Comparison of cardiac displacement and strain imaging using ultrasound radiofrequency and envelope signals

Preliminary Feasibility of Stress Myocardial Elastography for the Detection of Coronary Artery Disease

Myocardial elastography (ME) is a cardiac strain imaging technique that has been found capable of detecting a decrease in radial strain caused by ischemia or infarction in patients with coronary artery disease (CAD) as well as in a canine model. Prior studies have focused on rest imaging, but stress testing can reveal functional deficits caused by stenoses that are asymptomatic at rest. Therefore, it has been proposed that stress ME (S-ME) improves the detection of CAD. A novel strain difference (Δε) metric is presented and investigated in a canine model of induced ischemia, as well as in a study in human patients with CAD validated by myocardial perfusion imaging. In the canine model study, flow-limiting stenosis was induced by partial ligation in n = 2 canines, and stenosis was found to consistently reduce Δε in the affected myocardial regions compared with baseline, as well as compared to myocardial regions that are remote to the induced stenosis. In the clinical study, the median Δε was significantly lower (p < 0.05) in infarcted myocardial regions (-6.29%) than in those with normal perfusion (4.62%), with Δε in ischemic regions falling in between (-2.91%). The same trend was observed when considering radial strain during stress and, to a lesser degree, at rest alone. The results indicate that S-ME may be more sensitive to mild cases of CAD that are functionally asymptomatic at rest.

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.

Ultrafast Myocardial Principal Strain Ultrasound Elastography During Stress Tests: In Vitro Validation and In Vivo Feasibility

Objective myocardial contractility assessment during stress tests aims to improve the diagnosis of myocardial ischemia. Tissue Doppler imaging (TDI) or optical flow (OF) speckle tracking echocardiography (STE) has been used to quantify myocardial contractility at rest. However, this is more challenging during stress tests due to image decorrelation at high heart rates. Moreover, stress tests imply a high frame rate which leads to a limited lateral field of view. Therefore, a large lateral field-of-view robust ultrafast myocardial regularized OF-TDI principal strain estimator has been developed for high-frame-rate echocardiography of coherently compounded transmitted diverging waves. The feasibility and accuracy of the proposed estimator were validated in vitro (using sonomicrometry as the gold standard) and in vivo stress experiments. Compared with OF strain imaging, the proposed estimator improved the accuracy of principal major and minor strains during stress tests, with an average contrast-to-noise ratio improvement of 4.4 ± 2.7 dB ( p -value < 0.01). Moreover, there was a significant correlation and a very close agreement between the proposed estimator and sonomicrometry for tested heart rates between 60 and 180 beats per minute (bpm). The averages ± standard deviations (STD) of R² and biases ± STD between them were 0.96 ± 0.04 ( p -value < 0.01) and 0.01 ± 0.03% in the axial direction, respectively; and 0.94 ± 0.02 ( p -value < 0.01) and 0.04 ± 0.06% in the lateral direction, respectively. These results suggest that the proposed estimator could be useful clinically to provide an accurate and quantitative 2-D large lateral field-of-view myocardial strain assessment at high heart rates during stress echocardiography.

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).

Myocardial Strain Imaging With Electrocardiogram-Gated and Coherent Compounding for Early Diagnosis of Coronary Artery Disease

Myocardial elastography (ME) is an ultrasound-based technique that uses radiofrequency signals for 2-D cardiac motion tracking and strain imaging at a high frame rate. Early diagnosis of coronary artery disease (CAD) is critical for timely treatment and improvement of patient outcome. The objective of this study was to assess the performance of ME radial and circumferential strains in the detection and characterization of CAD in patients. In this study, 86 patients suspected of CAD were imaged with ME prior to invasive coronary angiography (ICA). End-systolic radial and circumferential left ventricular strains were estimated in all patients in each of their perfusion territories: left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA). ME radial strains were capable of differentiating the obstructive CAD group (55.3 ± 29.8%) from the non-obstructive CAD (72.5 ± 46.8%, p < 0.05) and no CAD groups (73.4 ± 30.4%, p < 0.05) in the RCA territory. ME circumferential strains were capable of differentiating the obstructive CAD group (-3.1 ± 7.5%) from the non-obstructive CAD (-7.2 ± 6.8%, p < 0.05) and normal (-6.9 ± 8.0%, p < 0.05) groups in the LAD territory and to differentiate the normal group (-17.1 ± 8.2%) from the obstructive (-12.8 ± 7.2%, p < 0.05) and non-obstructive CAD (-13.6 ± 8.5%, p < 0.05) groups in the RCA territory. ME circumferential strain performed better than ME radial strain in differentiating normal, non-obstructive and obstructive perfusion territories. In the LCX territory, both ME radial and circumferential strains decreased when the level of stenosis was higher. However, it was not statistically significant. The findings presented herein indicate that ME radial and circumferential estimation obtained from ECG-gated and compounded acquisitions is a promising tool for early, non-invasive and radiation-free detection of CAD in patients.

