Radio Frequency Data Research Articles

A Sensor-Driven Analysis of Distributed Direction Finding Systems Based on UAV Swarms.

This paper reports on the research of factors that impact the accuracy and efficiency of an unmanned aerial vehicle (UAV) based radio frequency (RF) and microwave data collection system. The swarming UAVs (agents) can be utilized to create micro-UAV swarm-based (MUSB) aperiodic antenna arrays that reduce angle ambiguity and improve convergence in sub-space direction-of-arrival (DOA) techniques. A mathematical data model is addressed in this paper to demonstrate fundamental properties of MUSB antenna arrays and study the performance of the data collection system framework. The Cramer–Rao bound (CRB) associated with two-dimensional (2D) DOAs of sources in the presence of sensor gain and phase coefficient is derived. The single-source case is studied in detail. The vector-space of emitters is exploited and the iterative-MUSIC (multiple signal classification) algorithm is created to estimate 2D DOAs of emitters. Numerical examples and practical measurements are provided to demonstrate the feasibility of the proposed MUSB data collection system framework using iterative-MUSIC algorithm and benchmark theoretical expectations.

Pulse wave velocity to the global longitudinal strain ratio in survivors of myocardial infarction.

New index of pulse wave velocity to global longitudinal peak systolic strain (PWV/GLPSS) was reported to be associated with cardiovascular damage. We evaluated the prognostic role of this metric in survivors of acute myocardial infarction (AMI). We investigated in 569 patients with AMI, whether PWV/GLPSS was associated with a composite endpoint of death, stroke or new myocardial infarction, in long-term follow-up. Left ventricular longitudinal strain was evaluated by speckle tracking, and carotid arterial stiffness (local PWV) was determined using radiofrequency data technology. During follow-up (median 1316days), 114 subjects reached composite endpoint. These subjects were significantly older (P<0.0001) and were characterized by lower ejection fraction (P<0.0001), lower GLPSS (P<0.0001), higher PWV (P=0.007) and lower PWV/GLPSS index (P<0.0001). Patients with PWV/GLPSS <-0.74 were at a significantly higher risk for the composite endpoint during the follow-up (hazard rate: 1.7; 95% confidence interval: 1.2-2.6; P<0.001). The PWV/GLPSS was additive to the predictive value of EF<35%-patients with PWV/GLPSS <-0.74 and EF<35% had the highest risk for the endpoint events. The current study shows that PWV/GLPSS index has significant, independent and additive value in predicting CV complications, in subjects with myocardial infarction.

Lagrangian carotid strain imaging indices normalized to blood pressure for vulnerable plaque.

Ultrasound Lagrangian carotid strain imaging (LCSI) utilizes physiological deformation caused by arterial pressure variations to generate strain tensor maps of the vessel walls and plaques. LCSI has been criticized for the lack of normalization of magnitude-based strain indices to physiological stimuli, namely blood pressure. We evaluated the impact of normalization of magnitude-based strain indices to blood pressure measured immediately after the acquisition of radiofrequency (RF) data loops for LCSI. A complete clinical ultrasound examination along with RF data loops for LCSI was performed on 50 patients (30 males and 20 females) who presented with >60% carotid stenosis and were scheduled for carotid endarterectomy. Cognition was assessed using the 60-minute neuropsychological test protocol. For axial strains correlation of maximum accumulated strain indices (MASI), cognition scores were -0.46 for non-normalized and -0.45, -0.49, -0.37, and -0.48 for systolic, diastolic, pulse pressure, and mean arterial pressure normalized data, respectively. The corresponding area under the curve (AUC) values for classifiers designed using maximum likelihood estimation of a binormal distribution with a median-split of the executive function cognition scores were 0.73, 0.70, 0.71, 0.70, and 0.71, respectively. No significant differences in the AUC estimates were obtained between normalized and non-normalized magnitude-based strain indices.

Coherent Multi-Transducer Ultrasound Imaging.

