Ultrasonic Nakagami Imaging: A Strategy to Visualize the Scatterer Properties of Benign and Malignant Breast Tumors

Previous studies have demonstrated the usefulness of the Nakagami parameter in characterizing breast tumors by ultrasound. However, physicians or radiologists may need imaging tools in a clinical setting to visually identify the properties of breast tumors. This study proposed the ultrasonic Nakagami image to visualize the scatterer properties of breast tumors and then explored its clinical performance in classifying benign and malignant tumors. Raw data of ultrasonic backscattered signals were collected from 100 patients (50 benign and 50 malignant cases) using a commercial ultrasound scanner with a 7.5 MHz linear array transducer. The backscattered signals were used to form the B-scan and the Nakagami images of breast tumors. For each tumor, the average Nakagami parameter was calculated from the pixel values in the region-of-interest in the Nakagami image. The receiver operating characteristic (ROC) curve was used to evaluate the clinical performance of the Nakagami image. The results showed that the Nakagami image shadings in benign tumors were different from those in malignant cases. The average Nakagami parameters for benign and malignant tumors were 0.69 ± 0.12 and 0.55 ± 0.12, respectively. This means that the backscattered signals received from malignant tumors tend to be more pre-Rayleigh distributed than those from benign tumors, corresponding to a more complex scatterer arrangement or composition. The ROC analysis showed that the area under the ROC curve was 0.81 ± 0.04 and the diagnostic accuracy was 82%, sensitivity was 92% and specificity was 72%. The results showed that the Nakagami image is useful to distinguishing between benign and malignant breast tumors.     

Changes in Backscattered Ultrasonic Envelope Statistics as a Function of Thrombus Age: An in Vitro Study

It is necessary to determine the age of thrombi in planning clinical treatment for thrombolysis. Ultrasound imaging can potentially be used to evaluate thrombus age in real time. The backscattered signals from thrombi may contain useful information regarding their age. On the basis of the randomness of ultrasound backscattering, this study explored changes in backscattered US statistics as a function of thrombus age. Porcine blood samples were used for the in vitro induction of fresh thrombi (day 0) with hematocrits ranging from 0%–40% and aged thrombi (days 0–8) with a hematocrit of 40%. Each thrombus was imaged using a pulse-echo ultrasound scanner equipped with a 7.5-MHz linear array transducer to acquire raw backscattered signals for B-mode and Nakagami imaging, by which the backscattered statistics were visualized. Hematoxylin and eosin staining and scanning electron microscopy were used to observe the histology of fresh and aged thrombi. The results indicated that a decrease in the number of red blood cells in the thrombus caused by the aging effect was observed in the in vitro model, indicating that the proposed model could simulate the structural changes in the thrombus during aging. Compared with fresh thrombi with various hematocrits, the aged thrombi exhibited a trend toward more substantial decreases in the Nakagami parameter with increasing thrombus age (the Nakagami parameter decreased from 1.1 to 0.6 as thrombus age increased from day 0 to day 8), indicating that thrombus aging causes the backscattered statistics to follow a pre-Rayleigh distribution to a high degree. This finding may be applied to the determination of thrombus age using conventional ultrasound imaging in the future.     

Nakagami–m Parametric Imaging for Atherosclerotic Plaque Characterization Using the Coarse-to-Fine Method

The Nakagami model was used to analyze the statistical differences in ultrasound backscattered signals between different plaque types. To improve image resolution, Nakagami-m parametric imaging using the coarse-to-fine method based on the maximum likelihood estimation (CTF-BOW) was proposed for atherosclerotic plaque characterization. Simulation results confirmed that the CTF-BOW method significantly outperforms the sliding window method in precision, smoothness and resolution. Preliminary in vivo results (n = 45) indicated that the ranges of the m parameters for calcified, mixed and echolucent plaques are, respectively, 0.2852–0.5225, 0.6532–0.8784 and 0.8908–1.4011, with no overlap. Results revealed that the CTF-BOW method significantly improves image resolution without sacrificing accuracy and can distinguish between calcified, mixed and echolucent plaques. Moreover, it was found that the parameter m is related to the composition of the plaque, indicating that Nakagami-m parametric imaging has the potential to characterize plaques.     