Spatiotemporal Bayesian Regularization for Cardiac Strain Imaging: Simulation and In Vivo Results

Cardiac strain imaging (CSI) plays a critical role in the detection of myocardial motion abnormalities. Displacement estimation is an important processing step to ensure the accuracy and precision of derived strain tensors. In this paper, we propose and implement Spatiotemporal Bayesian regularization (STBR) algorithms for two-dimensional (2-D) normalized cross-correlation (NCC) based multi-level block matching along with incorporation into a Lagrangian cardiac strain estimation framework. Assuming smooth temporal variation over a short span of time, the proposed STBR algorithm performs displacement estimation using at least four consecutive ultrasound radio-frequency (RF) frames by iteratively regularizing 2-D NCC matrices using information from a local spatiotemporal neighborhood in a Bayesian sense. Two STBR schemes are proposed to construct Bayesian likelihood functions termed as Spatial then Temporal Bayesian (STBR-1) and simultaneous Spatiotemporal Bayesian (STBR-2). Radial and longitudinal strain estimated from a finite-element-analysis (FEA) model of realistic canine myocardial deformation were utilized to quantify strain bias, normalized strain error and total temporal relative error (TTR). Statistical analysis with one-way analysis of variance (ANOVA) showed that all Bayesian regularization methods significantly outperform NCC with lower bias and errors (p < 0.001). However, there was no significant difference among Bayesian methods. For example, mean longitudinal TTR for NCC, SBR, STBR-1 and STBR-2 were 25.41%, 9.27%, 10.38% and 10.13% respectively An in vivo feasibility study using RF data from ten healthy mice hearts were used to compare the elastographic signal-to-noise ratio (SNR_e) calculated using stochastic analysis. STBR-2 had the highest expected SNR_e both for radial and longitudinal strain. The mean expected SNR_e values for accumulated radial strain for NCC, SBR, STBR-1 and STBR-2 were 5.03, 9.43, 9.42 and 10.58, respectively. Overall results suggest that STBR improves CSI in vivo.

Monitoring Canine Myocardial Infarction Formation and Recovery via Transthoracic Cardiac Strain Imaging

Myocardial elastography (ME) is an ultrasound-based strain imaging method that aims to determine the degree of ischemia or infarction as a result of the change in the elastic properties of the myocardium. A survival canine model (n = 11) was employed to investigate the ability of ME to image myocardial infarction formation and recovery. Infarcts were generated by ligation of the left anterior descending coronary artery. Canines were survived and imaged for 4 days (n = 7) or 4 weeks (n = 4), allowing sufficient time for recovery via collateral perfusion. A radial strain-based metric, percentage of healthy myocardium by strain (PHMε), was developed as a marker for healthy myocardial tissue. PHMε was strongly linearly correlated with actual infarct size as determined by gross pathology (R2 = 0.80). Mean PHMε was reduced 1-3 days post-infarction (p < 0.05) at the papillary and apical short-axis levels; full infarct recovery was achieved by day 28, with mean PHMε returning to baseline levels. ME was capable of diagnosing individual myocardial segments as non-infarcted or infarcted with high sensitivity (82%), specificity (92%) and precision (85%) (area under the receiver operating characteristic curve = 0.90). The study therefore strengthens the ME premise that it can detect and assess myocardial infarction progression and recovery in vivo and could thus provide an important role in both disease diagnosis and treatment assesssment.