This work extends the effective aperture size by coherently compounding the received radio frequency data from multiple transducers. As a result, it is possible to obtain an improved image, with enhanced resolution, an extended field of view (FoV), and high-acquisition frame rates. A framework is developed in which an ultrasound imaging system consisting of N synchronized matrix arrays, each with partly shared FoV, take turns to transmit plane waves (PWs). Only one individual transducer transmits at each time while all N transducers simultaneously receive. The subwavelength localization accuracy required to combine information from multiple transducers is achieved without the use of any external tracking device. The method developed in this study is based on the study of the backscattered echoes received by the same transducer and resulting from a targeted scatterer point in the medium insonated by the multiple ultrasound probes of the system. The current transducer locations along with the speed of sound in the medium are deduced by optimizing the cross correlation between these echoes. The method is demonstrated experimentally in 2-D for two linear arrays using point targets and anechoic lesion phantoms. The first demonstration of a free-hand experiment is also shown. Results demonstrate that the coherent multi-transducer ultrasound imaging method has the potential to improve ultrasound image quality, improving resolution, and target detectability. Compared with coherent PW compounding using a single probe, lateral resolution improved from 1.56 to 0.71 mm in the coherent multi-transducer imaging method without acquisition frame rate sacrifice (acquisition frame rate 5350 Hz).

Acoustic Shadow Detection: Study and Statistics of B-Mode and Radiofrequency Data

An acoustic shadow is an ultrasound artifact occurring at boundaries between significantly different tissue impedances, resulting in signal loss and a dark appearance. Shadow detection is important as shadows can identify anatomical features or obscure regions of interest. A study was performed to scan human participants (N = 37) specifically to explore the statistical characteristics of various shadows from different anatomy and with different transducers. Differences in shadow statistics were observed and used for shadow detection algorithms with a fitted Nakagami distribution on radiofrequency (RF) speckle or cumulative entropy on brightness-mode (B-mode) data. The fitted Nakagami parameter and entropy values in shadows were consistent across different transducers and anatomy. Both algorithms utilized adaptive thresholding, needing only the transducer pulse length as an input parameter for easy utilization by different operators or equipment. Mean Dice coefficients (± standard deviation) of 0.90 ± 0.07 and 0.87 ± 0.08 were obtained for the RF and B-mode algorithms, which is within the range of manual annotators. The high accuracy in different imaging scenarios indicates that the shadows can be detected with high versatility and without expert configuration. The understanding of shadow statistics can be used for more specialized techniques to be developed for specific applications in the future, including pre-processing for machine learning and automatic interpretation.

Application of virtual histological intravascular ultrasound in plaque composition assessment of saphenous vein graft diseases.

Objective:Saphenous vein grafts disease (SVGD) is a common complication after coronary artery bypass graft (CABG) and normally treated by percutaneous coronary intervention (PCI). The most common complication after SVG-PCI is slow or no-reflow. It is known that the no-reflow phenomenon occurs in up to 15% of the SVG-PCI and is associated with high risk of major adverse cardiac events (MACEs) and mortality, therefore, it is important to investigate the factors that could predict the clinical outcome of PCI for risk stratification and guiding interventions. In recent years, the spectral analysis of intravascular ultrasound (IVUS) radiofrequency data (virtual histology-IVUS [VH-IVUS]) has been used to provide quantitative assessment on both plaque compositions and morphologic characteristics.Data sources:The PubMed, Embase, and Central databases were searched for possible relevant studies published from 1997 to 2018 using the following index keywords: “Coronary artery bypass grafting,” “Saphenous venous graft disease,” “Virtual histology-intravascular ultrasound,” “Virtual histology-intravascular ultrasound,” and “Percutaneous coronary intervention.”Study selection:The primary references were Chinese and English articles including original studies and literature reviews, were identified and reviewed to summarize the advances in the application of VH-IVUS techniques in situ vascular and venous graft vascular lesions.Results:With different plaque components exhibiting a defined spectrum, VH-IVUS can classify atherosclerotic plaque into four types: fibrous tissue (FT), fibro fatty (FF), necrotic core (NC), and dense calcium (DC). The radiofrequency signal is mathematically transformed into a color-coded representation, including lipid, fibrous tissue, calcification, and necrotic core. Several studies have demonstrated the independent relationship between VH-IVUS–defined plaque classification or plaque composition and MACEs, but a significant association between plaque components and no-reflow after PCI in acute coronary syndrome. In recent years, VH-IVUS are applied to assess the plaque composition of SVGD, based on the similarity of pathophysiological mechanisms between coronary artery disease (CAD) and SVGD, further studies with the larger sample size, the long-term follow-up, multicenter clinical trials may be warranted to investigate the relationship between plaque composition of saphenous vein graft (SVG) by VH-IVUS and clinical outcomes in patients with SVGD undergoing PCI.Conclusions:In degenerative SVG lesions, VH-IVUS found that plaque composition was associated with clinical features, future studies need to explore the relationship between VH-IVUS defined atherosclerotic plaque components and clinical outcomes in SVGD patients undergoing PCI, an innovative prediction tool of clinical outcomes can be created.

