Radiofrequency Echo Signals Research Articles

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.

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

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

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

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

Nakagami imaging for detecting thermal lesions induced by high-intensity focused ultrasound in tissue

High-intensity focused ultrasound induces focalized tissue coagulation by increasing the tissue temperature in a tight focal region. Several methods have been proposed to monitor high-intensity focused ultrasound-induced thermal lesions. Currently, ultrasound imaging techniques that are clinically used for monitoring high-intensity focused ultrasound treatment are standard pulse-echo B-mode ultrasound imaging, ultrasound temperature estimation, and elastography-based methods. On the contrary, the efficacy of two-dimensional Nakagami parametric imaging based on the distribution of the ultrasound backscattered signals to quantify properties of soft tissue has recently been evaluated. In this study, ultrasound radio frequency echo signals from ex vivo tissue samples were acquired before and after high-intensity focused ultrasound exposures and then their Nakagami parameter and scaling parameter of Nakagami distribution were estimated. These parameters were used to detect high-intensity focused ultrasound-induced thermal lesions. Also, the effects of changing the acoustic power of the high-intensity focused ultrasound transducer on the Nakagami parameters were studied. The results obtained suggest that the Nakagami distribution's scaling and Nakagami parameters can effectively be used to detect high-intensity focused ultrasound-induced thermal lesions in tissue ex vivo. These parameters can also be used to understand the degree of change in tissue caused by high-intensity focused ultrasound exposures, which could be interpreted as a measure of degree of variability in scatterer concentration in various parts of the high-intensity focused ultrasound lesion.

Computer-Aided Diagnosis of Solid Breast Lesions Using an Ultrasonic Multi-Feature Analysis Procedure

We have developed a family of quantitative descriptors in order to provide noninvasive, reliable means of distinguishing benign from malignant breast lesions. These include acoustic descriptors (“echogenicity,” “heterogeneity,” “shadowing”) and morphometric descriptors (“area,” “aspect ratio,” “border irregularity,” “margin definition”). These quantitative descriptors are designed to be independent of instrument properties and physician expertise. Our analysis included manual tracing of lesion boundaries and adjacent areas on grayscale images generated from RF data. To derive quantitative acoustic features, we computed spectral-parameter maps of radio-frequency (RF) echo signals (using a sliding-window Fourier analysis) of the lesion and adjacent areas. We quantified morphometric features by geometric and fractal analysis of traced lesion boundaries. Although no single parameter can reliably discriminate cancerous from non-cancerous breast lesions, multi-feature analysis provides excellent discrimination of cancerous and non-cancerous lesions. Our analysis of data acquired during routine ultrasonic examination of 130 biopsy-scheduled patients produced a receiver-operating characteristic (ROC) area under the curve (AUC) of 0.947±0.045. Lesion-margin definition, spiculation, and border irregularity were the most useful among the quantitative descriptors; some morphometric features (such as border irregularity) also were particularly effective in lesion classification. Our results are consistent with many of the Breast Imaging Reporting and Data System (BI-RADS) breast-lesion-classification criteria in use today. DOI: http://dx.doi.org/10.3329/bjmp.v4i1.14672 Bangladesh Journal of Medical Physics Vol.4 No.1 2011 1-10

Objective Assessment of Sonographic: Quality II Acquisition Information Spectrum

This paper describes a task-based, information-theoretic approach to the assessment of image quality in diagnostic sonography. We expand the Kullback-Leibler divergence metric J, which quantifies the diagnostic information contained within recorded radio-frequency echo signals, into a spatial-frequency integral comprised of two spectral components: one describes patient features for low-contrast diagnostic tasks and the other describes instrumentation properties. The latter quantity is the acquisition information spectrum (AIS), which measures the density of object information that an imaging system is able to transfer to the echo data at each spatial frequency. AIS is derived based on unique properties of acoustic scattering in tissues that generate object contrast. Predictions made by the J integral expression were validated through Monte Carlo studies using echo-signal data from simulated lesions. Our analysis predicts the diagnostic performance of any sonographic system at specific diagnostic tasks based on engineering properties of the instrument that constitute image quality.

