Acoustic Radiation Force Impulse Displacement Research Articles

Quantitative multiparametric ultrasound for prostate cancer targeted biopsy

Prostate cancer (PCa) is conventionally diagnosed using transrectal ultrasound (TRUS) guided biopsy. B-mode ultrasound is used to direct the biopsy needle to regions of the prostate gland, but is not used to target cancer-suspicious regions due to its low specificity for PCa. We are developing multiparametric quantitative ultrasound imaging approaches to facilitate targeting ultrasound-guided biopsies toward regions suspicious for PCa. To identify PCa during TRUS imaging, we combine information from four ultrasonic techniques: acoustic radiation force impulse (ARFI) imaging, shear wave elasticity imaging (SWEI), quantitative ultrasound (QUS) and B-mode ultrasound. 3-D co-registered in vivo ultrasound data, and MRI T2-weighted and ADC data volumes have been acquired from 30 patients prior to radical prostatectomy, obtaining estimates of ARFI displacement, shear wave speed, QUS midband fit, B-mode brightness, T2 intensity, and ADC values. In each data volume, healthy and cancerous regions were manually segmented with guidance from whole mount histology; the intersection of the cancerous segmentations from all modalities was labeled as the ground truth. We will present a range of classification approaches, including LDA and SVM, to combine information from each modality in order to develop automated tools for targeted biopsy.Prostate cancer (PCa) is conventionally diagnosed using transrectal ultrasound (TRUS) guided biopsy. B-mode ultrasound is used to direct the biopsy needle to regions of the prostate gland, but is not used to target cancer-suspicious regions due to its low specificity for PCa. We are developing multiparametric quantitative ultrasound imaging approaches to facilitate targeting ultrasound-guided biopsies toward regions suspicious for PCa. To identify PCa during TRUS imaging, we combine information from four ultrasonic techniques: acoustic radiation force impulse (ARFI) imaging, shear wave elasticity imaging (SWEI), quantitative ultrasound (QUS) and B-mode ultrasound. 3-D co-registered in vivo ultrasound data, and MRI T2-weighted and ADC data volumes have been acquired from 30 patients prior to radical prostatectomy, obtaining estimates of ARFI displacement, shear wave speed, QUS midband fit, B-mode brightness, T2 intensity, and ADC values. In each data volume, healthy and cancerous regions were manually segm...

Scanned 3-D Intracardiac ARFI and SWEI for Imaging Radio-Frequency Ablation Lesions.

Radio-frequency ablation (RFA) is used to locally disrupt electrical propagation in myocardium and treat arrhythmias, and direct visualization of ablation lesions by acoustic radiation force methods may benefit RFA procedures. This paper compares four imaging modalities, B-mode, acoustic radiation force impulse (ARFI), single-track-location shear wave elasticity imaging (STL-SWEI), and multiple-track-location shear wave elasticity imaging (MTL-SWEI), in their ability to resolve RFA lesions in four ex vivo experiments. Ablation lesions are shown to be marked by at least a local halving of ARFI displacements and doubling of shear wave speeds. In a controlled ablation of ex vivo porcine and canine cardiac tissue, STL-SWEI and ARFI are shown to have a similar CNR, better than MTL-SWEI and B-mode. The SWEI modalities are demonstrated to have improved imaging of distal lesion boundaries. Gaps smaller than 5 mm are visualized in ablation lines made of discretely spaced ablations, and complex structures are reconstructed through depth in an "x" ablation experiment. Scans of suspended atria show increased noise, but successfully visualize ablations in ARFI, MTL-SWEI, and STL-SWEI.

Preliminary Results on the Feasibility of Using ARFI/SWEI to Assess Cutaneous Sclerotic Diseases

In this study, acoustic radiation force impulse (ARFI) and shear wave elasticity imaging (SWEI) were applied to the skin to investigate the feasibility of their use in assessing sclerotic skin diseases. Our motivation was to develop a non-invasive imaging technology with real-time feedback of sclerotic skin disease diagnosis. This paper shows representative results from an ongoing study, recruiting patients with and without sclerosis. The stiffness of the imaged site was evaluated using two metrics: mean ARFI displacement magnitude and bulk shear wave speed inside the region of interest (ROI). In a subject with localized graft versus host disease (GVHD), the mean ARFI displacement inside sclerotic skin was 61% lower (p < 0.01) and shear wave speed 128% higher (p < 0.005) compared to those in normal skin—indicating stiffer mechanical properties in the sclerotic skin. This trend persisted through disease types. We conclude ARFI and SWEI can successfully differentiate sclerotic lesions from normal dermis.