Evaluation of subclinical atherosclerosis by ultrasound radiofrequency data technology in patients with Behçet's disease.

We aimed to evaluate subclinical atherosclerosis based on carotid intima-media thickness (CIMT) and arterial stiffness measurements in patients with Behçet's disease (BD), using ultrasound (US) radiofrequency (RF) data technology. We included 33 BD patients and 33 healthy controls in this study. The participants did not have any primary cardiovascular risk factors, such as diabetes mellitus, hypertension, hyperlipidemia and obesity. All participants were evaluated using Doppler ultrasonography. Arterial stiffness and CIMT measurements were performed in bilateral common carotid arteries using the US RF data technology. The right, left and mean CIMT values were similar between the patient and control groups (P >0.05). There was also no statistically significant difference in the right side α and β stiffness indices despite higher values in the patient group (P> 0.05). The right, left and mean distensibility coefficient (DC) and compliance coefficient (CC) values of the patient group were significantly lower than the control group (P< 0.05). The left and mean α- and β-stiffness indices, and the right, left and mean pulse wave velocity (PWV) values were significantly higher in the patient group (P< 0.05). We found higher mean CIMT and PWV values, and α- and β-stiffness indices in patients with mucocutaneous involvement compared with those with major organ involvement, while the mean DC and CC values were lower in the former. However, these results did not reach a statistically significant level. This study demonstrated evidence of subclinical atherosclerosis in BD in the absence of major atherosclerotic risk factors.

Compressed Sensing with Gaussian Sampling Kernel for Ultrasound Imaging

Recently, compressed sensing (CS) has been applied to ultrasound imaging for either data reduction or frame rate improvement. However, there are no detailed reports yet on strategies for lateral undersampling of channel data in conventional focused beamforming (CFB) and its recovery exploiting the CS approach. We propose a strategic lateral undersampling approach for channel data using the Gaussian sampling scheme and compare it with a direct extension of the often-used uniform undersampling reported for axial undersampling to the lateral direction and 2-D random sampling reported in the literature. As opposed to the reported 2-D random undersampling, we explore undersampling of channel data in the lateral direction by acquiring radiofrequency data from only a reduced number of chosen receive elements and subjecting these data to further undersampling in the axial direction. The effect of the sampling schemes on CS recovery was studied using data from simulations and experiments for various lateral and axial undersampling rates. The results suggest that CS-recovered data from the Gaussian distribution-based channel data subsampling yielded better recovery and contrast in comparison to those obtained from the often-used uniform distribution-based undersampling. Although 90% of the samples from the original data using the proposed sampling scheme were discarded, the contrast of the CS-recovered image was comparable to that of the reference image. Thus, CS with the proposed Gaussian sampling scheme for channel data subsampling not only reduces the data size significantly, but also strategically uses only a few active receive elements in the process; thus, it can provide an attractive option for the affordable point-of-care ultrasound system.

Transbronchial evaluation of peripheral pulmonary lesions using ultrasonic spectrum analysis in lung cancer patients.

Analysis of the endobronchial ultrasound (EBUS) radiofrequency spectrum has been used for convex-probe EBUS technology. Quantitative imaging analysis is also warranted for guided bronchoscopy using radial-probe EBUS (RP-EBUS) targeting peripheral pulmonary lesions (PPL). This study aimed to determine the feasibility of radiofrequency spectrum analysis for distinguishing malignant and benign PPL during diagnostic bronchoscopy. Raw RP-EBUS images with radiofrequency data, including backscatter signals, were prospectively recorded. The ultrasonic spectral parameters, such as intercept, midband-fit and slope within the region of interest, were retrospectively computed by linear regression analysis and compared with the final diagnosis. A total of 71 PPL, including 45 malignant and 26 benign lesions, were analysed. Malignant PPL showed a significantly lower intercept (P < 0.0001), lower midband-fit (P < 0.0001) and higher slope (P = 0.014) than benign PPL. Analyses of the area under the curve of receiver operating characteristic plots demonstrated that the intercept showed the best diagnostic performance among three parameters (0.87, 0.77 and 0.69 for intercept, midband-fit and slope, respectively). The sensitivity, specificity, accuracy, positive likelihood and negative likelihood were 75.6%, 96.2%, 83.1%, 19.6 and 0.25 for the intercept; 88.9%, 57.7%, 77.5%, 2.1 and 0.19 for the midband-fit; and 68.9%, 73.1%, 70.4%, 2.6 and 0.43 for the slope. Spectrum analysis of EBUS radiofrequency can be used as a novel non-invasive predictor of malignant or benign PPL. Analysis of the 'intercept' of the targeted lesion may provide useful supporting data for real-time sampling from PPL during diagnostic bronchoscopy.