Use of Nakagami Statistics and Empirical Mode Decomposition for Ultrasound Tissue Characterization by a Nonfocused Transducer

The Nakagami parameter associated with the Nakagami distribution estimated from ultrasonic backscattered signals reflects the scatterer concentration in a tissue. A nonfocused transducer does not allow tissue characterization based on the Nakagami parameter. This paper proposes a new method called the noise-assisted Nakagami parameter based on empirical mode decomposition of noisy backscattered echoes to allow quantification of the scatterer concentration based on data obtained using a nonfocused transducer. To explore the practical feasibility of the proposed method, the current study performed experiments on phantoms and measurements on rat livers in vitro with and without fibrosis induction. The results show that using a nonfocused transducer makes it possible to use the noise-assisted Nakagami parameter to classify phantoms with different scatterer concentrations and different stages of liver fibrosis in rats more accurately than when using techniques based on the echo intensity and the conventional Nakagami parameter. However, the conventional Nakagami parameter and the noise-assisted Nakagami parameter have different meanings: the former represents the statistics of signals backscattered from unresolvable scatterers, whereas the latter is associated with stronger resolvable scatterers or local inhomogeneity caused by scatterer aggregation. (E-mail: mechang@gate.sinica.edu.tw; mcho1215@ntu.edu.tw)     

Ultrasound Detection of Liver Fibrosis in Individuals with Hepatic Steatosis Using the Homodyned K Distribution

Acoustic structure quantification (ASQ) based on the analysis of ultrasound backscattered statistics has been reported to detect liver fibrosis without significant hepatic steatosis. This study proposed using ultrasound parametric imaging based on the parameter α of the homodyned K (HK) distribution for staging liver fibrosis in patients with significant hepatic steatosis. Raw ultrasound image data were acquired from patients (n = 237) to construct B-mode and HK α parametric images, which were compared with the focal disturbance (FD) ratio obtained from ASQ on the basis of histologic evidence (METAVIR fibrosis score and hepatic steatosis severity). The data were divided into group I (n = 173; normal to mild hepatic steatosis) and group II (n = 64; with moderate to severe hepatic steatosis) for statistical analysis through one-way analysis of variance and receiver operating characteristic (ROC) curve analysis. The results showed that the HK α parameter monotonically decreased as the liver fibrosis stage increased (p < .05); concurrently, the FD ratio increased (p < .05). For group I, the areas under the ROC (AUROCs) obtained using the FD ratio and the α parameter (AUROC_FD and AUROC_α) were, respectively, 0.56 and 0.55, 0.68 and 0.68, 0.64 and 0.64 and 0.62 and 0.62 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. The values of AUROC_FD and AUROC_α for group II were, respectively, 0.88 and 0.91, 0.81 and 0.81, 0.77 and 0.76 and 0.78 and 0.73 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. As opposed to previous studies, ASQ was found to fail in characterizing liver fibrosis in group I; however, it was workable for identifying liver fibrosis in patients with significant hepatic steatosis (group II). Compared with ASQ, HK imaging provided improved diagnostic performance in the early detection of liver fibrosis coexisting with moderate to severe hepatic steatosis. Ultrasound HK imaging is recommended as a strategy to evaluate early fibrosis risk in patients with significant hepatic steatosis.     

Performance evaluation of ultrasonic Nakagami image in tissue characterization

Conventional ultrasonic B-mode images qualitatively describe tissue structures but are unsuitable for quantitative analyses of scatterer properties. We have recently developed an ultrasonic parametric imaging technique based on the Nakagami statistical distribution that is able to quantify scatterer concentrations. The aim of the present study is to further explore both the behavior of a Nakagami image in characterizing different scatterer structures at different signal-to-noise ratios (SNRs) and the feasibility of Nakagami imaging using a general commercial ultrasound scanner for tissue examinations. Simulations, experiments on a tissue-mimicking phantom and in vitro measurements on a muscle tissue before and after microwave treatment were carried out. The SNR and contrast-to-noise ratio (CNR) were estimated to quantify image performance. The results demonstrate that a Nakagami image can differentiate different scatterer concentrations for single, hypoechoic and hyperechoic targets. Also, a Nakagami image, when combined with an ultrasound scanner, can complement the B-scan to characterize tissue and to identify the region of interest with a larger CNR. However, the noise effect can degrade the performance of a Nakagami image. When the signal SNR decreased to 15 dB in simulations and to 8 dB in experiments, the CNR of the hyperechoic Nakagami image decreased by 4% and 27%, respectively, and that of the hypoechoic one decreased by 42% and 80%, respectively. These results indicate that a Nakagami image behaves well in identifying regions with high scatterer concentrations but does not perform well when both the scatterer concentration and SNR are low.     