Non-invasive in Vivo Characterization of Human Carotid Plaques with Acoustic Radiation Force Impulse Ultrasound: Comparison with Histology after Endarterectomy

Ischemic stroke from thromboembolic sources is linked to carotid artery atherosclerotic disease with a trend toward medical management in asymptomatic patients. Extent of disease is currently diagnosed by non-invasive imaging techniques that measure luminal stenosis, but it has been suggested that a better biomarker for determining risk of future thromboembolic events is plaque morphology and composition. Specifically, plaques that are composed of mechanically soft lipid/necrotic regions covered by thin fibrous caps are the most vulnerable to rupture. An ultrasound technique that non-invasively interrogates the mechanical properties of soft tissue, called acoustic radiation force impulse (ARFI) imaging, has been developed as a new modality for atherosclerotic plaque characterization using phantoms and atherosclerotic pigs, but the technique has yet to be validated in vivo in humans. In this preliminary study, in vivo ARFI imaging is presented in a case study format for four patients undergoing clinically indicated carotid endarterectomy and compared with histology. In two type Va plaques, characterized by lipid/necrotic cores covered by fibrous caps, mean ARFI displacements in focal regions were high relative to the surrounding plaque material, suggesting soft features were covered by stiffer layers within the plaques. In two type Vb plaques, characterized by heavy calcification, mean ARFI peak displacements were low relative to the surrounding plaque and arterial wall, suggesting stiff tissue. This pilot study illustrates the feasibility and challenges of transcutaneous ARFI for characterizing the material and structural composition of carotid atherosclerotic plaques via mechanical properties, in humans, in vivo.

Experimental Validation of Displacement Underestimation in ARFI Ultrasound

Acoustic radiation force impulse (ARFI) imaging is an elastography technique that uses ultrasonic pulses to displace and track tissue motion. Previous modeling studies have shown that ARFI displacements are susceptible to underestimation due to lateral and elevational shearing that occurs within the tracking resolution cell. In this study, optical tracking was utilized to experimentally measure the displacement underestimation achieved by acoustic tracking using a clinical ultrasound system. Three optically translucent phantoms of varying stiffness were created, embedded with subwavelength diameter microspheres, and ARFI excitation pulses with F/1.5 or F/3 lateral focal configurations were transmitted from a standard linear array to induce phantom motion. Displacements were tracked using confocal optical and acoustic methods. As predicted by earlier finite element method studies, significant acoustic displacement underestimation was observed for both excitation focal configurations; the maximum underestimation error was 35% of the optically measured displacement for the F/1.5 excitation pulse in the softest phantom. Using higher F/#, less tightly focused beams in the lateral dimension improved accuracy of displacements by approximately 10 percentage points. This work experimentally demonstrates limitations of ARFI implemented on a clinical scanner using a standard linear array and sets up a framework for future displacement tracking validation studies.

In Vitro Monitoring of the Dynamic Elasticity Changes During Radiofrequency Ablation with Acoustic Radiation Force Impulse Imaging

Acoustic radiation force impulse (ARFI) imaging is an ultrasound technique that generates relative tissue elasticity maps. Acoustic radiation force from the ultrasound transducer displaces the tissue and the resulting tissue response is monitored with conventional ultrasound methods. The tissue displacement magnitude is inversely proportional to tissue stiffness. The objective of this in vitro demonstration was to monitor dynamic elasticity changes during radiofrequency ablation (RFA). A section of porcine myocardium was ARFI imaged during RFA using a VF10-5 transducer and software modified ACUSON Antares ultrasound scanner (SiemensHealthcare; Issaquah, WA). RF delivery was temperature controlled at 65°C for 120 seconds. Figure 1 shows a pre-RFA ARFI image (A), three images taken during RFA (B-D), and two post-RFA images (E, F). In these images, the plane of the RFA catheter is into the page and the effective depth of field (15 mm ARFI energy focus) is between 10 and 22.5 mm. The color bar units are micrometers of displacement. The pre-RFA image shows high ARFI-induced displacement throughout the myocardium. During RFA a growing region of increased stiffness appeared. Figure 1(G) shows that the mean and standard deviation (n = 960 pixels) of the ARFI displacements measured outside the lesion (figure 1(A)-1) remained constant during RFA, while inside the lesion (figure 1(A)-2) they decreased. The tissue was sliced in the approximate imaging plane and stained with triphenyltetrazolium chloride (TTC) to confirm that a lesion was created (figure 2(H)). Figure 1 This experiment demonstrated that ARFI imaging can visualize the dynamic myocardial stiffness increase caused by RFA. This experimental paradigm could be used to enhance our understanding of how RFA lesions form and to evaluate lesion growth dynamics for new thermal ablation catheter designs.

