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.     

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)     

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.     

The effect of transducer characteristics on the estimation of Nakagami paramater as a function of scatterer concentration

The effect of transducer characteristics on the sensitivity of the Nakagami parameter to detect the variation of scatterer concentrations was studied. The rationale for this study stems from our pilot results which showed that the Nakagami parameters, estimated using a nonfocused transducer were not as sensitive as those of measurements using a commercial ultrasonic scanner in previous reports. This discrepancy may be attributed to the effects of transducer characteristics relative to the size of the resolution cell as verified by measurements of phantoms and 2-D computer simulations. The Nakagami parameter as a function of scatterer concentration was calculated using backscattered signals acquired from the scattering medium of different scatterer concentrations ranging from 2 to 32 scatterers/mm(3) using both 5 MHz nonfocused and focused transducers. Experimental and simulation results obtained from the nonfocused transducer represent that their respective Nakagami parameters increased from 1.17 to 1.31 and from 0.82 to 1.01 corresponding to the increase of scatterer concentrations. For the results obtained from the focused transducer, their average Nakagami parameters increased from 0.27 to 0.72 and from 0.33 to 0.81. These consistent results demonstrated that Nakagami parameter estimated using a focused transducer tends to be more sensitive than that by a nonfocused transducer to detect the variation of low scatterer concentration. This difference is fully due to the effect of transducer characteristics associated with the effective number of scatterers in the resolution cell.     

Feasibility of Using Ultrasonic Nakagami Imaging for Monitoring Microwave-Induced Thermal Lesion in Ex Vivo Porcine Liver

The feasibility of using ultrasonic Nakagami imaging to evaluate thermal lesions induced by microwave ablation (MWA) in ex vivo porcine liver was explored. Dynamic changes in echo amplitudes and Nakagami parameters in the region of the MWA-induced thermal lesion, as well as the contrast-to-noise ratio (CNR) between the MWA-induced thermal lesion and the surrounding normal tissue, were calculated simultaneously during the MWA procedure. After MWA exposure, a bright hyper-echoic region appeared in ultrasonic B-mode and Nakagami parameter images as an indicator of the thermal lesion. Mean values of the Nakagami parameter in the thermal lesion region increased to 0.58, 0.71 and 0.91 after 1, 3 and 5 min of MVA. There were no significant differences in envelope amplitudes in the thermal lesion region among ultrasonic B-mode images obtained after different durations of MWA. Unlike ultrasonic B-mode images, Nakagami images were less affected by the shadow effect in monitoring of MWA exposure, and a fairly complete hyper-echoic region was observed in the Nakagami image. The mean value of the Nakagami parameter increased from approximately 0.47 to 0.82 during MWA exposure. At the end of the postablation stage, the mean value of the Nakagami parameter decreased to 0.55 and was higher than that before MWA exposure. CNR values calculated for Nakagami parameter images increased from 0.13 to approximately 0.61 during MWA and then decreased to 0.26 at the end of the post-ablation stage. The corresponding CNR values calculated for ultrasonic B-mode images were 0.24, 0.42 and 0.17. This preliminary study on ex vivo porcine liver suggested that Nakagami imaging have potential use in evaluating the formation of MWA-induced thermal lesions. Further in vivo studies are needed to evaluate the potential application.     

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.     

Classification of breast masses in ultrasonic B-mode images using a compounding technique in the Nakagami distribution domain

Classification of masses in ultrasonic B-mode images of the breast tissue using "normalized" parameters of the Nakagami distribution was recently investigated. The technique, however, did not yield performances that were comparable to those of an experienced radiologist, and utilized only a single image for tissue characterization. Because radiologists commonly use two to four images of a mass for characterization, a similar procedure is developed here. A simple summation of the normalized Nakagami parameters from two different images of a mass is utilized for classification as benign or malignant. The performance of the normalized Nakagami parameters before and after the summation has been carried out through a receiver operating characteristic (ROC) study. The bootstrap procedure has been utilized to compute the mean and SD of the ROC area, A(z), obtained for each parameter. It has been observed that combining normalized Nakagami parameters from two images of the mass may help to improve classification performance over that from utilizing the parameters of just a single image. The performance of this automated parameter-based approach appears to match that of a trained radiologist.     

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.     