Statistical variations of ultrasound signals backscattered from flowing blood

The statistical distributions of ultrasonic signals backscattered from blood have recently been used to characterize hemodynamic properties, such as red blood cell (RBC) aggregation and blood coagulation. However, a thorough understanding of the relationship between blood properties and the statistical behavior of signals backscattered from flowing blood is still lacking. This prompted us to use the statistical parameter to characterize signals backscattered from both whole blood and RBC suspensions at different flow velocities (from 10 to 60 cm/s) and hematocrits (from 20% to 50%) under a steady laminar flow condition. The Nakagami parameter, scaling parameter, backscatter amplitude profile and flow velocity profile across a flow tube were acquired using a 10 MHz focused ultrasonic transducer. The backscattered signal peaked approximately at the centerline of the flow tube due to the effects of RBC aggregation, with the peak value increasing as the flow velocity of whole blood decreased. The Nakagami parameter increased from 0.45 to 0.78 as the flow velocity increased from 10 to 60 cm/s. The probability density function (PDF) of signals backscattered from flowing whole blood conformed with a pre-Rayleigh distribution. The Nakagami parameter was close to 1 for signals backscattered from RBC suspensions at all the flow velocities and hematocrits tested, for which the PDF was Rayleigh distributed. These differences in the statistical distributions of backscattered signals between whole blood and RBC suspensions suggest that variations in the size of dynamic scatterers in the flow affect the shape of the backscattered signal envelope, which should be considered in future statistical models used to characterize blood properties. (E-mail: j648816n@ms23.hinet.net and shyhhau@cycu.edu.tw)     

Early Detection of Liver Fibrosis in Rats Using 3-D Ultrasound Nakagami Imaging: A Feasibility Evaluation

We investigated the feasibility of using 3-D ultrasound Nakagami imaging to detect the early stages of liver fibrosis in rats. Fibrosis was induced in livers of rats (n = 60) by intraperitoneal injection of 0.5% dimethylnitrosamine (DMN). Group 1 was the control group, and rats in groups 2–6 received DMN injections for 1–5 weeks, respectively. Each rat was sacrificed to perform 3-D ultrasound scanning of the liver in vitro using a single-element transducer of 6.5 MHz. The 3-D raw data acquired at a sampling rate of 50 MHz were used to construct 3-D Nakagami images. The liver specimen was further used for histologic analysis with hematoxylin and eosin and Masson staining to score the degree of liver fibrosis. The results indicate that the Metavir scores of the hematoxylin and eosin-stained sections in Groups 1–4 were 0 (defined as early liver fibrosis in this study), and those in groups 5 and 6 ranged from 1 to 2 and 2 to 3, respectively. To quantify the degree of early liver fibrosis, the histologic sections with Masson stain were analyzed to calculate the number of fiber-related blue pixels. The number of blue pixels increased from (2.36 ± 0.79) × 10⁴ (group 1) to (7.68 ± 2.62) × 10⁴ (group 4) after DMN injections for 3 weeks, indicating that early stages of liver fibrosis were successfully induced in rats. The Nakagami parameter increased from 0.36 ± 0.02 (group 1) to 0.55 ± 0.03 (group 4), with increasing numbers of blue pixels in the Masson-stained sections (p-value < 0.05, t-test). We concluded that 3-D Nakagami imaging has potential in the early detection of liver fibrosis in rats and may serve as an image-based pathologic model to visually track fibrosis formation and growth.     

Minimum requirement of artificial noise level for using noise-assisted correlation algorithm to suppress artifacts in ultrasonic Nakagami images

The Nakagami image is a complementary imaging mode for pulse-echo ultrasound B-scan to characterize tissues. White noise in anechoic areas induces artifacts in the Nakagami image. Recently, we proposed a noise-assisted correlation algorithm (NCA) for suppressing the Nakagami artifact. In the NCA, artificial white noise is intentionally added twice to backscattered signals to produce two noisy data, which are used to establish a correlation profile for rejecting noise. This study explored the effects of artificial noise level on the NCA to suppress the artifact of the Nakagami image. Simulations were conducted to produce B-mode images of anechoic regions under signal-to-noise ratios (SNRs) of 20, 10 and 5 dB. Various artificial noise levels ranging from 0.1- to 1-fold of the intrinsic noise amplitude were used in the NCA for constructing the Nakagami images. Phantom experiments were conducted to validate the performance of using the optimal artificial noise level suggested by the simulation results to suppress the Nakagami artifacts by the NCA. The simulation results indicated that the artifacts of the Nakagami image in the anechoic regions can be gradually suppressed by increasing the artificial noise level used in the NCA to improve the image contrast-to-noise ratio (CNR). The CNR of the Nakagami image reached 20 dB when the artificial noise level was 0.7-fold of the intrinsic noise amplitude. This criterion was demonstrated by the phantom results to provide the NCA with an excellent ability to obtain artifact-free Nakagami images.     