Monitoring breast cancer response to neoadjuvant chemotherapy with ultrasound signal statistics and integrated backscatter.

BackgroundNeoadjuvant chemotherapy (NAC) is used in patients with breast cancer to reduce tumor focus, metastatic risk, and patient mortality. Monitoring NAC effects is necessary to capture resistant patients and stop or change treatment. The existing methods for evaluating NAC results have some limitations. The aim of this study was to assess the tumor response at an early stage, after the first doses of the NAC, based on the variability of the backscattered ultrasound energy, and backscatter statistics. The backscatter statistics has not previously been used to monitor NAC effects.MethodsThe B-mode ultrasound images and raw radio frequency data from breast tumors were obtained using an ultrasound scanner before chemotherapy and 1 week after each NAC cycle. The study included twenty-four malignant breast cancers diagnosed in sixteen patients and qualified for neoadjuvant treatment before surgery. The shape parameter of the homodyned K distribution and integrated backscatter, along with the tumor size in the longest dimension, were determined based on ultrasound data and used as markers for NAC response. Cancer tumors were assigned to responding and non-responding groups, according to histopathological evaluation, which was a reference in assessing the utility of markers. Statistical analysis was performed to rate the ability of markers to predict the final NAC response based on data obtained after subsequent therapeutic doses.ResultsStatistically significant differences (p<0.05) between groups were obtained after 2, 3, 4, and 5 doses of NAC for quantitative ultrasound markers and after 5 doses for the assessment based on maximum tumor dimension. Statistical analysis showed that, after the second and third NAC courses the classification based on integrated backscatter marker was characterized by an AUC of 0.69 and 0.82, respectively. The introduction of the second quantitative marker describing the statistical properties of scattering increased the corresponding AUC values to 0.82 and 0.91.ConclusionsQuantitative ultrasound information can characterize the tumor's pathological response better and at an earlier stage of therapy than the assessment of the reduction of its dimensions. The introduction of statistical parameters of ultrasonic backscatter to monitor the effects of chemotherapy can increase the effectiveness of monitoring and contribute to a better personalization of NAC therapy.

Interpretability and generalizability of a one-dimensional convolutional neural network method for hepatic steatosis characterization

Nonalcoholic fatty liver disease (NAFLD) affects 25% of the population globally. We developed a one-dimensional convolutional neural network (1-D CNN) method for the ultrasound tissue characterization using radio-frequency (RF) data and demonstrated its potential for the liver fat classification and quantification. We investigate herein the interpretability and generalizability of the method to understand why it works, and whether the performance is affected by settings, transducers, and platforms. We studied under various conditions the performances of 1-D CNN for predicting steatosis using magnetic resonance imaging-estimated proton density fat fraction (MRI-PDFF) as reference (steatosis: PDFF > 5%). Three datasets were used, each containing ultrasound RF data acquired from adults and same-day MRI-PDFF estimates: (1) 200 normal and NAFLD participants scanned using the Siemens S2000 ultrasound system with the 4C1 transducer (1–4 MHz); (2) 87 participants with known/suspected NAFLD scanned using Siemens S3000 with the 4C1 and/or 6C1HD transducers (1.5–6 MHz); and (3) 46 participants with known/suspected NAFLD scanned using GE Logiq e9 with the C1-6 transducer (1–6 MHz). The 1-D CNN method is generalizable among various instrumentation settings (e.g., focal depth, time gain compensation), betweentransducers of similar frequencies, between platforms, but not between the fundamental and tissue harmonic image modes. [Work supported by R01DK106419.] Nonalcoholic fatty liver disease (NAFLD) affects 25% of the population globally. We developed a one-dimensional convolutional neural network (1-D CNN) method for the ultrasound tissue characterization using radio-frequency (RF) data and demonstrated its potential for the liver fat classification and quantification. We investigate herein the interpretability and generalizability of the method to understand why it works, and whether the performance is affected by settings, transducers, and platforms. We studied under various conditions the performances of 1-D CNN for predicting steatosis using magnetic resonance imaging-estimated proton density fat fraction (MRI-PDFF) as reference (steatosis: PDFF > 5%). Three datasets were used, each containing ultrasound RF data acquired from adults and same-day MRI-PDFF estimates: (1) 200 normal and NAFLD participants scanned using the Siemens S2000 ultrasound system with the 4C1 transducer (1–4 MHz); (2) 87 participants with known/suspected NAFLD scanned using Siemens ...