Catheter Ablation Lesion Visualization With Intracardiac Strain Imaging in Canines and Humans

Catheter ablation is a common treatment for arrhythmia, but can fail if lesion lines are noncontiguous. Identification of gaps and nontransmural lesions can reduce the likelihood of treatment failure and recurrent arrhythmia. Intracardiac myocardial elastography (IME) is a strain imaging technique that provides visualization of the lesion line. Estimation of lesion size and gap resolution were evaluated in an open-chest canine model ( n = 3 ), and clinical feasibility was investigated in patients undergoing ablation to treat typical cavotricuspid isthmus (CTI) atrial flutter ( n = 5 ). A lesion line consisting of three lesions and two gaps was generated on the canine left ventricle via epicardial ablation. One lesion was generated in one canine right ventricle. Average lesion and gap areas were measured with high agreement (33 ± 14 and 30 ± 15 mm², respectively) when compared against gross pathology (34 ± 19 and 26 ± 11 mm², respectively). Gaps as small as 11 mm² (3.6 mm on epicardial surface) were identifiable. Absolute error and relative error in estimated lesion area were 9.3 ± 8.4 mm² and 31% ± 34%; error in estimated gap area was 11 ± 9.0 mm² and 40% ± 29%. Flutter patients were imaged throughout the procedure. Strain was shown to be capable of differentiating between baseline and after ablation completion as confirmed by conduction block. In all patients, strain decreased in the CTI after ablation (mean paired difference of -17% ± 11%, ). IME could potentially become a useful ablation monitoring tool in health facilities.

Motion synchronisation patterns of the carotid atheromatous plaque from B-mode ultrasound

Asynchronous movement of the carotid atheromatous plaque from B-mode ultrasound has been previously reported, and associated with higher risk of stroke, but not quantitatively estimated. Based on the hypothesis that asynchronous plaque motion is associated with vulnerable plaque, in this study, synchronisation patterns of different tissue areas were estimated using cross-correlations of displacement waveforms. In 135 plaques (77 subjects), plaque radial deformation was synchronised by approximately 50% with the arterial diameter, and the mean phase shift was 0.4 s. Within the plaque, the mean phase shifts between the displacements of the top and bottom surfaces were 0.2 s and 0.3 s, in the radial and longitudinal directions, respectively, and the synchronisation about 80% in both directions. Classification of phase-shift-based features using Random Forests yielded Area-Under-the-Curve scores of 0.81, 0.79, 0.89 and 0.90 for echogenicity, symptomaticity, stenosis degree and plaque risk, respectively. Statistical analysis showed that echolucent, high-stenosis and high-risk plaques exhibited higher phase shifts between the radial displacements of their top and bottom surfaces. These findings are useful in the study of plaque kinematics.

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.

2D myocardial deformation imaging based on RF-based non-rigid image registration

Myocardial deformation imaging is a well-established echocardiographic technique for the assessment of myocardial function. Although some solutions make use of speckle tracking of the reconstructed B-mode images, others apply block matching on the underlying radio-frequency (RF) data in order to increase sensitivity to small inter-frame motion and deformation. However, for both approaches, lateral motion estimation remains a challenge due to the relatively poor lateral resolution of the ultrasound image in combination with the lack of phase information in this direction. Hereto, non-rigid image registration (NRIR) of B-mode images has previously been proposed as an attractive solution. However, hereby, the advantages of RF-based tracking were lost. The aim of this study was therefore to develop an NRIR motion estimator adopted to RF data sets. The accuracy of this estimator was quantified using synthetic data and was contrasted against a state of the art block matching solution. The results show that RF-based NRIR outperforms BM in terms of tracking accuracy particularly, as hypothesized, in the lateral direction. Finally, this RF-based NRIR algorithm was applied clinically, illustrating its ability to estimate both in-plane velocity components in-vivo.

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.