Imaging local scatterer concentrations by the Nakagami statistical model

The ultrasonic B-mode image is an important clinical tool used to examine the internal structures of the biological tissue. Due to the fact that the conventional B-scans cannot fully reflect the nature of the tissue, some useful quantitative parameters have been applied to quantify the properties of the tissue. Among various possibilities, the Nakagami parameter was demonstrated to have an outstanding ability to detect the variation of the scatterer concentration. This study is aimed to develop a scatterer concentration image based on the Nakagami parameter map to assist in the B-mode image for tissue characterization. In particular, computer simulations are carried out to generate phantoms of different scatterer concentrations and echogenicity coefficients and their B-mode and Nakagami parametric images are compared to evaluate the performance of the Nakagami image in differentiating the properties of the scatterers. The simulated results show that the B-mode image would be affected by the system settings and user operations, whereas the Nakagami parametric image provides a comparatively consistent image result when different diagnosticians use different dynamic ranges and system gains. This is largely because the Nakagami image formation is only based on the backscattered statistics of the ultrasonic signals in local tissues. Such an imaging principle allows the Nakagami image to quantify the local scatterer concentrations in the tissue and to extract the backscattering information from the regions of the weaker echoes that may be lost in the B-mode image. These findings suggest that the Nakagami image can be combined with the use of the B-mode image simultaneously to visualize the tissue structures and the scatterer properties for a better medical diagnosis.     

Effect of Microbubble-Enhanced Ultrasound on Radiofrequency Ablation of Rabbit Liver

Microbubble-enhanced ultrasound (MEUS) can non-invasively disrupt and block liver blood perfusion. It may potentially overcome the heat sink effect during a thermal ablation and consequently enhance radiofrequency ablation (RFA) of the liver. We propose a new strategy combining RFA with MEUS. For ultrasound treatment, an 831-kHz air-backed focused transducer directed 400-cycle bursts at 4.3?MPa to the liver at a 9-Hz rate. The treatment was nucleated by a lipids microbubble forming MEUS. Eighteen surgically exposed rabbit livers were treated using MEUS combined with RFA; the other 32 livers were treated using MEUS (n?=?14) or RFA (n?=?18) alone and served as the controls. Contrast ultrasound imaging confirmed that MEUS treatment significantly reduced liver blood perfusion by cutting contrast peak intensities in half (44.7%–54.1%) without severe liver function damage. The ablated liver volume treated using MEUS combined with RFA was 2.8 times greater than that treated using RFA alone. In conclusion, RFA of the liver can be safely and greatly enhanced by combination with MEUS pre-treatment.     

Modeling of Errors in Nakagami Imaging: Illustration on Breast Mass Characterization

Nakagami imaging is an attractive tissue characterization method, as the parameter estimated at each location is related to properties of the tissues. The application to clinical ultrasound images is problematic, as the estimation of the parameters is disturbed by the presence of complex structures. We propose to consider separately the different aspects potentially affecting the value of the Nakagami parameters and quantify their effects on the estimation. This framework is applied to the classification of breast masses. Quantitative parameters are computed on two groups of ultrasound images of benign and malignant tumors. A statistical analysis of the result indicated that the previously observed difference between average values of the Nakagami parameters is explained mostly by estimation errors. In the future, new methods for reliable computation of Nakagami parameters need to be developed, and factors of error should be considered in studies using Nakagami parameters.     