ICE-MoCha: Intelligent Crowd Engineering using Mobility Characterization and Analytics.

Human injuries and casualties at entertaining, religious, or political crowd events often occur due to the lack of proper crowd safety management. For instance, for a large scale moving crowd, a minor accident can create a panic for the people to start stampede. Although many smart video surveillance tools, inspired by the recent advanced artificial intelligence (AI) technology and machine learning (ML) algorithms, enable object detection and identification, it is still challenging to predict the crowd mobility in real-time for preventing potential disasters. In this paper, we propose an intelligent crowd engineering platform using mobility characterization and analytics named ICE-MoCha. ICE-MoCha is to assist safety management for mobile crowd events by predicting and thus helping to prevent potential disasters through real-time radio frequency (RF) data characterization and analysis. The existing video surveillance based approaches lack scalability thus have limitations in its capability for wide open areas of crowd events. Via effectively integrating RF signal analysis, our approach can enhance safety management for mobile crowd. We particularly tackle the problems of identification, speed, and direction detection for the mobile group, among various crowd mobility characteristics. We then apply those group semantics to track the crowd status and predict any potential accidents and disasters. Taking the advantages of power-efficiency, cost-effectiveness, and ubiquitous availability, we specifically use and analyze a Bluetooth low energy (BLE) signal. We have conducted experiments of ICE-MoCha in a real crowd event as well as controlled indoor and outdoor lab environments. The results show the feasibility of ICE-MoCha detecting the mobile crowd characteristics in real-time, indicating it can effectively help the crowd management tasks to avoid potential crowd movement related incidents.

Monitoring Microwave Ablation Using Ultrasound Echo Decorrelation Imaging: An ex vivo Study.

In this study, a microwave-induced ablation zone (thermal lesion) monitoring method based on ultrasound echo decorrelation imaging was proposed. A total of 15 cases of ex vivo porcine liver microwave ablation (MWA) experiments were carried out. Ultrasound radiofrequency (RF) signals at different times during MWA were acquired using a commercial clinical ultrasound scanner with a 7.5-MHz linear-array transducer. Instantaneous and cumulative echo decorrelation images of two adjacent frames of RF data were calculated. Polynomial approximation images were obtained on the basis of the thresholded cumulative echo decorrelation images. Experimental results showed that the instantaneous echo decorrelation images outperformed conventional B-mode images in monitoring microwave-induced thermal lesions. Using gross pathology measurements as the reference standard, the estimation of thermal lesions using the polynomial approximation images yielded an average accuracy of 88.60%. We concluded that instantaneous ultrasound echo decorrelation imaging is capable of monitoring the change of thermal lesions during MWA, and cumulative ultrasound echo decorrelation imaging and polynomial approximation imaging are feasible for quantitatively depicting thermal lesions.

Inter-platform reproducibility of ultrasonic attenuation and backscatter coefficients in assessing NAFLD.