Ultrasound functional imaging in an ex vivo beating porcine heart platform

In recent years, novel ultrasound functional imaging (UFI) techniques have been introduced to assess cardiac function by measuring, e.g. cardiac output (CO) and/or myocardial strain. Verification and reproducibility assessment in a realistic setting remain major issues. Simulations and phantoms are often unrealistic, whereas in vivo measurements often lack crucial hemodynamic parameters or ground truth data, or suffer from the large physiological and clinical variation between patients when attempting clinical validation. Controlled validation in certain pathologies is cumbersome and often requires the use of lab animals. In this study, an isolated beating pig heart setup was adapted and used for performance assessment of UFI techniques such as volume assessment and ultrasound strain imaging. The potential of performing verification and reproducibility studies was demonstrated. For proof-of-principle, validation of UFI in pathological hearts was examined. Ex vivo porcine hearts (n  =  6, slaughterhouse waste) were resuscitated and attached to a mock circulatory system. Radio frequency ultrasound data of the left ventricle were acquired in five short axis views and one long axis view. Based on these slices, the CO was measured, where verification was performed using flow sensor measurements in the aorta. Strain imaging was performed providing radial, circumferential and longitudinal strain to assess reproducibility and inter-subject variability under steady conditions. Finally, strains in healthy hearts were compared to a heart with an implanted left ventricular assist device, simulating a failing, supported heart. Good agreement between ultrasound and flow sensor based CO measurements was found. Strains were highly reproducible (intraclass correlation coefficients  >0.8). Differences were found due to biological variation and condition of the hearts. Strain magnitude and patterns in the assisted heart were available for different pump action, revealing large changes compared to the normal condition. The setup provides a valuable benchmarking platform for UFI techniques. Future studies will include work on different pathologies and other means of measurement verification.

Feasibility and relevance of compound strain imaging in non-stenotic arteries: comparison between individuals with cardiovascular diseases and healthy controls

BACKGROUND

Compound strain imaging is a novel method to noninvasively evaluate arterial wall deformation which has recently shown to enable differentiation between fibrous and (fibro-)atheromatous plaques in patients with severe stenosis. We tested the hypothesis that compound strain imaging is feasible in non-stenotic arteries and provides incremental discriminative power to traditional measures of vascular health (i.e., distensibility coefficient (DC), central pulse wave velocity [cPWV], and intima-media thickness [IMT]) for differentiating between participants with and without a history of cardiovascular diseases (CVD).

METHODS

Seventy two participants (60 ± 7 years) with non-stenotic arteries (IMT < 1.1 mm) were categorized in healthy participants (CON, n = 36) and CVD patients (n = 36) based on CVD history. Participants underwent standardised ultrasound-based assessment (DC, cPWV, and IMT) and compound strain imaging (radial [RS] and circumferential [CS] strain) in left common carotid artery. Area under receiver operating characteristics (AROC)-curve was used to determine the discriminatory power between CVD and CON of the various measures.

RESULTS

CON had a significantly (P < 0.05) smaller carotid IMT (0.68 [0.58 to 0.76] mm) than CVD patients (0.76 [0.68 to 0.80] mm). DC, cPWV, RS, and CS did not significantly differ between groups (P > 0.05). A higher CS or RS was associated with a higher DC (CS: r = -0.32;p < 0.05 and RS: r = 0.24;p < 0.05) and lower cPWV (CS: r = 0.24;p < 0.05 and RS: r = -0.25;p < 0.05). IMT could identify CVD (AROC: 0.66, 95%-CI: 0.53 to 0.79), whilst the other measurements, alone or in combination, did not significantly increase the discriminatory power compared to IMT.

CONCLUSIONS

In non-stenotic arteries, compound strain imaging is feasible, but does not seem to provide incremental discriminative power to traditional measures of vascular health for differentiation between individuals with and without a history of CVD.

Evaluation of Coronary Artery Disease Using Myocardial Elastography with Diverging Wave Imaging: Validation against Myocardial Perfusion Imaging and Coronary Angiography

Myocardial elastography (ME) is an ultrasound-based technique that can image 2-D myocardial strains. The objectives of this study were to illustrate that 2-D myocardial strains can be imaged with diverging wave imaging and differ, on average, between normal and coronary artery disease (CAD) patients. In this study, 66 patients with symptoms of CAD were imaged with myocardial elastography before a nuclear stress test or an invasive coronary angiography. Radial cumulative strains were estimated in all patients. The end-systolic radial strain in the total cross section of the myocardium was significantly higher in normal patients (17.9 ± 8.7%) than in patients with reversible perfusion defect (6.2 ± 9.3%, p < 0.001) and patients with significant (-0.9 ± 7.4%, p < 0.001) and non-significant (3.7 ± 5.7%, p < 0.01) lesions. End-systolic radial strain in the left anterior descending, left circumflex and right coronary artery territory was found to be significantly higher in normal patients than in CAD patients. These preliminary findings indicate that end-systolic radial strain measured with ME is higher on average in healthy persons than in CAD patients and that ME has the potential to be used for non-invasive, radiation-free early detection of CAD.

