view. Finally, in vivo examples demonstrate the feasibility and the suitability of the method in clinical studies.

Cardiac Lesion Mapping In Vivo Using Intracardiac Myocardial Elastography

Radio frequency (RF) ablation of the myocardium is used to treat various cardiac arrhythmias. The size, spacing, and transmurality of lesions have been shown to affect the success of the ablation procedure; however, there is currently no method to directly image the size and formation of ablation lesions in real time. Intracardiac myocardial elastography (ME) has been previously used to image the decrease in cardiac strain during systole in the ablated region as a result of the lesion formation. However, the feasibility of imaging multiple lesions and identifying the presence of gaps between lesions has not yet been investigated. In this paper, RF ablation lesions ( ) were generated in the left ventricular epicardium in three anesthetized canines. Two sets of two lesions each were created in close proximity to one another with small gaps (1.5 and 4 cm), while one set of two lesions was created directly next to each other with no gap. A clinical intracardiac echocardiography system was programmed to transmit a custom diverging beam sequence at 600 Hz and used to image the ablation site before and after the induction of ablation lesions. Cumulative strains were estimated over systole using a normalized cross-correlational displacement algorithm and a least-squares strain kernel. Afterward, lesions were excised and subjected to tetrazolium chloride staining. Results indicate that intracardiac ME was capable of imaging the reduction in systolic strain associated with the formation of an ablation lesion. Furthermore, lesion sets containing gaps were able to be distinguished from lesion sets created with no gaps. These results indicate that the end-systolic strain measured using intracardiac ME may be used to image the formation of lesions induced during an RF ablation procedure, in order to provide critical assessment of lesion viability during the interventional procedure.

Reproducibility and Angle Independence of Electromechanical Wave Imaging for the Measurement of Electromechanical Activation during Sinus Rhythm in Healthy Humans

Electromechanical wave imaging (EWI) is an ultrasound-based technique that can non-invasively map the transmural electromechanical activation in all four cardiac chambers in vivo. The objective of this study was to determine the reproducibility and angle independence of EWI for the assessment of electromechanical activation during normal sinus rhythm (NSR) in healthy humans. Acquisitions were performed transthoracically at 2000 frames/s on seven healthy human hearts in parasternal long-axis, apical four- and two-chamber views. EWI data was collected twice successively in each view in all subjects, while four successive acquisitions were obtained in one case. Activation maps were generated and compared (i) within the same acquisition across consecutive cardiac cycles; (ii) within same view across successive acquisitions; and (iii) within equivalent left-ventricular regions across different views. EWI was capable of characterizing electromechanical activation during NSR and of reliably obtaining similar patterns of activation. For consecutive heart cycles, the average 2-D correlation coefficient between the two isochrones across the seven subjects was 0.9893, with a mean average activation time fluctuation in LV wall segments across acquisitions of 6.19%. A mean activation time variability of 12% was obtained across different views with a measurement bias of only 3.2 ms. These findings indicate that EWI can map the electromechanical activation during NSR in human hearts in transthoracic echocardiography in vivo and results in reproducible and angle-independent activation maps.

Feasibility and Validation of 4-D Pulse Wave Imaging in Phantoms and In Vivo

Pulse wave imaging (PWI) is a noninvasive technique for tracking the propagation of the pulse wave along the arterial wall. The 3-D ultrasound imaging would aid in objectively estimating the pulse wave velocity (PWV) vector. This paper aims to introduce a novel PWV estimation method along the propagation direction, validate it in phantoms, and test its feasibility in vivo. A silicone vessel phantom consisting of a stiff and a soft segment along the longitudinal axis and a silicone vessel with a plaque were constructed. A 2-D array with a center frequency of 2.5 MHz was used. Propagation was successfully visualized in 3-D in each phantom and in vivo in six healthy subjects. In three of the healthy subjects, results were compared against conventional PWI using a linear array. PWVs were estimated in the stiff (3.42 ± 0.23 m [Formula: see text]) and soft (2.41 ± 0.07 m [Formula: see text]) phantom segments. Good agreement was found with the corresponding static testing values (stiff: 3.41 m [Formula: see text] and soft: 2.48 m [Formula: see text]). PWI-derived vessel compliance values were validated with dynamic testing. Comprehensive views of pulse propagation in the plaque phantom were generated and compared against conventional PWI acquisitions. Good agreement was found in vivo between the results of 4-D PWI (4.80 ± 1.32 m [Formula: see text]) and conventional PWI (4.28±1.20 m [Formula: see text]) ( n=3 ). PWVs derived for all of the healthy subjects ( n = 6 ) were within the physiological range. Thus, the 4-D PWI was successfully validated in phantoms and used to image the pulse wave propagation in normal human subjects in vivo.