The 2D analytic signal for envelope detection and feature extraction on ultrasound images

The fundamental property of the analytic signal is the split of identity, meaning the separation of qualitative and quantitative information in form of the local phase and the local amplitude, respectively. Especially the structural representation, independent of brightness and contrast, of the local phase is interesting for numerous image processing tasks. Recently, the extension of the analytic signal from 1D to 2D, covering also intrinsic 2D structures, was proposed. We show the advantages of this improved concept on ultrasound RF and B-mode images. Precisely, we use the 2D analytic signal for the envelope detection of RF data. This leads to advantages for the extraction of the information-bearing signal from the modulated carrier wave. We illustrate this, first, by visual assessment of the images, and second, by performing goodness-of-fit tests to a Nakagami distribution, indicating a clear improvement of statistical properties. The evaluation is performed for multiple window sizes and parameter estimation techniques. Finally, we show that the 2D analytic signal allows for an improved estimation of local features on B-mode images.     

Cataract measurement by estimating the ultrasonic statistical parameter using an ultrasound needle transducer: an in vitro study

A cataract is a clouding of the crystalline lens that reduces the amount of incoming light and impairs visual perception. Phacoemulsification is the most common surgical method for treating advanced cataracts, and the optimal phacoemulsification energy is determined by the lens hardness. A previous study proposed using the ultrasonic Nakagami image to complement the B-scan for distinguishing different degrees of lens hardening. However, it is difficult to implement the use of an imaging probe to detect the lens during phacoemulsification surgery in a clinical situation. To resolve this problem, this study applied an ultrasonic needle transducer to estimate the Nakagami parameter as an alternative for characterizing the cataract lens. Cataracts of porcine lenses were artificially induced in vitro, and the Young's modulus, backscattering intensities, and the Nakagami parameters were measured. The results showed that the backscattering intensity was not correlated with Young's modulus. In contrast, the average Nakagami parameter increased from 0.34 to 0.95 with increasing Young's modulus of the lens from 1.71 to 101 kPa. The above findings showed that the Nakagami parameter estimated with a needle transducer may be useful in differentiating different degrees of lens hardening, and implied that determining the optimal ultrasonic energy during clinical cataract surgery is possible if the needle transducer can be combined with the phacoemulsification probe to estimate the Nakagami parameter.     

Statistical framework for ultrasonic spectral parameter imaging

This study examines the statistics of ultrasonic spectral parameter images that are being used to evaluate tissue microstructure in several organs. The parameters are derived from sliding-window spectrum analysis of radiofrequency echo signals. Calibrated spectra are expressed in dB and analyzed with linear regression procedures to compute spectral slope, intercept and midband fit, which is directly related to integrated backscatter. Local values of each parameter are quantitatively depicted in gray-scale cross-sectional images to determine tissue type, response to therapy and physical scatterer properties. In this report, we treat the statistics of each type of parameter image for statistically homogeneous scatterers. Probability density functions are derived for each parameter, and theoretical results are compared with corresponding histograms clinically measured in homogeneous tissue segments in the liver and prostate. Excellent agreement was found between theoretical density functions and data histograms for homogeneous tissue segments. Departures from theory are observed in heterogeneous tissue segments. The results demonstrate how the statistics of each spectral parameter and integrated backscatter are related to system and analysis parameters. These results are now being used to guide the design of system and analysis parameters, to improve assays of tissue heterogeneity and to evaluate the precision of estimating features associated with effective scatterer sizes and concentrations.     

Parametric ultrasound imaging from backscatter coefficient measurements: image formation and interpretation.

A broadband method for measuring backscatter coefficients sigma b and other acoustic parameters is described. From the sigma b measurements, using a commercially-available imaging system, four high-resolution parametric ultrasound images are formed in a C-scan image plane. Scatterer size images are computed from the frequency dependence of sigma b and a correlation model function that describes the structure and elastic properties of the medium. Scattering strength images are computed from the absolute magnitude of sigma b. Chi-square images are generated to display how well the correlation model represents the interrogated medium. Integrated backscatter coefficient images are formed over the transducer bandwidth. All four images are generated simultaneously and compared with the corresponding B-mode image. Test samples with known physical properties were used to demonstrate experimentally that accurate parametric images are possible if an accurate correlation model is used. Local variations in attenuation, the center frequency and bandwidth of the transducer, and the distribution of scatterer sizes greatly influence the accuracy of estimates and the appearance of the image, thus demonstrating the importance of these factors in parametric image interpretation.     

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.     