To assess inter-platform reproducibility of ultrasonic attenuation coefficient (AC) and backscatter coefficient (BSC) estimates in adults with known/suspected nonalcoholic fatty liver disease (NAFLD). This HIPAA-compliant prospective study was approved by an institutional review board; informed consent was obtained. Participants with known/suspected NAFLD were recruited and underwent same-day liver examinations with clinical ultrasound scanner platforms from two manufacturers. Each participant was scanned by the same trained sonographer who performed multiple data acquisitions in the right liver lobe using a lateral intercostal approach. Each data acquisition recorded a B-mode image and the underlying radio frequency (RF) data. AC and BSC were calculated using the reference phantom method. Inter-platform reproducibility was evaluated for AC and log-transformed BSC (logBSC = 10log10BSC) by intraclass correlation coefficient (ICC), Pearson's correlation, Bland-Altman analysis with computation of limits of agreement (LOAs), and within-subject coefficient of variation (wCV; applicable to AC). Sixty-four participants were enrolled. Mean AC values measured using the two platforms were 0.90 ± 0.13 and 0.94 ± 0.15dB/cm/MHz while mean logBSC values were - 30.6 ± 5.0 and - 27.9 ± 5.6dB, respectively. Inter-platform ICC was 0.77 for AC and 0.70 for log-transformed BSC in terms of absolute agreement. Pearson's correlation coefficient was 0.81 for AC and 0.80 for logBSC. Ninety-five percent LOAs were - 0.21 to 0.13dB/cm/MHz for AC, and - 9.48 to 3.98dB for logBSC. The wCV was 7% for AC. Hepatic AC and BSC are reproducible across two different ultrasound platforms in adults with known or suspected NAFLD. • Ultrasonic attenuation coefficient and backscatter coefficient are reproducible between two different ultrasound platforms in adults with NAFLD. • This inter-platform reproducibility may qualify quantitative ultrasound biomarkers for generalized clinical application in patients with suspected/known NAFLD.

MR-Guided Focused Ultrasound Versus Radiofrequency Capsulotomy for Treatment-Refractory Obsessive-Compulsive Disorder: A Cost-Effectiveness Threshold Analysis.

Meta-analytic techniques support neuroablation as a promising therapy for treatment-refractory obsessive-compulsive disorder (OCD). This technique appears to offer a more favorable complication rate and higher utility than deep brain stimulation. Moreover, these pooled findings suggest that bilateral radiofrequency (RF) capsulotomy has marginally greater efficacy than stereotactic radiosurgery or cingulotomy. MR-guided focused ultrasound (MRgFUS) capsulotomy is an emerging approach with a potentially more favorable profile than RF ablation and radiosurgery, with preliminary data suggesting safety and efficacy. As a clinical trial is being developed, our study examined the cost and clinical parameters necessary for MRgFUS capsulotomy to be a more cost-effective alternative to RF capsulotomy. A decision analytical model of MRgFUS with RF capsulotomy for OCD was performed using outcome parameters of percent surgical improvement in Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score, complications, and side effects. The analysis compared measured societal costs, derived from Medicare reimbursement rates, and effectiveness, based on published RF data. Effectiveness was defined as the degree to which MRgFUS lowered Y-BOCS score. Given that MRgFUS is a new therapy for OCD with scant published data, theoretical risks of MRgFUS capsulotomy were derived from published essential tremor outcomes. Sensitivity analysis yielded cost, effectiveness, and complication rates as critical MRgFUS parameters defining the cost-effectiveness threshold. Literature search identified eight publications (162 subjects). The average reduction of preoperative Y-BOCS score was 56.6% after RF capsulotomy with a 22.6% improvement in utility, a measure of quality of life. Complications occurred in 16.2% of RF cases. In 1.42% of cases, complications were considered acute-perioperative and incurred additional hospitalization cost. The adverse events, including neurological and neurobehavioral changes, in the other 14.8% of cases did not incur further costs, although they impacted utility. Rollback analysis of RF capsulotomy yielded an expected effectiveness of 0.212 quality-adjusted life years/year at an average cost of $24,099. Compared to RF capsulotomy, MRgFUS was more cost-effective under a range of possible cost and complication rates. While further study will be required, MRgFUS lacks many of the inherent risks associated with more invasive modalities and has potential as a safe and cost-effective treatment for OCD.

Attenuation estimation of soft tissue with reference-free minimization of system effects

Estimation of ultrasonic attenuation coefficient (AC) is essential for quantifying and characterizing the features of tissue microstructure. In the conventional AC estimation methods, a well-specified reference phantom is commonly used for minimizing the diffraction and transmit pulse related effects on the ultrasound radio-frequency (RF) signal. In this paper, a novel AC estimation technique is proposed avoiding the need of using any reference data, where the undesired system effects on the RF data are minimized through point spread function (PSF) separation and band-pass filtering of the envelope signal of the tissue reflectivity function (TRF). An improved and computationally efficient non-parametric cepstrum-based technique is used for separating the TRF and PSF from the measured RF signal. The Hilbert transform based temporal envelope is introduced to smooth out the unwanted effects of discontinuity and noise in the TRF and PSF signals. Finally, a band-pass filter based log power approximation of the TRF-envelope is applied to estimate the center frequency component of the attenuating power spectra with reduced diffraction effect. Assuming continuity of AC within a small uniform region, an exponentially weighted-average of logarithmic signal power of the neighboring blocks at the center frequency is measured for different depths, with a view to fit a regression line for obtaining an average AC value from its slope. Comparative results of the proposed reference-free AC estimation method with other conventional reference-based methods are presented for tissue-mimicking (TM) phantoms, in vivo breast and liver data. For the TM phantoms, the AC estimates using the new algorithm are within 10% deviation of the actual values. The obtained results for the breasts, normal livers, and fatty livers are 0.44 ± 0.23 dB/cm-MHz, 0.55 ± 0.21 dB/cm-MHz, and 0.61 ± 0.20 dB/cm-MHz, respectively, which are consistent with the literature-reported AC values. Different from reference-based methods, the novel technique is free from the bias that may result from the dissimilarity between acoustic property of the reference and sample.