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

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

Ultrasound speed and attenuation in progressive trypsin digested articular cartilage

Subtle changes of articular cartilage (AC) can lead to tissue degeneration and even osteoarthritis (OA). The early degeneration of AC is closely related to a change in proteoglycans (PG) content. The observation of PG is therefore an appropriate way of studying OA and evaluating the degree of AC degeneration. In this study, 20 cartilage-bone samples were prepared from normal porcine femoral condyle cartilage and 10 samples were digested over 2 h using 0.25% trypsin solution. The dynamic process of PG-digestion was explored using a conventional A-mode ultrasound (US) experimental system with a 10 MHz center frequency. Quantitative acoustic parameters were calculated from ultrasonic radio-frequency echo signals and included US speed (USS), US amplitude attenuation coefficient (UAA) and broadband US attenuation coefficient (BUA). The experimental results showed that the conventional A-mode ultrasound is valuable for tracking the degree of PG-digestion. Histology also confirmed the validity of the ultrasound observations. For every AC sample, the degree of PG-digestion within a given time was different and was affected by individual differences. After two hours of degeneration, USS showed a mean decrease of 0.4% (P<0.05). UAA was significantly lower after a two-hour PG depletion period (from (2.45±0.23) to (2.28±0.41) dB mm⁻¹). BUA showed no significant differences during this process. In conclusion, conventional ultrasound can provide useful information about trypsin-induced progressive PG depletion in AC and can reflect variations of PG content via the quantitative acoustic parameters USS and UAA. The results of this study may be used to identify an indirect indicator of cartilage matrix integrity and OA disease progression.

Improving the Statistics of Quantitative Ultrasound Techniques with Deformation Compounding: An Experimental Study

Many quantitative ultrasound (QUS) techniques are based on estimates of the radio-frequency (RF) echo signal power spectrum. Historically, reliable spectral estimates required spatial averaging over large regions-of-interest (ROIs). Spatial compounding techniques have been used to obtain robust spectral estimates for data acquired over small regions of interest. A new technique referred to as “deformation compounding” is another method for providing robust spectral estimates over smaller regions of interest. Motion tracking software is used to follow an ROI while the tissue is deformed (typically by pressing with the transducer). The deformation spatially reorganizes the scatterers so that the resulting echo signal is decorrelated. The RF echo signal power spectrum for the ROI is then averaged over several frames of RF echo data as the tissue is deformed, thus, undergoing deformation compounding. More specifically, averaging spectral estimates among the uncorrelated RF data acquired following small deformations allows reduction in the variance of the power spectral density estimates and, thereby, improves accuracy of spectrum-based tissue property estimation. The viability of deformation compounding has been studied using phantoms with known attenuation and backscatter coefficients. Data from these phantoms demonstrates that a deformation of about 2% frame-to-frame average strain is sufficient to obtain statistically-independent echo signals (with correlations of less than 0.2). Averaging five such frames, where local scatterer reorganization has taken place due to mechanical deformations, reduces the average percent standard deviation among power spectra by 26% and averaging 10 frames reduces the average percent standard deviation by 49%. Deformation compounding is used in this study to improve measurements of backscatter coefficients. These tests show deformation compounding is a promising method to improve the accuracy of spectrum-based quantitative ultrasound for tissue characterization.

Reliability of Quantitative Ultrasonic Assessment of Normal-Tissue Toxicity in Breast Cancer Radiotherapy

We have recently reported that ultrasound imaging, together with ultrasound tissue characterization (UTC), can provide quantitative assessment of radiation-induced normal-tissue toxicity. This study's purpose is to evaluate the reliability of our quantitative ultrasound technology in assessing acute and late normal-tissue toxicity in breast cancer radiotherapy. Our ultrasound technique analyzes radiofrequency echo signals and provides quantitative measures of dermal, hypodermal, and glandular tissue toxicities. To facilitate easy clinical implementation, we further refined this technique by developing a semiautomatic ultrasound-based toxicity assessment tool (UBTAT). Seventy-two ultrasound studies of 26 patients (720 images) were analyzed. Images of 8 patients were evaluated for acute toxicity (<6 months postradiotherapy) and those of 18 patients were evaluated for late toxicity (≥ 6 months postradiotherapy). All patients were treated according to a standard radiotherapy protocol. To assess intraobserver reliability, one observer analyzed 720 images in UBTAT and then repeated the analysis 3 months later. To assess interobserver reliability, three observers (two radiation oncologists and one ultrasound expert) each analyzed 720 images in UBTAT. An intraclass correlation coefficient (ICC) was used to evaluate intra- and interobserver reliability. Ultrasound assessment and clinical evaluation were also compared. Intraobserver ICC was 0.89 for dermal toxicity, 0.74 for hypodermal toxicity, and 0.96 for glandular tissue toxicity. Interobserver ICC was 0.78 for dermal toxicity, 0.74 for hypodermal toxicity, and 0.94 for glandular tissue toxicity. Statistical analysis found significant changes in dermal (p < 0.0001), hypodermal (p = 0.0027), and glandular tissue (p < 0.0001) assessments in the acute toxicity group. Ultrasound measurements correlated with clinical Radiation Therapy Oncology Group (RTOG) toxicity scores of patients in the late toxicity group. Patients with RTOG Grade 1 or 2 had greater ultrasound-assessed toxicity percentage changes than patients with RTOG Grade 0. Early and late radiation-induced effects on normal tissue can be reliably assessed using quantitative ultrasound.