3D Myocardial Elastography In Vivo

Strain evaluation is of major interest in clinical cardiology as it can quantify the cardiac function. Myocardial elastography, a radio-frequency (RF)-based cross-correlation method, has been developed to evaluate the local strain distribution in the heart in vivo. However, inhomogeneities such as RF ablation lesions or infarction require a three-dimensional approach to be measured accurately. In addition, acquisitions at high volume rate are essential to evaluate the cardiac strain in three dimensions. Conventional focused transmit schemes using 2D matrix arrays, trade off sufficient volume rate for beam density or sector size to image rapid moving structure such as the heart, which lowers accuracy and precision in the strain estimation. In this study, we developed 3D myocardial elastography at high volume rates using diverging wave transmits to evaluate the local axial strain distribution in three dimensions in three open-chest canines before and after radio-frequency ablation. Acquisitions were performed with a 2.5 MHz 2D matrix array fully programmable used to emit 2000 diverging waves at 2000 volumes/s. Incremental displacements and strains enabled the visualization of rapid events during the QRS complex along with the different phases of the cardiac cycle in entire volumes. Cumulative displacement and strain volumes depict high contrast between non-ablated and ablated myocardium at the lesion location, mapping the tissue coagulation. 3D myocardial strain elastography could thus become an important technique to measure the regional strain distribution in three dimensions in humans.

Imaging the Propagation of the Electromechanical Wave in Heart Failure Patients with Cardiac Resynchronization Therapy

BACKGROUND

Current electrocardiographic and echocardiographic measurements in heart failure (HF) do not take into account the complex interplay between electrical activation and local wall motion. The utilization of novel technologies to better characterize cardiac electromechanical behavior may lead to improved response rates with cardiac resynchronization therapy (CRT). Electromechanical wave imaging (EWI) is a noninvasive ultrasound-based technique that uses the transient deformations of the myocardium to track the intrinsic EW that precedes myocardial contraction. In this paper, we investigate the performance and reproducibility of EWI in the assessment of HF patients and CRT.

METHODS

EWI acquisitions were obtained in five healthy controls and 16 HF patients with and without CRT pacing. Responders (n = 8) and nonresponders (n = 8) to CRT were identified retrospectively on the basis of left ventricular (LV) reverse remodeling. Electromechanical activation maps were obtained in all patients and used to compute a quantitative parameter describing the mean LV lateral wall activation time (LWAT).

RESULTS

Mean LWAT was increased by 52.1 ms in HF patients in native rhythm compared to controls (P < 0.01). For all HF patients, CRT pacing initiated a different electromechanical activation sequence. Responders exhibited a 56.4-ms ± 28.9-ms reduction in LWAT with CRT pacing (P < 0.01), while nonresponders showed no significant change.

CONCLUSION

In this initial feasibility study, EWI was capable of characterizing local cardiac electromechanical behavior as it pertains to HF and CRT response. Activation sequences obtained with EWI allow for quantification of LV lateral wall electromechanical activation, thus providing a novel method for CRT assessment.

