Artifact reduction of ultrasound Nakagami imaging by combining multifocus image reconstruction and the noise-assisted correlation algorithm

Quantitative Ultrasound: An Emerging Technology for Detecting, Diagnosing, Imaging, Evaluating, and Monitoring Disease

Ultrasound has been a popular clinical imaging modality for decades. It is a well-established means of displaying the macroscopic anatomy of soft-tissue structures. While conventional ultrasound methods, i.e., B-mode and Doppler methods, are well proven and continue to advance technically in many ways, e.g., by extending into higher frequencies and taking advantage of harmonic phenomena in tissues, fundamentally new so-called quantitative ultrasound (QUS) technologies also are emerging and offer exciting promise for making significant improvements in clinical imaging and characterization of disease. These emerging quantitative methods include spectrum analysis, image statistics, elasticity imaging, contrast-agent methods, and flow-detection and -measurement techniques. Each provides independent information. When used alone, each can provide clinically valuable imaging capabilities; when combined with each other, their capabilities may be more powerful in many applications. Furthermore, all can be used fused with other imaging modalities, such as computed tomography (CT), magnetic-resonance (MR), positron-emission-tomography (PET), or single-photon emission computerized tomography (SPECT) imaging, to offer possibly even greater improvements in detecting, diagnosing, imaging, evaluating, and monitoring disease. This chapter focuses on QUS methods that are based on spectrum analysis and image statistics.

Deep Estimation of Speckle Statistics Parametric Images

Quantitative Ultrasound (QUS) provides important information about the tissue properties. QUS parametric image can be formed by dividing the envelope data into small overlapping patches and computing different speckle statistics such as parameters of the Nakagami and Homodyned K-distributions (HK-distribution). The calculated QUS parametric images can be erroneous since only a few independent samples are available inside the patches. Another challenge is that the envelope samples inside the patch are assumed to come from the same distribution, an assumption that is often violated given that the tissue is usually not homogenous. In this paper, we propose a method based on Convolutional Neural Networks (CNN) to estimate QUS parametric images without patching. We construct a large dataset sampled from the HK-distribution, having regions with random shapes and QUS parameter values. We then use a well-known network to estimate QUS parameters in a multi-task learning fashion. Our results confirm that the proposed method is able to reduce errors and improve border definition in QUS parametric images.

The Spectrum-Beamformer for Conventional B-Mode Ultrasound Imaging System: Principle, Validation, and Robustness

Fast and efficient imaging techniques are important for real-time ultrasound imaging. The delay and sum (DAS) beamformer is the most widely-used strategy in focused ultrasound imaging (FUI) modality. However, calculating the time delays and coherently summing the amplitude response in DAS is computationally expensive and generally require a high-performance processor to realize real-time processing. In this study, an efficient spectrum beamformer, namely full-matrix capture (FMC)-stolt, is proposed in FUI system with a linear phased array. The imaging performance of FMC-stolt was validated with the point-scatter simulation and in vitro point and cyst phantoms, and then compared with that of five beamformers, that is, Multiline acquisition (MLA), retrospective transmit beamforming (RTB) in the FUI modality, as well as DAS, Garcia's frequency-wavenumber (f-k), Lu's f-k in the coherent plane wave compounding imaging (CPWCI) modality, under specific conditions. We show that the imaging performance of FMC-stolt is better than MLA-DAS in non-transmit-focal regions, and comparable with RTB-DAS at all imaging depths. FMC-stolt also shows better discontinuity alleviation than MLA and RTB. In addition, FMC-stolt has similar imaging characteristics (e.g., off-axis resolution, computational cost) as the f-k beamformers. The computational complexity and actual computational time indicate that FMC-stolt is comparable to Garcia's f-k, Lu's f-k, and faster than RTB and CPWCI-DAS if the transmitting numbers are close for FUI and CPWCI. The study demonstrates that the proposed FMC-stolt could achieve good reconstruction speed while preserving high-quality images and thus provide a choice for software beamforming for conventional B-mode ultrasound imaging, especially for hand-held devices with limited performance processors.