In vivo Ultrafast Quantitative Ultrasound and Shear Wave Elastography Imaging on Farm-Raised Duck Livers during Force Feeding

Shear wave elastography (speed and dispersion), local attenuation coefficient slope and homodyned-K parametric imaging were used for liver steatosis grading. These ultrasound biomarkers rely on physical interactions between shear and compression waves with tissues at both macroscopic and microscopic scales. These techniques were applied in a context not yet studied with ultrasound imaging, that is, monitoring steatosis of force-fed duck livers from pre-force-fed to foie gras stages. Each estimated feature presented a statistically significant trend along the feeding process (p values <10^–3). However, whereas a monotonic increase in the shear wave speed was observed along the process, most quantitative ultrasound features exhibited an absolute maximum value halfway through the process. As the liver fat fraction in foie gras is much higher than that seen clinically, we hypothesized that a change in the ultrasound scattering regime is encountered for high-fat fractions, and consequently, care has to be taken when applying ultrasound biomarkers to grading of severe states of steatosis.     

Statistics of Boundaries in Ultrasonic B-Scan Images

The existence of edges and boundaries in regions of interest (ROIs) in B-scan images alters the statistics of the backscattered echo from the ROI. Boundaries are the result of at least two different types of scattering scenarios in tissue, and the Nakagami model, which is being used extensively in ultrasound, is unlikely to fit the statistics of the backscattered echo under these conditions. Furthermore, there are very few other statistical models exist that describe the statistics of the backscattered echo from regions containing boundaries. In this work, the gamma mixture density and the recently proposed McKay density are explored as two viable models to fill this void. Justifications of these models are presented along with methods for estimating their parameters. Random number simulations and studies on tissue-mimicking phantoms indicate that the McKay and gamma mixture densities are the best for the modeling of the backscattered echo intensity when boundaries are present in the regions of interest.     

Ex vivo Study of Quantitative Ultrasound Parameters in Fatty Rabbit Livers

Nonalcoholic fatty liver disease (NAFLD) affects more than 30% of Americans, and with increasing problems of obesity in the United States, NAFLD is poised to become an even more serious medical concern. At present, accurate classification of steatosis (fatty liver) represents a significant challenge. In this study, the use of high-frequency (8 to 25 MHz) quantitative ultrasound (QUS) imaging to quantify fatty liver was explored. QUS is an imaging technique that can be used to quantify properties of tissue giving rise to scattered ultrasound. The changes in the ultrasound properties of livers in rabbits undergoing atherogenic diets of varying durations were investigated using QUS. Rabbits were placed on a special fatty diet for 0, 3, or 6 weeks. The fattiness of the livers was quantified by estimating the total lipid content of the livers. Ultrasonic properties, such as speed of sound, attenuation, and backscatter coefficients, were estimated in ex vivo rabbit liver samples from animals that had been on the diet for varying periods. Two QUS parameters were estimated based on the backscatter coefficient: effective scatterer diameter (ESD) and effective acoustic concentration (EAC), using a spherical Gaussian scattering model. Two parameters were estimated based on the backscattered envelope statistics (the k parameter and the μ parameter) according to the homodyned K distribution. The speed of sound decreased from 1574 to 1565 m/s and the attenuation coefficient increased from 0.71 to 1.27 dB/cm/MHz, respectively, with increasing fat content in the liver. The ESD decreased from 31 to 17 μm and the EAC increased from 38 to 63 dB/cm³ with increasing fat content in the liver. A significant increase in the μ parameter from 0.18 to 0.93 scatterers/mm³ was observed with increasing fat content in the liver samples. The results of this study indicate that QUS parameters are sensitive to fat content in the liver.     

Comparative Study of Raw Ultrasound Data Representations in Deep Learning to Classify Hepatic Steatosis