Ultrasonic Multi-Feature Analysis Procedure for Computer-Aided Diagnosis of Solid Breast Lesions

We have developed quantitative descriptors to provide an objective means of noninvasive identification of cancerous breast lesions. These descriptors include quantitative acoustic features assessed using spectrum analysis of ultrasonic radiofrequency (rf) echo signals and morphometric properties related to lesion shape. Acoustic features include measures of echogenicity, heterogeneity and shadowing, computed by generating spectral-parameter images of the lesion and surrounding tissue. Spectral-parameter values are derived from rf echo signals at each pixel using a sliding-window Fourier analysis. We derive quantitative acoustic features from spectral-parameter maps of the lesion and adjacent areas. We quantify morphometric features by geometric and fractal analysis of traced lesion boundaries. Initial results on biopsy-proven cases show that although a single parameter cannot reliably discriminate cancerous from noncancerous breast lesions, multi-feature analysis provides excellent discrimination for this data set. We have processed data for 130 biopsy-proven patients, acquired during routine ultrasonic examinations at three clinical sites and produced an area under the receiver-operating-characteristics (ROC) curve of 0.947 +/- 0.045. Among the quantitative descriptors, lesion-margin definition, spiculation and border irregularity are the most useful; some additional morphometric features (such as border irregularity) also are particularly effective in lesion classification. Our findings are consistent with many of the BI-RADS (Breast Imaging Reporting and Data System) breast-lesion-classification criteria in use today.

Computer Aided Diagnosis of Parotid Gland Lesions Using Ultrasonic Multi-Feature Tissue Characterization

In this article, an ultrasound based system for computer aided characterization of biologic tissue and its application to differential diagnosis of parotid gland lesions is proposed. Aiming at an automated differentiation between malignant and benign cases, the system is based on a supervised classification using tissue-describing features derived from ultrasound radio-frequency (RF) echo signals and image data. Standard diagnostic ultrasound equipment was employed to acquire ultrasound RF echo data from parotid glands of 138 patients. Lesions were manually demarcated as regions-of-interest (ROIs) in the B-mode images. Spectral ultrasound backscatter and attenuation parameters are estimated from diffraction corrected RF data, yielding spatially resolved parameter images. Histogram based statistical measures derived from the parameters distributions inside the ROI are used as tissue describing features. In addition, texture features and shape descriptors are extracted from demodulated ultrasound image data. The features are processed by a maximum likelihood classifier. An optimal set of 10 features was chosen by a sequential forward selection algorithm. The classifier’s performance is evaluated using total cross validation and receiver operating characteristic (ROC) analysis. As a reference method, postoperative pathohistologic analysis was conducted and proved malignancy or prospective malignancy in 51 patients. The classification using the proposed system yielded an area under the ROC curve of 0.91, proving significant potential for differentiating between malignant and benign parotid gland lesions. (E-mail: stefan.siebers@rub.de)

Tissue typing using ultrasound RF time series: Experiments with animal tissue samples