Monitoring microwave ablation using ultrasound homodyned K imaging based on the noise-assisted correlation algorithm: An ex vivo study

In this paper, we proposed ultrasound homodyned K (HK) imaging based on the noise-assisted correlation algorithm (NCA) for monitoring microwave ablation of porcine liver ex vivo. The NCA-based HK (α_NCA and k_NCA) imaging was compared with NCA-based Nakagami (m_NCA) imaging and NCA-based cumulative echo decorrelation (CED_NCA) imaging. Backscattered ultrasound radiofrequency signals of porcine liver ex vivo during and after the heating of microwave ablation were collected (n = 15), which were processed for constructing B-mode imaging, NCA-based HK imaging, NCA-based Nakagami imaging, and NCA-based CED imaging. To quantitatively evaluate the final coagulation zone, the polynomial approximation (PAX) technique was applied. The accuracy of detecting coagulation area with α_NCA, k_NCA, m_NCA, and CED_NCA parametric imaging was evaluated by comparing the PAX imaging with the gross pathology. The receiver operating characteristic (ROC) curve was used to further evaluate the performance of the three quantitative ultrasound imaging methods for detecting the coagulation zone. Experimental results showed that the average accuracies of α_NCA, k_NCA, m_NCA, and CED_NCA parametric imaging combined with PAX imaging were 89.6%, 83.25%, 89.23%, and 91.6%, respectively. The average areas under the ROC curve (AUROCs) of α_NCA, k_NCA, m_NCA, and CED_NCA parametric imaging were 0.83, 0.77, 0.83, and 0.86, respectively. The proposed NCA-based HK imaging may be used as a new method for monitoring microwave ablation.

Ex Vivo and In Vivo Monitoring and Characterization of Thermal Lesions by High-Intensity Focused Ultrasound and Microwave Ablation Using Ultrasonic Nakagami Imaging

The feasibility of ultrasonic Nakagami imaging to evaluate thermal lesions by high-intensity focused ultrasound and microwave ablation was explored in ex vivo and in vivo liver models. Dynamic changes of the ultrasonic Nakagami parameter in thermal lesions were calculated, and ultrasonic B-mode and Nakagami images were reconstructed simultaneously. The contrast-to-noise ratio (CNR) between thermal lesions and normal tissue was used to estimate the contrast resolution of the monitoring images. After thermal ablation, a bright hyper-echoic region appeared in the ultrasonic B-mode and Nakagami images, identifying the thermal lesion. During thermal ablation, mean values of Nakagami parameter showed an increasing trend from 0.72 to 1.01 for the ex vivo model and 0.54 to 0.72 for the in vivo model. After thermal ablation, mean CNR values of the ultrasonic Nakagami images were 1.29 dB (ex vivo) and 0.80 dB (in vivo), significantly higher ( ) than those for B-mode images. Thermal lesion size, assessed using ultrasonic Nakagami images, shows a good correlation to those obtained from the gross-pathology images (for the ex vivo model: length, = 0.96; width, = 0.90; for the in vivo model: length, = 0.95; width, = 0.85). This preliminary study suggests that ultrasonic Nakagami parameter may have a potential use in evaluating the formation of thermal lesions with better image contrast. Moreover, ultrasonic Nakagami imaging combined with B-mode imaging may be utilized as an alternative modality in developing monitoring systems for image-guided thermal ablation treatments.