Segmental Analysis of Cardiac Short-Axis Views Using Lagrangian Radial and Circumferential Strain

Accurate description of myocardial deformation in the left ventricle is a three-dimensional problem, requiring three normal strain components along its natural axis, that is, longitudinal, radial, and circumferential strains. Although longitudinal strains are best estimated from long-axis views, radial and circumferential strains are best depicted in short-axis views. An algorithm that utilizes a polar grid for short-axis views previously developed in our laboratory for a Lagrangian description of tissue deformation is utilized for radial and circumferential displacement and strain estimation. Deformation of the myocardial wall, utilizing numerical simulations with ANSYS, and a finite-element analysis-based canine heart model were adapted as the input to a frequency-domain ultrasound simulation program to generate radiofrequency echo signals. Clinical in vivo data were also acquired from a healthy volunteer. Local displacements estimated along and perpendicular to the ultrasound beam propagation direction are then transformed into radial and circumferential displacements and strains using the polar grid based on a pre-determined centroid location. Lagrangian strain variations demonstrate good agreement with the ideal strain when compared with Eulerian results. Lagrangian radial and circumferential strain estimation results are also demonstrated for experimental data on a healthy volunteer. Lagrangian radial and circumferential strain tracking provide accurate results with the assistance of the polar grid, as demonstrated using both numerical simulations and in vivo study.

Systematic Performance Evaluation of a Cross-Correlation-Based Ultrasound Strain Imaging Method

Estimation of tissue motion in the lateral direction remains a major challenge in 2-D ultrasound strain imaging (USI). Although various methodologies have been proposed to improve the accuracy of estimation of in-plane displacements and strains, the fundamental limitations of 2-D USI and how to choose optimal algorithmic parameters in various tissue deformation paradigms to retrieve the full strain tensor of acceptable accuracy are scattered throughout the literature. Thus, this study attempts to provide a systematic investigation of a 2-D cross-correlation-based USI method in a theoretical framework. Our previously developed cross-correlation-based USI method was revisited, and additional estimation strategies were incorporated to improve in-plane displacement and strain estimation. The performance of the presented method using different matching kernel sizes (axial: from 1λ to 14λ, where λ = wavelength; lateral: from 1 to 13 pitches) and two data formats (radiofrequency and envelope) in various kinematic scenarios (normal, shear or hybrid deformation) was investigated using Field II simulations, in which coherent plane wave compounding with 64 steered angles was realized. For radiofrequency-based USI, smaller axial and larger lateral kernel sizes were preferred in scenarios with normal strains, whereas larger kernel sizes along the shearing direction and smaller ones orthogonal to the shearing direction were more suitable in scenarios with shear strains. For envelope-based USI, in contrast, the kernel size requirement was relatively relaxed. A compromise between optimal kernel sizes and estimation accuracy of various strain components was required in complex kinematic scenarios. These practical strategies for accurate motion estimation using 2-D cross-correlation-based USI were further tested in a tissue-mimicking phantom under quasi-static compression and in a preliminary in vivo examination of a normal human median nerve at the wrist during active finger motion.

Postprocessing Approaches for the Improvement of Cardiac Ultrasound B-Mode Images: A Review

The improvement in the quality and diagnostic value of ultrasound images has been an ongoing research theme for the last three decades. Cardiac ultrasound suffers from a wide range of artifacts such as acoustic noise, shadowing, and enhancement. Most artifacts are a consequence of the interaction of the transmitted ultrasound signals with anatomic structures of the examined body. Structures such as bone, lungs (air), and fat have a direct limiting effect on the quality of the acquired images. Furthermore, physical phenomena such as speckle introduce a granular pattern on the imaged tissue structures that can sometimes obscure fine anatomic detail. Over the years, numerous studies have attempted to address a range of artifacts in medical ultrasound, including cardiac ultrasound B-mode images. This review provides extensive coverage of such attempts identifying their limitations as well as future research opportunities.

Performance comparison of rigid and affine models for motion estimation using ultrasound radio-frequency signals