ARFI and shear wave imaging of the prostate to delineate clinically-significant cancers

Current prostate cancer screening methods involve non-targeted needle biopsies and the detection of clinically-insignificant lesions that receive excessive treatments, exposing patients to unnecessary adverse side effects and placing a burden on our health care systems. There is a strong clinical need for improved prostate imaging methods that are sensitive and specific for clinically-significant prostate cancer lesions to guide needle biopsies, target focal treatments, and improve overall patient outcomes. We have developed a 3D, in vivo Acoustic Radiation Force Impulse (ARFI) imaging and Shear Wave Elasticity Imaging (SWEI) system using a side-fire endorectal linear array with a custom rotation stage to collect prostate imaging volumes to identify regions of suspicion that should be targeted during biopsy procedures. We have validated that ARFI imaging can reliability identify regions of clinically-significant prostate cancer by comparing our imaging volumes with whole-mount histology in patients undergoing radical prostatectomy; however, there was opportunity to improve the diagnostic sensitivity and specificity by combining ARFI imaging data with SWEI. While ARFI images contain regions of relative contrast (decreased displacement) to delineate regions of suspicion, we hypothesized that SWEI could provide absolute shear wave speeds that could quantify the degree of suspicion of an identified lesion, with more aggressive lesions being stiffer and having higher shear wave speeds. In an ongoing clinical study of over 30 patients, we have demonstrated that the combination of ARFI and SWEI data can improve the diagnostic accuracy of clinically-significant lesion identification, while the inclusion of B-mode echogenicity was not found to improve diagnostic accuracy. More complex classification models to identify clinically-significant prostate cancer using ARFI and SWEI metrics are being developed using Linear Discriminant Analysis (LDA) and Support-Vector Machines (SVMs). These classification models will be further extended to explore the diagnostic value of additional quantitative ultrasound metrics derived from the raw radiofrequency (RF) data and other imaging methods commonly used in the diagnostic workup of prostate cancer patients, such as multiparametric magnetic resonance imaging (mp-MRI).

Clinical validation of ultrasound backscatter statistics for the assessment of liver fibrosis

Introduction Deposition of fibrous tissue in the liver changes with the progression of liver cirrhosis. Ultrasound backscatter imaging may describe the scatterer distribution in the liver, and reflect the severity of liver cirrhosis. However, it is known that the backscatter statistics are often subject to ultrasound imaging settings, region of interest (ROI) for analysis and hepatic steatosis. This study aims to establish a standard imaging procedure and a discriminant model for assessment of liver fibrosis regardless of the degrees of liver fatty changes. Methods 201 patients received elective liver resection were prospectively enrolled in the study. Ultrasound radio-frequency (RF) data of right liver lobe through an intercostal space with the maximum imaging depth of 8cm were collected using the Terason t3000 ™ (convex array) system pre-operatively from each patient. Since significant inter-ROI variation was found when the ROI is less than 10 cm2, all the ROI's were selected such that the ROI area covered as much as possible the liver parenchyma and was larger than 10 cm2. The liver tissue was examined and determined by an experienced pathologist the degrees of liver fibrosis and fatty changes. Among the 201 patients, there were 36 F0, 51 F1, 26 F2, 22 F3 and 66 F4 patients while 62 with mild steatosis (5-30%) and 26 with severe steatosis (> 30%). A FDA-cleared backscatter analysis tool (AmCAD-USTM) was used to calculate the statistics and a stepwise logistic regression model was established to differentiate significant liver fibrosis (≥ F2). Results Three backscatter statistics, including the 95th percentile of the Nakagami (m) statistic, and the 75th and 95th percentiles of the histogram (h) statistics, were selected into the logistic model. Regardless of the liver fatty changes, the Receiver Operating Characteristic (ROC) curve analysis showed a significant discriminant power of the model for evaluation of liver fibrosis - stage 0 versus stage 1-4, AUC 0.77 (p-value Conclusions The liver fibrosis in human results in variation of the scatterer distributions in medical ultrasound imaging. Following a standard imaging procedure, a discriminant model is established and shown to be able to distinguish significantly different degrees of liver fibrosis regardless of the presence of steatosis.