Three-dimensional Visualization of Ultrasound Backscatter Statistics by Window-modulated Compounding Nakagami Imaging

In this study, the window-modulated compounding (WMC) technique was integrated into three-dimensional (3D) ultrasound Nakagami imaging for improving the spatial visualization of backscatter statistics. A 3D WMC Nakagami image was produced by summing and averaging a number of 3D Nakagami images (number of frames denoted as N) formed using sliding cubes with varying side lengths ranging from 1 to N times the transducer pulse. To evaluate the performance of the proposed 3D WMC Nakagami imaging method, agar phantoms with scatterer concentrations ranging from 2 to 64 scatterers/mm³ were made, and six stages of fatty liver (zero, one, two, four, six, and eight weeks) were induced in rats by methionine-choline-deficient diets (three rats for each stage, total n = 18). A mechanical scanning system with a 5-MHz focused single-element transducer was used for ultrasound radiofrequency data acquisition. The experimental results showed that 3D WMC Nakagami imaging was able to characterize different scatterer concentrations. Backscatter statistics were visualized with various numbers of frames; N = 5 reduced the estimation error of 3D WMC Nakagami imaging in visualizing the backscatter statistics. Compared with conventional 3D Nakagami imaging, 3D WMC Nakagami imaging improved the image smoothness without significant image resolution degradation, and it can thus be used for describing different stages of fatty liver in rats.

A Review of Ultrasound Tissue Characterization with Mean Scatterer Spacing

Tissues exhibiting quasi-periodic structures can be modeled as a collection of diffuse scatterers and coherent scatterers. The mean scatterer spacing (MSS) of coherent and quasi-periodic components is directly related to tissue microstructure and has become an important quantitative ultrasound (QUS) parameter in the characterization of quasi-periodic tissues. In this paper, a review of the literature on the development of MSS as a QUS parameter was conducted. First, a unified theoretical background of MSS estimates was provided. Then, the application of MSS estimates was summarized with respect to liver, spleen, breast, bone, muscle, and other tissues. MSS estimation techniques were applied to (a) the diagnosis of hepatitis, liver fibrosis and cirrhosis, and lesions in tissues such as liver, breast, and spleen; (b) the differentiation between benign and malignant breast tumors, and the grading of breast cancer; (c) the detection of cancellous bone; and (d) the monitoring of the efficacy of treatments such as thermal ablation, with various levels of success. Future developments were also discussed in terms of real-time implementation of MSS estimates, local MSS estimation, relationship of MSS to other QUS parameters, combination of MSS with other QUS parameters, in vivo validation of MSS estimates, MSS parametric imaging, and three-dimensional ultrasound tissue characterization.

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.

Ultrasound window-modulated compounding Nakagami imaging: Resolution improvement and computational acceleration for liver characterization

Ultrasound Nakagami imaging is an attractive method for visualizing changes in envelope statistics. Window-modulated compounding (WMC) Nakagami imaging was reported to improve image smoothness. The sliding window technique is typically used for constructing ultrasound parametric and Nakagami images. Using a large window overlap ratio may improve the WMC Nakagami image resolution but reduces computational efficiency. Therefore, the objectives of this study include: (i) exploring the effects of the window overlap ratio on the resolution and smoothness of WMC Nakagami images; (ii) proposing a fast algorithm that is based on the convolution operator (FACO) to accelerate WMC Nakagami imaging. Computer simulations and preliminary clinical tests on liver fibrosis samples (n=48) were performed to validate the FACO-based WMC Nakagami imaging. The results demonstrated that the width of the autocorrelation function and the parameter distribution of the WMC Nakagami image reduce with the increase in the window overlap ratio. One-pixel shifting (i.e., sliding the window on the image data in steps of one pixel for parametric imaging) as the maximum overlap ratio significantly improves the WMC Nakagami image quality. Concurrently, the proposed FACO method combined with a computational platform that optimizes the matrix computation can accelerate WMC Nakagami imaging, allowing the detection of liver fibrosis-induced changes in envelope statistics. FACO-accelerated WMC Nakagami imaging is a new-generation Nakagami imaging technique with an improved image quality and fast computation.