This article provides experimental evidence to show that the time series of radiofrequency (RF) ultrasound data can be used for tissue typing. It also explores the tissue typing information in RF time series. Clinical and high-frequency ultrasound are studied. Bovine liver, pig liver, bovine muscle, and chicken breast were used in the experiments as the animal tissue types. In the proposed approach, the authors record RF echo signals backscattered from tissue, while the imaging probe and the tissue are stationary. This sequence of recorded RF data generates a time series of RF echoes for each spatial sample of the RF signal. The authors use spectral and fractal features of ultrasound RF time series averaged over a region of interest, along with feedforward neural networks for tissue typing. The experiments are repeated at ultrasound frequency of 6.6 and also 55 MHz. The effects of increasing power and frame rate are studied. The methodology yielded an average two-class classification accuracy of 95.1% when ultrasound data were acquired at 6.6 MHz and 98.1% when data were collected with a high-frequency probe operating at 55 MHz. In four-class classification experiments, the recorded accuracies were 78.6% and 86.5% for low and high-frequency ultrasound data, respectively. A set of 12 texture features extracted from the B-mode image equivalents of the RF data yields an accuracy of only 77.5% in typing the analyzed tissues. An increase in acoustic power and the frame rate of ultrasound results in an improvement in classification results. The results of this study demonstrate that RF time series can be used for ultrasound-based tissue typing. Further investigation of the underlying physical mechanisms is necessary.

Quantitative Ultrasonic Evaluation of Radiation-Induced Late Tissue Toxicity: Pilot Study of Breast Cancer Radiotherapy

To investigate the use of advanced ultrasonic imaging to quantitatively evaluate normal-tissue toxicity in breast-cancer radiation treatment. Eighteen breast cancer patients who received radiation treatment were enrolled in an institutional review board-approved clinical study. Radiotherapy involved a radiation dose of 50.0 to 50.4 Gy delivered to the entire breast, followed by an electron boost of 10.0 to 16.0 Gy delivered to the tumor bed. Patients underwent scanning with ultrasound during follow-up, which ranged from 6 to 94 months (median, 22 months) postradiotherapy. Conventional ultrasound images and radio-frequency (RF) echo signals were acquired from treated and untreated breasts. Three ultrasound parameters, namely, skin thickness, Pearson coefficient, and spectral midband fit, were computed from RF signals to measure radiation-induced changes in dermis, hypodermis, and subcutaneous tissue, respectively. Ultrasound parameter values of the treated breast were compared with those of the untreated breast. Ultrasound findings were compared with clinical assessment using Radiation Therapy Oncology Group (RTOG) late-toxicity scores. Significant changes were observed in ultrasonic parameter values of the treated vs. untreated breasts. Average skin thickness increased by 27.3%, from 2.05 ± 0.22 mm to 2.61 ± 0.52 mm; Pearson coefficient decreased by 31.7%, from 0.41 ± 0.07 to 0.28 ± 0.05; and midband fit increased by 94.6%, from -0.92 ± 7.35 dB to 0.87 ± 6.70 dB. Ultrasound evaluations were consistent with RTOG scores. Quantitative ultrasound provides a noninvasive, objective means of assessing radiation-induced changes to the skin and subcutaneous tissue. This imaging tool will become increasingly valuable as we continue to improve radiation therapy technique.

Implementation and validation of an ultrasonic tissue characterization technique for quantitative assessment of normal‐tissue toxicity in radiation therapy

The goal of this study was to implement and validate a noninvasive, quantitative ultrasonic technique for accurate and reproducible measurement of normal-tissue toxicity in radiation therapy. The authors adapted an existing ultrasonic tissue characterization (UTC) technique that used a calibrated 1D spectrum based on region-of-interest analysis. They modified the calibration procedure by using a reference phantom instead of a planar reflector. This UTC method utilized ultrasonic radiofrequency echo signals to generate spectral parameters related to the physical properties (e.g., size, shape, and relative acoustic impedance) of tissue microstructures. Three spectral parameters were investigated for quantification of normal-tissue injury: Spectral slope, intercept, and midband fit. They conducted a tissue-mimicking phantom study to verify the reproducibility of UTC measurements and initiated a clinical study of radiation-induced breast-tissue toxicity. Spectral parameter values from measurements on two phantoms were reproducible within 1% of each other. Eleven postradiation breast-cancer patients were studied and significant differences between the irradiated and untreated (contralateral) breasts were observed for spectral intercept (p = 0.003) and midband fit (p < 0.001) but not for slope (p = 0.14). In comparison to the untreated breast, the average difference in the spectral intercept was 2.99 +/- 0.75 dB and the average difference in the midband fit was 3.99 +/- 0.65 dB. The preliminary clinical study demonstrated the feasibility of using the quantitative ultrasonic method to evaluate normal-tissue toxicity in radiation therapy.