Tissue motion estimation is widely used in many ultrasound techniques. Rigid-model-based and nonrigid-modelbased methods are two main groups of space-domain methods of tissue motion estimation. The affine model is one of the commonly used nonrigid models. The performances of the rigid model and affine model have not been compared on ultrasound RF signals, which have been demonstrated to obtain higher accuracy, precision, and resolution in motion estimation compared with B-mode images. In this study, three methods, i.e., the normalized cross-correlation method with rigid model (NCC), the optical flow method with rigid model (OFRM), and the optical flow method with affine model (OFAM), are compared using ultrasound RF signals, rather than the B-mode images used in previous studies. Simulations, phantom, and in vivo experiments are conducted to make the comparison. In the simulations, the root-mean-square errors (RMSEs) of axial and lateral displacements and strains are used to assess the accuracy of motion estimation, and the elastographic signal-tonoise ratio (SNRe) and contrast-to-noise ratio (CNRe) are used to evaluate the quality of axial strain images. In the phantom experiments, the registration error between the pre- and postdeformation RF signals, as well as the SNRe and CNRe of axial strain images, are utilized as the evaluation criteria. In the in vivo experiments, the registration error is used to evaluate the estimation performance. The results show that the affinemodel- based method (i.e., OFAM) obtains the lowest RMSE or registration error and the highest SNRe and CNRe among all the methods. The affine model is demonstrated to be superior to the rigid model in motion estimation based on RF signals.

Intracardiac myocardial elastography in canines and humans in vivo

Intracardiac echocardiography (ICE) is a useful imaging modality which is used during RF ablation procedures to identify anatomical structures. Utilizing ICE in conjunction with myocardial elastography (ME) can provide additional information on the mechanical properties of cardiac tissue and provide information on mechanical changes caused by ablation. The objective of this study was to demonstrate that ICE can be used at high frame rate using a diverging beam transmit sequence to image myocardial strain and differentiate myocardial tissue properties before, during, and after ablation for a clinical ablation procedure. In this feasibility study, three normal canines and eight patients with atrial fibrillation (AF) were studied in vivo. A 5.8-MHz ICE transducer was used to image the heart with a diverging beam transmit method achieving 1200 frames per second (fps). Cumulative axial displacement estimation was performed using 1-D cross-correlation with a window size of 2.7 mm and 95% overlap. Axial cumulative strains were estimated in the left atrium (LA) and right atrium (RA) using a least-squares estimator with a kernel of 2 mm on the axial displacements. In the canine case, radial thickening was detected in the lateral wall and in the interatrial septum during LA emptying. For AF patients, the mean absolute strain in the ablated region was lower (6.7 ± 3.1%) than before the ablation (17.4 ± 9.3%) in LA at the end of the LA emptying phase. In the cavotricuspid isthmus (CTI) region, mean absolute strain magnitude at the end of the RA emptying phase was found to be higher during ablation (43.0 ± 18.1%) compared with after ablation (33.7 ± 15.8%). Myocardial strains in the LA of an AF patient were approximately 2.6 times lower in the ablated region than before ablation. This initial feasibility indicates that ME can be used as a new imaging modality in conjunction with ICE in RF ablation guidance and lesion monitoring.

Stochastic precision analysis of 2D cardiac strain estimation in vivo

Ultrasonic strain imaging has been applied to echocardiography and carries great potential to be used as a tool in the clinical setting. Two-dimensional (2D) strain estimation may be useful when studying the heart due to the complex, 3D deformation of the cardiac tissue. Increasing the framerate used for motion estimation, i.e. motion estimation rate (MER), has been shown to improve the precision of the strain estimation, although maintaining the spatial resolution necessary to view the entire heart structure in a single heartbeat remains challenging at high MERs. Two previously developed methods, the temporally unequispaced acquisition sequence (TUAS) and the diverging beam sequence (DBS), have been used in the past to successfully estimate in vivo axial strain at high MERs without compromising spatial resolution. In this study, a stochastic assessment of 2D strain estimation precision is performed in vivo for both sequences at varying MERs (65, 272, 544, 815 Hz for TUAS; 250, 500, 1000, 2000 Hz for DBS). 2D incremental strains were estimated during left ventricular contraction in five healthy volunteers using a normalized cross-correlation function and a least-squares strain estimator. Both sequences were shown capable of estimating 2D incremental strains in vivo. The conditional expected value of the elastographic signal-to-noise ratio (E(SNRe|ε)) was used to compare strain estimation precision of both sequences at multiple MERs over a wide range of clinical strain values. The results here indicate that axial strain estimation precision is much more dependent on MER than lateral strain estimation, while lateral estimation is more affected by strain magnitude. MER should be increased at least above 544 Hz to avoid suboptimal axial strain estimation. Radial and circumferential strain estimations were influenced by the axial and lateral strain in different ways. Furthermore, the TUAS and DBS were found to be of comparable precision at similar MERs.