Ultrasound characterization of the mastoid for detecting middle ear effusion: A preliminary clinical validation

Ultrasound detection of middle ear effusion (MEE) is an emerging technique in otolaryngology. This study proposed using ultrasound characterization of the mastoid to noninvasively measure MEE-induced mastoid effusion (ME) as a new strategy for determining the presence of MEE. In total, 53 patients were enrolled (Group I: normal, n = 20; Group II: proven MEE through both otoscopy and tympanometry, n = 15; Group III: patients with MEE having effusions observed during grommet surgery, n = 18). A 2.25-MHz delay-line transducer was used to measure backscattered signals from the mastoid. The Nakagami parameter was estimated using the acquired signals to model the echo amplitude distribution for quantifying changes in the acoustic structures of mastoid air cells. The median Nakagami parameter and interquartile range were 0.35 (0.34-0.37) for Group I, 0.39 (0.37-0.41) for Group II, and 0.43 (0.39-0.51) for Group III. The echo amplitude distribution observed for patients with MEE was closer to Rayleigh distribution than that without MEE. Receiver operating characteristic (ROC) curve analysis further revealed that the area under the ROC was 0.88, sensitivity was 72.73%, specificity was 95%, and accuracy was 81.13%. The proposed method has considerable potential for noninvasive and comfortable evaluation of MEE.

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Effects of Estimators on Ultrasound Nakagami Imaging in Visualizing the Change in the Backscattered Statistics from a Rayleigh Distribution to a Pre-Rayleigh Distribution

Ultrasound Nakagami imaging has recently attracted interest as an imaging technique for analyzing envelope statistics. Because the presence of structures has a strong effect on estimation of the Nakagami parameter, previous studies have indicated that Nakagami imaging should be used specifically for characterization of soft tissues with fewer structures, such as liver tissues. Typically, changes in the properties of the liver parenchyma cause the backscattered statistics to transform from a Rayleigh distribution to a pre-Rayleigh distribution, and this transformation can be visualized using a Nakagami imaging technique. However, different estimators result in different estimated values; thus, the performance of a Nakagami image may depend on the type of estimator used. This study explored the effects of various estimators on ultrasound Nakagami imaging to describe the backscattered statistics as they change from a Rayleigh distribution to a pre-Rayleigh distribution. Simulations and clinical measurements involving patients with liver fibrosis (n = 85) yielded image data that were used to construct B-mode and conventional Nakagami images based on the moment estimator (denoted as mINV images) and maximum-likelihood estimator (denoted as mML images). In addition, novel window-modulated compounding Nakagami images based on the moment estimator (denoted as mWMC images) were also obtained. The means and standard deviations of the Nakagami parameters were examined as a function of the backscattered statistics. The experimental results indicate that the mINV, mML and mWMC images enabled quantitative visualization of the change in backscattered statistics from a Rayleigh distribution to a pre-Rayleigh distribution. Importantly, the mWMC image is superior to both mINV and mML images because it simultaneously realizes sensitive detection of the backscattered statistics and a reduction of estimation variance for image smoothness improvement. We therefore recommend using mWMC image as a novel strategy in Nakagami imaging technique for liver tissue characterization.

Effects of fatty infiltration in human livers on the backscattered statistics of ultrasound imaging

Ultrasound imaging has been widely applied to screen fatty liver disease. Fatty liver disease is a condition where large vacuoles of triglyceride fat accumulate in liver cells, thereby altering the arrangement of scatterers and the corresponding backscattered statistics. In this study, we used ultrasound Nakagami imaging to explore the effects of fatty infiltration in human livers on the statistical distribution of backscattered signals. A total of 107 patients volunteered to participate in the experiments. The livers were scanned using a clinical ultrasound scanner to obtain the raw backscattered signals for ultrasound B-mode and Nakagami imaging. Clinical scores of fatty liver disease for each patient were determined according to a well-accepted sonographic scoring system. The results showed that the Nakagami image can visualize the local backscattering properties of liver tissues. The Nakagami parameter increased from 0.62 ± 0.11 to 1.02 ± 0.07 as the fatty liver disease stage increased from normal to severe, indicating that the backscattered statistics vary from pre-Rayleigh to Rayleigh distributions. A significant positive correlation (correlation coefficient ρ = 0.84; probability value (p value) < 0.0001) exists between the degree of fatty infiltration and the Nakagami parameter, suggesting that ultrasound Nakagami imaging has potentials in future applications in fatty liver disease diagnosis.