Ultrasonic Assessment of Thermal Therapy in Rat Liver

One way to assess the efficacy of thermal therapy is to quantify changes in tissue properties through ultrasonic interrogation, which requires knowledge of the acoustic properties of thermally treated tissues. In this study, estimates of ultrasonic attenuation, speed of sound, backscatter coefficient (BSC), and scattering property estimates were generated from rat liver samples submersed for 10 minutes in a saline bath that was heated to one of seven temperature values over a range of 37–70°C. The attenuation coefficient increased monotonically with exposure temperature, with a maximum increase of 90%. Speed of sound changed by <1% for the different treatment conditions. The BSC had close agreement for all thermal doses over the frequency range of 8–15 MHz. Above this frequency range, samples heated ≥55°C demonstrated an increased BSC slope, and the effective scatterer diameter and effective acoustic concentration were able to distinguish treated from nontreated cases. The findings suggest that attenuation and either BSCs or scatterer property estimates above 15 MHz were sensitive to tissue changes in excised liver caused by thermal therapy.     

Parametric imaging of rat mammary tumors in vivo for the purposes of tissue characterization.

OBJECTIVE: To estimate the average scatterer properties from ultrasonic backscatter in tissues for evaluating differences between neoplastic and healthy tissues. METHODS: Parametric images of 8 retired breeder rats in which spontaneous mammary tumors had developed were created by superimposing color-coded pixels related to the estimated average scatterer properties on conventional gray scale B-mode images. RESULTS: The images showed a distinct difference between the tumors and surrounding healthy tissues. Analysis of the average scatterer diameters and acoustic concentrations showed a statistically significant difference (P < .05) between estimates inside and outside the tumors for most of the cases. Scatterer sizes inside the tumors were on average 30% larger than scatterer sizes in surrounding normal tissues. A feature analysis plot showed that there was a distinct difference between results obtained inside and outside the tumors. CONCLUSIONS: Parametric imaging that uses estimates of scatterer properties in tissues may lead to detection and characterization (diagnosis) of diseased tissues on conventional sonographic scanning systems.     

A computer model for simulating ultrasonic scattering in biological tissues with high scatterer concentration

Scattering of ultrasonic waves by biological tissues at different scatterer concentrations is investigated using one- and two-dimensional computer simulation models. The backscattered power as a function of scatterer concentrations is calculated using two types of incident waves, a Gaussian shaped pulse and a continuous wave (CW). The simulation results are in good agreement with the Percus-Yevick packing theory within the scatterer concentrations, from 0% to 100% in one-dimensional (1D) space, and 0% to 46% in two-dimensional (2D) space. In all cases, the simulation results from a pulsed incident wave show a much smaller standard deviation (SD) than those from an incident CW. The simulation can serve as a useful tool to verify scattering theories, simulate different experimental conditions, and to investigate the interaction between the scatterer properties and the scattering of ultrasonic waves. More importantly, the 2D) simulation procedure serves as an initial step toward the final realization of a true three-dimensional (3D) simulation of ultrasonic scattering in biological tissues.     

On Monitoring Structural Changes of Anisotropic Tissues by Means of Statistical Analysis of Ultrasonic Images

An investigation into statistical properties of ultrasonic image texture from three-dimensional clusters of anisotropic scatterers is carried out. The structural properties of the clusters are modeled after those of soft biological tissues, such as skeletal muscle tissues, both in their healthy condition and at the early stage of degenerative diseases. The average axial autocorrelation function of the intensity of the image texture is used to characterize and monitor changes of the geometrical properties of the tissue components. A distinct local increase of the autocorrelation is observed within a range of small time shifts, and it is explained in terms of the structure of the time-domain backscattered signal from each individual scatterer. It is shown that such an increase is sensitive to structural variations of the cluster similar to those occurring at the early stage of several muscular diseases.     

Relationship between ultrasonic attenuation, size and axial strain parameters for ex vivo atherosclerotic carotid plaque

Many ultrasonic parameters, primarily related to attenuation and scatterer size, have been used to characterize the composition of atherosclerotic plaque tissue. In this study, we combine elastographic (axial strain ratio) and ultrasonic tissue characterization parameters, namely the attenuation coefficient and a scattering parameter associated with an "equivalent" scatterer size to delineate between fibrous, calcified, and lipidic plaque tissue. We present results obtained from 44 ex vivo atherosclerotic plaque specimens obtained after carotid endarterectomy on human patients. Our results in the frequency range 2.5 - 7.5 MHz indicate that softer plaques (with higher values of the strain ratio) are usually associated with larger equivalent scatterer size estimates (200 - 500 microm) and lower values of the attenuation coefficient slope (<1 dB/cm/MHz). On the other hand, stiffer plaques (with lower strain ratio values) are associated with smaller equivalent scatterer size estimates (100 - 200 microm) and higher values of the attenuation coefficient slope (1 - 3 dB/cm/MHz). These results indicate that ultrasonic tissue characterization and strain parameters have the potential to differentiate between different plaque types. These parameters can be estimated from radio-frequency data acquired under in vivo conditions and may help the clinician decide on appropriate interventional techniques.     

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.