Analysis of 2-d ultrasound cardiac strain imaging using joint probability density functions

Ultrasound frame rates play a key role for accurate cardiac deformation tracking. Insufficient frame rates lead to an increase in signal de-correlation artifacts resulting in erroneous displacement and strain estimation. Joint probability density distributions generated from estimated axial strain and its associated signal-to-noise ratio provide a useful approach to assess the minimum frame rate requirements. Previous reports have demonstrated that bi-modal distributions in the joint probability density indicate inaccurate strain estimation over a cardiac cycle. In this study, we utilize similar analysis to evaluate a 2-D multi-level displacement tracking and strain estimation algorithm for cardiac strain imaging. The effect of different frame rates, final kernel dimensions and a comparison of radio frequency and envelope based processing are evaluated using echo signals derived from a 3-D finite element cardiac model and five healthy volunteers. Cardiac simulation model analysis demonstrates that the minimum frame rates required to obtain accurate joint probability distributions for the signal-to-noise ratio and strain, for a final kernel dimension of 1 λ by 3 A-lines, was around 42 Hz for radio frequency signals. On the other hand, even a frame rate of 250 Hz with envelope signals did not replicate the ideal joint probability distribution. For the volunteer study, clinical data was acquired only at a 34 Hz frame rate, which appears to be sufficient for radio frequency analysis. We also show that an increase in the final kernel dimensions significantly affect the strain probability distribution and joint probability density function generated, with a smaller effect on the variation in the accumulated mean strain estimated over a cardiac cycle. Our results demonstrate that radio frequency frame rates currently achievable on clinical cardiac ultrasound systems are sufficient for accurate analysis of the strain probability distribution, when a multi-level 2-D algorithm and kernel dimensions on the order of 1 λ by 3 A-lines or smaller are utilized.

Radial basis functions for combining shape and speckle tracking in 4D echocardiography

Quantitative analysis of left ventricular deformation can provide valuable information about the extent of disease as well as the efficacy of treatment. In this work, we develop an adaptive multi-level compactly supported radial basis approach for deformation analysis in 3D+time echocardiography. Our method combines displacement information from shape tracking of myocardial boundaries (derived from B-mode data) with mid-wall displacements from radio-frequency-based ultrasound speckle tracking. We evaluate our methods on open-chest canines (N=8) and show that our combined approach is better correlated to magnetic resonance tagging-derived strains than either individual method. We also are able to identify regions of myocardial infarction (confirmed by postmortem analysis) using radial strain values obtained with our approach.

Non-invasive vascular radial/circumferential strain imaging and wall shear rate estimation using video images of diagnostic ultrasound

The aim of this work was to develop a convenient method for radial/circumferential strain imaging and shear rate estimation that could be used as a supplement to the current routine screening for carotid atherosclerosis using video images of diagnostic ultrasound. A reflection model-based correction for gray-scale non-uniform distribution was applied to B-mode video images before strain estimation to improve the accuracy of radial/circumferential strain imaging when applied to vessel transverse cross sections. The incremental and cumulative radial/circumferential strain images can then be calculated based on the displacement field between consecutive B-mode images. Finally, the transverse Doppler spectra acquired at different depths along the vessel diameter were used to construct the spatially matched instantaneous wall shear values in a cardiac cycle. Vessel phantom simulation results revealed that the signal-to-noise ratio and contrast-to-noise ratio of the radial and circumferential strain images were increased by 2.8 and 5.9 dB and by 2.3 and 4.4 dB, respectively, after non-uniform correction. Preliminary results for 17 patients indicated that the accuracy of radial/circumferential strain images was improved in the lateral direction after non-uniform correction. The peak-to-peak value of incremental strain and the maximum cumulative strain for calcified plaques are evidently lower than those for other plaque types, and the echolucent plaques had higher values, on average, than the mixed plaques. Moreover, low oscillating wall shear rate values, found near the plaque and stenosis regions, are closely related to plaque formation. In conclusion, the method described can provide additional valuable results as a supplement to the current routine ultrasound examination for carotid atherosclerosis and, therefore, has significant potential as a feasible screening method for atherosclerosis diagnosis in the future.