3D dynamic model of healthy and pathologic arteries for ultrasound technique evaluation

A 3D model reproducing the biomechanical behavior of human blood vessels is presented. The model, based on a multilayer geometry composed of right generalized cylinders, enables the representation of different vessel morphologies, including bifurcations, either healthy or affected by stenoses. Using a finite element approach, blood flow is simulated by considering a dynamic displacement of the scatterers (erythrocytes), while arterial pulsation due to the hydraulic pressure is taken into account through a fluid-structure interaction based on a wall model. Each region is acoustically characterized using FIELD II software, which produces the radio frequency echo signals corresponding to echographic scans. Three acoustic physiological phantoms of carotid arteries surrounded by elastic tissue are presented to illustrate the model's capability. The first corresponds to a healthy blood vessel, the second includes a 50% stenosis, and the third represents a carotid bifurcation. Examples of M mode, B mode and color Doppler images derived from these phantoms are shown. Two examples of M-mode image segmentation and the identification of the atherosclerotic plaque boundaries on Doppler color images are reported. The model could be used as a tool for the preliminary evaluation of ultrasound signal processing and visualization techniques.

Ultrasound frame rate requirements for cardiac elastography: Experimental and in vivo results

Cardiac elastography using radiofrequency echo signals can provide improved 2D strain information compared to B-mode image data, provided data are acquired at sufficient frame rates. In this paper, we evaluate ultrasound frame rate requirements for unbiased and robust estimation of tissue displacements and strain. Both tissue-mimicking phantoms under cyclic compressions at rates that mimic the contractions of the heart and in vivo results are presented. Sinusoidal compressions were applied to the phantom at frequencies ranging from 0.5 to 3.5 cycles/sec, with a maximum deformation of 5% of the phantom height. Local displacements and strains were estimated using both a two-step one-dimensional and hybrid two-dimensional cross-correlation method. Accuracy and repeatability of local strains were assessed as a function of the ultrasound frame rate based on signal-to-noise ratio values. The maximum signal-to-noise ratio obtained in a uniformly elastic phantom is 20 dB for both a 1.26 Hz and a 2 Hz compression frequency when the radiofrequency echo acquisition is at least 12 Hz and 20 Hz respectively. However, for compression frequencies of 2.8 Hz and 4 Hz the maximum signal-to-noise ratio obtained is around 16 dB even for a 40 Hz frame rate. Our results indicate that unbiased estimation of displacements and strain require ultrasound frame rates greater than ten times the compression frequency, although a frame rate of about two times the compression frequency is sufficient to estimate the compression frequency imparted to the tissue-mimicking phantom. In vivo results derived from short-axis views of the heart acquired from normal human volunteers also demonstrate this frame rate requirement for elastography.

SU‐EE‐A4‐06: Estimation of the Optimal Maximum Beam Angle and Angular Increment for Normal and Shear Strain Estimation

Purpose: In current ultrasound elastography, only the axial component of the displacement vector is estimated and used to produce strain images. Previously we had proposed a method to estimate both the axial and lateral components of a displacement vector using radiofrequency echo signal data acquired along multiple angular insonification directions of the ultrasound beam. In this study, we present error propagation through the least square fitting process for optimization of the angular increment and maximum beam steered angle. Method and Materials: Ultrasound simulations are performed to corroborate theoretical predictions of the optimal values for the maximum beam angle and angular increment. Beam steering characteristics of the linear array were simulated by selecting appropriate time delays for each element which determines the focal point and steering angle for the beam. A uniformly elastic phantom was simulated by modeling a random distribution of 50 μm polystyrene beads with an average concentration of 9.7/mm3 in a medium (to simulate Rayleigh scattering). After computing RF signals for each insonification angle, the phantom was deformed by a uniaxial compression (1% of the phantom height). The displacement of each scatterer in the phantom was calculated using the Finite Element Analysis (FEA) software ANSYS. The new scatterer positions were used for calculating the post compression echo signals at each insonification angle. Results: The theoretical prediction matches well with numerical simulations. For typical system parameters, the optimal maximum beam angle is around 10‐deg for axial strain estimation, and around 15‐deg for lateral strain estimation. The optimal angular increment is around 4∼6 deg, which indicates that only 5∼7 beam angles are required for this strain tensor estimation technique. Conclusion: The theory presented in this study is useful for choosing optimal parameters for the angular data acquisition process for strain tensor estimation.