Adiposity accumulation in the liver is an early-stage indicator of non-alcoholic fatty liver disease. Analysis of ultrasound (US) backscatter echoes from liver parenchyma with deep learning (DL) may offer an affordable alternative for hepatic steatosis staging. The aim of this work was to compare DL classification scores for liver steatosis using different data representations constructed from raw US data. Steatosis in N = 31 patients with confirmed or suspected non-alcoholic fatty liver disease was stratified based on fat-fraction cutoff values using magnetic resonance imaging as a reference standard. US radiofrequency (RF) frames (raw data) and clinical B-mode images were acquired. Intermediate image formation stages were modeled from RF data. Power spectrum representations and phase representations were also calculated. Co-registered patches were used to independently train 1-, 2- and 3-D convolutional neural networks (CNNs), and classifications scores were compared with cross-validation. There were 67,800 patches available for 2-D/3-D classification and 1,830,600 patches for 1-D classification. The results were also compared with radiologist B-mode annotations and quantitative ultrasound (QUS) metrics. Patch classification scores (area under the receiver operating characteristic curve [AUROC]) revealed significant reductions along successive stages of the image formation process (p < 0.001). Patient AUROCs were 0.994 for RF data and 0.938 for clinical B-mode images. For all image formation stages, 2-D CNNs revealed higher patch and patient AUROCs than 1-D CNNs. CNNs trained with power spectrum representations converged faster than those trained with RF data. Phase information, which is usually discarded in the image formation process, provided a patient AUROC of 0.988. DL models trained with RF and power spectrum data (AUROC = 0.998) provided higher scores than conventional QUS metrics and multiparametric combinations thereof (AUROC = 0.986). Radiologist annotations indicated lower hepatic steatosis classification accuracies (Acc = 0.914) with respect to magnetic resonance imaging proton density fat fraction that DL models (Acc = 0.989). Access to raw ultrasound data combined with artificial intelligence techniques may offer superior opportunities for quantitative tissue diagnostics than conventional sonographic images.     

Utilizing Contrast-Enhanced Ultrasound Imaging for Evaluating Fatty Liver Disease Progression in Pre-clinical Mouse Models

We developed a protocol to investigate and optimize the application of contrast-enhanced ultrasound (CEUS) to non-invasive diagnosis of progressing fatty liver disease in mouse models. Eighteen 4-wk-old male C57 L/J mice were randomly assigned to one of the three groups and placed on a control diet, high-fat diet or non-alcoholic steatohepatitis diet for the next 10 wk. After 14 wk, B-mode imaging and CEUS imaging using a VisualSonics Vevo2100 system were performed. CEUS imaging and data analysis using three different parameters—peak enhancement, wash-in rate and wash-in perfusion index—revealed a significant decrease in representative blood flow in the high-fat diet group versus controls and a further significant decrease in the non-alcoholic steatohepatitis group (p < 0.001; n?=?6/group). In conclusion, compared with B-mode imaging, non-targeted CEUS imaging was more sensitive in diagnosing early-stage fatty infiltration-mediated vascularity changes in liver parenchyma and provided a more accurate steatohepatitis diagnosis in mouse models.     

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.     

Effect of adaptive threshold filtering on ultrasonic nakagami parameter to detect variation in scatterer concentration

The Nakagami parameter is associated with the Nakagami distribution estimated from ultrasonic backscattered signals and closely reflects the scatterer concentrations in tissues. There is an interest in exploring the possibility of enhancing the ability of the Nakagami parameter to characterize tissues. In this paper, we explore the effect of adaptive thresholdfiltering based on the noise-assisted empirical mode decomposition of the ultrasonic backscattered signals on the Nakagami parameter as a function of scatterer concentration for improving the Nakagami parameter performance. We carried out phantom experiments using 5 MHz focused and nonfocused transducers. Before filtering, the dynamic ranges of the Nakagami parameter, estimated using focused and nonfocused transducers between the scatterer concentrations of 2 and 32 scatterers/mm3, were 0.44 and 0.1, respectively. After filtering, the dynamic ranges of the Nakagami parameter, using the focused and nonfocused transducers, were 0.71 and 0.79, respectively. The experimental results showed that the adaptive threshold filter makes the Nakagami parameter measured by a focused transducer more sensitive to the variation in the scatterer concentration. The proposed method also endows the Nakagami parameter measured by a nonfocused transducer with the ability to differentiate various scatterer concentrations. However, the Nakagami parameters estimated by focused and nonfocused transducers after adaptive threshold filtering have different physical meanings: the former represents the statistics of signals backscattered from unresolvable scatterers while the latter is associated with stronger resolvable scatterers or local inhomogeneity due to scatterer aggregation.     

二维超声图像定量诊断脂肪肝病变程度的应用研究

目的　初步探讨二维超声图像定量诊断脂肪肝病变程度的应用价值。方法　应用DFY型超声图像定量分析仪和TOSHIBAPV 80 0 0型彩超对病理确诊的脂肪肝实质回声强度 (echointensity ,EI)值进行定量分析。结果　近场肝实质EI值随脂肪肝病变程度加重而变大 ,远场EI值随病变加重而变小 ;脂肪肝病变越重 ,近场与远场EI值及其比值差别越大 (P <0 .0 5 )。结论　脂肪肝实质EI值能够反映脂肪肝病变程度 ,可为临床分级诊断提供量化的客观信息