Characterizing Stiffness of Human Prostates Using Acoustic Radiation Force

Acoustic Radiation Force Impulse (ARFI) imaging has been previously reported to portray normal anatomic structures and pathologies in ex vivo human prostates with good contrast and resolution. These findings were based on comparison with histological slides and McNeal's zonal anatomy. In ARFI images, the central zone (CZ) appears darker (smaller displacement) than other anatomic zones and prostate cancer (PCa) is darker than normal tissue in the peripheral zone (PZ). Since displacement amplitudes in ARFI images are determined by both the underlying tissue stiffness and the amplitude of acoustic radiation force that varies with acoustic attenuation, one question that arises is how the relative displacements in prostate ARFI images are related to the underlying prostatic tissue stiffness. In linear, isotropic elastic materials and in tissues that are relatively uniform in acoustic attenuation (e.g., liver), relative displacement in ARFI images has been shown to be correlated with underlying tissue stiffness. However, the prostate is known to be heterogeneous. Variations in acoustic attenuation of prostatic structures could confound the interpretation of ARFI images due to the associated variations in the applied acoustic radiation force. Therefore, in this study, co-registered three-dimensional (3D) ARFI datasets and quantitative shear wave elasticity imaging (SWEI) datasets were acquired in freshly-excised human prostates to investigate the relationship between displacement amplitudes in ARFI prostate images and the matched reconstructed shear moduli. The lateral time-to-peak (LTTP) algorithm was applied to the SWEI data to compute the shear-wave speed and reconstruct the shear moduli. Five types of prostatic tissue (PZ, CZ, transition zone (TZ) and benign prostatic hyperplasia (BPH), PCa and atrophy) were identified, whose shear moduli were quantified to be 4.1 +/- 0.8 kPa, 9.9 +/- 0.9 kPa, 4.8 +/- 0.6 kPa, 10.0 +/- 1.0 kPa and 8.0 kPa, respectively. Linear regression was performed to compare ARFI displacement amplitudes and the inverse of the corresponding reconstructed shear moduli at multiple depths. The results indicate an inverse relation between ARFI displacement amplitude and reconstructed shear modulus at all depths. These findings support the conclusion that ARFI prostate images portray underlying tissue stiffness variations.

Robust Principal Component Analysis and Clustering Methods for Automated Classification of Tissue Response to ARFI Excitation

We introduce a new method for automatic classification of acoustic radiation force impulse (ARFI) displacement profiles using what have been termed “robust” methods for principal component analysis (PCA) and clustering. Unlike classical approaches, the robust methods are less sensitive to high variance outlier profiles and require no a priori information regarding expected tissue response to ARFI excitation. We first validate our methods using synthetic data with additive noise and/or outlier curves. Second, the robust techniques are applied to classifying ARFI displacement profiles acquired in an atherosclerotic familial hypercholesterolemic (FH) pig iliac artery in vivo. The in-vivo classification results are compared with parametric ARFI images showing peak induced displacement and time to 67% recovery and to spatially correlated immunohistochemistry. Our results support that robust techniques outperform conventional PCA and clustering approaches to classification when ARFI data are inclusive of low to relatively high noise levels (up to 5 dB average signal-to-noise [SNR] to amplitude) but no outliers: for example, 99.53% correct for robust techniques vs. 97.75% correct for the classical approach. The robust techniques also perform better than conventional approaches when ARFI data are inclusive of moderately high noise levels (10 dB average SNR to amplitude) in addition to a high concentration of outlier displacement profiles (10% outlier content): for example, 99.87% correct for robust techniques vs. 33.33% correct for the classical approach. This work suggests that automatic identification of tissue structures exhibiting similar displacement responses to ARFI excitation is possible, even in the context of outlier profiles. Moreover, this work represents an important first step toward automatic correlation of ARFI data to spatially matched immunohistochemistry. (E-mail: fwm5f@virginia.edu)

In Vivo Assessment of Myocardial Stiffness with Acoustic Radiation Force Impulse Imaging

Acoustic radiation force impulse (ARFI) imaging has been demonstrated to be capable of visualizing variations in local stiffness within soft tissue. Recent advances in ARFI beam sequencing and parallel imaging have shortened acquisition times and lessened transducer heating to a point where ARFI acquisitions can be executed at high frame rates on commercially available diagnostic scanners. In vivo ARFI images were acquired with a linear array placed on an exposed canine heart. The electrocardiogram (ECG) was also recorded. When coregistered with the ECG, ARFI displacement images of the heart reflect the expected myocardial stiffness changes during the cardiac cycle. A radio-frequency ablation was performed on the epicardial surface of the left ventricular free wall, creating a small lesion that did not vary in stiffness during a heartbeat, though continued to move with the rest of the heart. ARFI images showed a hemispherical, stiffer region at the ablation site whose displacement magnitude and temporal variation through the cardiac cycle were less than the surrounding untreated myocardium. Sequences with radiation force pulse amplitudes set to zero were acquired to measure potential cardiac motion artifacts within the ARFI images. The results show promise for real-time cardiac ARFI imaging. (E-mail: stephen.j.hsu@duke.edu)

BSS-based filtering of physiological and ARFI-induced tissue and blood motion

Blind source separation (BSS) for adaptive filtering is presented in application to imaging both physiological and acoustic radiation force impulse (ARFI)-induced tissue and blood motion in the common carotid artery. The collected raw radiofrequency (RF) data includes vessel wall motion, blood flow and ARFI-induced motion. In the context of these complex motion patterns, the same BSS adaptive filtering method was employed for three diverse applications: 1. clutter filtering ensembles prior to blood velocity estimation, 2. extracting small axial velocity components from noisy velocity measurements given large flow angles and 3. reducing noise in measured ARFI-induced tissue displacement profiles to enhance differentiation of local tissue structures. The filter separated physiological vessel wall motion from axial blood flow and ARFI-induced motion; successful filter performance is demonstrated in velocity estimates, color flow images and ARFI displacement profiles. The results demonstrate the breadth of applications for BSS adaptive filtering in the clinical imaging environment. (E-mail: caterina.gallippi@duke.edu)