Automatic recognition of the common carotid artery in longitudinal ultrasound B-mode scans

Many morphological and dynamic properties of the common carotid artery (CCA), e.g. lumen diameter, distension and wall thickness, can be measured non-invasively with ultrasound (US) techniques. As common to other medical image segmentation processes, this requires as a preliminary step the manual recognition of the artery of interest within the ultrasound image. In real-time US imaging, such manual initialization procedure interferes with the difficult task of the sonographer to select and maintain a proper image scan plane. Even for off-line US segmentation the requirement for human supervision and interaction precludes full automation. To eliminate user interference and to speed up processing for both real-time and off-line applications, we developed an algorithm for the automatic artery recognition in longitudinal US scans of the CCA. It acts directly on the envelopes of received radio frequency echo signals, eventually composing the ultrasound image. In order to properly exploit the information content of the arterial structure the envelopes are decimated, according to the two-dimensional resolution characteristics of the echo system, thereby substantially decreasing computational load. Subsequently, based upon the expected diameter range and a priori knowledge of the typical pattern in the echo envelope of the arterial wall-lumen complex, parametrical template matching is performed, resulting in the location of the lumen position along each echo line considered. Finally, in order to reject incorrect estimates, a spatial and temporal clustering method is applied. Adequate values for the parameters involved in the processing are obtained via off-line testing of the proposed algorithm on 128 echo data recordings from 45 subjects. Using those robust parameter values, correct and fast recognition of the artery is achieved in more than 98% of the 6185 processed frames. Since these results are obtained via rigorous data decimation and using a cascade of rather simple steps, the proposed automatic algorithm is suitable for real-time recognition of the CCA.

Quantitative Assessment of Radiation Therapy Associated Breast Tissue Toxicity

To investigate the use of ultrasound tissue characterization (UTC) imaging to quantitatively evaluate normal tissue toxicity in breast cancer radiation treatment. For women with early stage breast cancer, breast-conservation surgery in combination with radiation therapy is an effective treatment. However, efficacy of radiation therapy is limited by radiation injury to normal tissue. There is currently no objective means of measuring breast tissue injury/toxicity in the clinic. We investigated the use of UTC to examine skin and subcutaneous tissue of the breast. Twenty two breast cancer patients were enrolled. All patients received a standard course of radiation: the whole breast received 50–50.4 Gy followed by an electron boost of 10–16 Gy at the lumpectomy site. Follow up time was 6 to 94 months with a median of 22 months. Patients were scanned with a clinical Ultrasonix® scanner in a supine position. Radio-frequency echo signals were acquired from the treated and the contra-lateral breast. Our UTC technique analyzes the RF signals and extracts spectral features that are associated with properties of tissue microstructures. Four UTC parameters were computed to quantitatively measure toxicity: skin thickness, UTC slope, intercept and midband fit (MBF). Statistical analysis was performed to correlate the UTC findings with clinical assessments (RTOG clinical toxicity scale). UTC measurements for the treated breast were compared with the contra-lateral (untreated) breast for quantitative assessment of normal tissue radiation toxicity. Two breast images are shown in the Figure: (a) treated right breast and (b) untreated left breast. The skin thickening (arrows) and hyper-echogenecity of the fat were observed. The plot on the right is the UTC 1-D power spectra. For all patients, the average thickness of the treated breast skin is 2.50 ± 0.82 mm while untreated skin is 1.68 ± 0.62 mm. For the underlying tissue, there are significant changes for the treated breast in the UTC intercept (p = 0.017) and midband fit (p = 0.002), except slope (p = 0.077). Changes in midband fit were primarily related to soft tissue stiffness, which correlates the presence of fibrosis. The UTC evaluations were consistent with the clinical breast toxicity assessments. Ultrasound tissue characterization provides an objective quantitative method of assessing radiation damage to the skin and the underlying breast tissue. This tool will become increasingly valuable as we evaluate new strategies for breast cancer radiation therapy.