Focused ultrasound activates voltage-gated calcium channels through depolarizing TRPC1 sodium currents in kidney and skeletal muscle.

Pulsed focused ultrasound (pFUS) technology is being developed for clinical neuro/immune modulation and regenerative medicine. Biological signal transduction of pFUS forces can require mechanosensitive or voltage-gated plasma membrane ion channels. Previous studies suggested pFUS is capable of activating either channel type, but their mechanistic relationship remains ambiguous. We demonstrated pFUS bioeffects increased mesenchymal stem cell tropism (MSC) by altering molecular microenvironments through cyclooxygenase-2 (COX2)-dependent pathways. This study explored specific relationships between mechanosensitive and voltage-gated Ca2+ channels (VGCC) to initiate pFUS bioeffects that increase stem cell tropism.Methods: Murine kidneys and hamstring were given pFUS (1.15 or 1.125 MHz; 4MPa peak rarefactional pressure) under ultrasound or magnetic resonance imaging guidance. Cavitation and tissue displacement were measure by hydrophone and ultrasound radiofrequency data, respectively. Elastic modeling was performed from displacement measurements. COX2 expression and MSC tropism were evaluated in the presence of pharmacological ion channel inhibitors or in transient-receptor-potential-channel-1 (TRPC1)-deficient mice. Immunohistochemistry and co-immunoprecipitation examined physical channel relationships. Fluorescent ionophore imaging of cultured C2C12 muscle cells or TCMK1 kidney cells probed physiological interactions.Results: pFUS induced tissue deformations resulting in kPa-scale forces suggesting mechanical activation of pFUS-induced bioeffects. Inhibiting VGCC or TRPC1 in vivo blocked pFUS-induced COX2 upregulation and MSC tropism to kidneys and muscle. A TRPC1/VGCC complex was observed in plasma membranes. VGCC or TRPC1 suppression blocked pFUS-induced Ca2+ transients in TCMK1 and C2C12 cells. Additionally, Ca2+ transients were blocked by reducing transmembrane Na+ potentials and observed Na+ transients were diminished by genetic TRPC1 suppression.Conclusion: This study suggests that pFUS acoustic radiation forces mechanically activate a Na+-containing TRPC1 current upstream of VGCC rather than directly opening VGCC. The electrogenic function of TRPC1 provides potential mechanistic insight into other pFUS techniques for physiological modulation and optimization strategies for clinical implementation.

Real-time H-scan ultrasound imaging using a Verasonics research scanner

H-scan ultrasound (US) is a new imaging technique that relies on matching a model that describes US image formation to the mathematics of a class of Gaussian-weighted Hermite polynomials (GH). In short, H-scan US (where the ‘H’ denotes Hermite or hue) is a tissue classification technique that images the relative size of acoustic scatterers. Herein, we detail development of a real-time H-scan US imaging technology that was implemented on a programmable US research scanner (Vantage 256, Verasonics Inc, Kirkland, WA). This custom US imaging system has a dual display for real-time visualization of both the H-scan and B-scan US images. This MATLAB-based (Mathworks Inc, Natick, MA) system includes a graphical user interface (GUI) for controlling the entire US scan sequence including the raw radio frequency (RF) data acquisition parameters, image processing, variable control of a parallel set of convolution filters used to derive the H-scan US signal, and data (cine loop) save. The system-level structure used for software-based image reconstruction and display is detailed. Imaging studies were conducted using a series of homogeneous and heterogeneous tissue-mimicking phantom materials embedded with monodisperse spherical US scatterers of size 15–40 µm in diameter. Relative to H-scan US image measurements from a phantom with 15 µm-sized scatterers, data from phantoms with the 30 and 40 µm-sized scatterers exhibited mean intensity increases of 5.2% and 11.6%, respectively. Overall, real-time H-scan US imaging is a promising approach for visualizing the relative size and distribution of acoustic scattering objects.