Ultrasonic Assessment of Liver Fibrosis Using One-Dimensional Convolutional Neural Networks Based on Frequency Spectra of Radiofrequency Signals with Deep Learning Segmentation of Liver Regions in B-Mode Images: A Feasibility Study.

The early detection of liver fibrosis is of significant importance. Deep learning analysis of ultrasound backscattered radiofrequency (RF) signals is emerging for tissue characterization as the RF signals carry abundant information related to tissue microstructures. However, the existing methods only used the time-domain information of the RF signals for liver fibrosis assessment, and the liver region of interest (ROI) is outlined manually. In this study, we proposed an approach for liver fibrosis assessment using deep learning models on ultrasound RF signals. The proposed method consisted of two-dimensional (2D) convolutional neural networks (CNNs) for automatic liver ROI segmentation from reconstructed B-mode ultrasound images and one-dimensional (1D) CNNs for liver fibrosis stage classification based on the frequency spectra (amplitude, phase, and power) of the segmented ROI signals. The Fourier transform was used to obtain the three kinds of frequency spectra. Two classical 2D CNNs were employed for liver ROI segmentation: U-Net and Attention U-Net. ROI spectrum signals were normalized and augmented using a sliding window technique. Ultrasound RF signals collected (with a 3-MHz transducer) from 613 participants (Group A) were included for liver ROI segmentation and those from 237 participants (Group B) for liver fibrosis stage classification, with a liver biopsy as the reference standard (Fibrosis stage: F0 = 27, F1 = 49, F2 = 51, F3 = 49, F4 = 61). In the test set of Group A, U-Net and Attention U-Net yielded Dice similarity coefficients of 95.05% and 94.68%, respectively. In the test set of Group B, the 1D CNN performed the best when using ROI phase spectrum signals to evaluate liver fibrosis stages ≥F1 (area under the receive operating characteristic curve, AUC: 0.957; accuracy: 89.19%; sensitivity: 85.17%; specificity: 93.75%), ≥F2 (AUC: 0.808; accuracy: 83.34%; sensitivity: 87.50%; specificity: 78.57%), and ≥F4 (AUC: 0.876; accuracy: 85.71%; sensitivity: 77.78%; specificity: 94.12%), and when using the power spectrum signals to evaluate ≥F3 (AUC: 0.729; accuracy: 77.14%; sensitivity: 77.27%; specificity: 76.92%). The experimental results demonstrated the feasibility of both the 2D and 1D CNNs in liver parenchyma detection and liver fibrosis characterization. The proposed methods have provided a new strategy for liver fibrosis assessment based on ultrasound RF signals, especially for early fibrosis detection. The findings of this study shed light on deep learning analysis of ultrasound RF signals in the frequency domain with automatic ROI segmentation.

Frequency-Domain Robust PCA for Real-Time Monitoring of HIFU Treatment.

High intensity focused ultrasound (HIFU) is a thriving non-invasive technique for thermal ablation of tumors, but significant challenges remain in its real-time monitoring with medical imaging. Ultrasound imaging is one of the main imaging modalities for monitoring HIFU surgery in organs other than the brain, mainly due to its good temporal resolution. However, strong acoustic interference from HIFU irradiation severely obscures the B-mode images and compromises the monitoring. To address this problem, we proposed a frequency-domain robust principal component analysis (FRPCA) method to separate the HIFU interference from the contaminated B-mode images. Ex-vivo and in-vivo experiments were conducted to validate the proposed method based on a clinical HIFU therapy system combined with an ultrasound imaging platform. The performance of the FRPCA method was compared with the conventional notch filtering method. Results demonstrated that the FRPCA method can effectively remove HIFU interference from the B-mode images, which allowed HIFU-induced grayscale changes at the focal region to be recovered. Compared to notch-filtered images, the FRPCA-processed images showed an 8.9% improvement in terms of the structural similarity (SSIM) index to the uncontaminated B-mode images. These findings demonstrate that the FRPCA method presents an effective signal processing framework to remove the strong HIFU acoustic interference, obtains better dynamic visualization in monitoring the HIFU irradiation process, and offers great potential to improve the efficacy and safety of HIFU treatment and other focused ultrasound related applications.

Ultrasound k-nearest neighbor entropy imaging: Theory, algorithm, and applications.

Ultrasound information entropy is a flexible approach for analyzing ultrasound backscattering. Shannon entropy imaging based on probability distribution histograms (PDHs) has been implemented as a promising method for tissue characterization and diagnosis. However, the bin number affects the stability of entropy estimation. In this study, we introduced the k-nearest neighbor (KNN) algorithm to estimate entropy values and proposed ultrasound KNN entropy imaging. The proposed KNN estimator leveraged the Euclidean distance between data samples, rather than the histogram bins by conventional PDH estimators. We also proposed cumulative relative entropy (CRE) imaging to analyze time-series radiofrequency signals and applied it to monitor thermal lesions induced by microwave ablation (MWA). Computer simulation phantom experiments were conducted to validate and compare the performance of the proposed KNN entropy imaging, the conventional PDH entropy imaging, and Nakagami-m parametric imaging in detecting the variations of scatterer densities and visualizing inclusions. Clinical data of breast lesions were analyzed, and porcine liver MWA experiments ex vivo were conducted to validate the performance of KNN entropy imaging in classifying benign and malignant breast tumors and monitoring thermal lesions, respectively. Compared with PDH, the entropy estimation based on KNN was less affected by the tuning parameters. KNN entropy imaging was more sensitive to changes in scatterer densities and performed better visualizable capability than typical Shannon entropy (TSE) and Nakagami-m parametric imaging. Among different imaging methods, KNN-based Shannon entropy (KSE) imaging achieved the higher accuracy in classification of benign and malignant breast tumors and KNN-based CRE imaging had larger lesion-to-normal contrast when monitoring the ablated areas during MWA at different powers and treatment durations. Ultrasound KNN entropy imaging is a potential quantitative ultrasound approach for tissue characterization.

Ultrasound tissue scatterer distribution imaging: An adjunctive diagnostic tool for shear wave elastography in characterizing focal liver lesions.

OBJECTIVES: Focal liver lesion (FLL) is a prevalent finding in cross-sectional imaging, and distinguishing between benign and malignant FLLs is crucial for liver health management. While shear wave elastography (SWE) serves as a conventional quantitative ultrasound tool for evaluating FLLs, ultrasound tissue scatterer distribution imaging (TSI) emerges as a novel technique, employing the Nakagami statistical distribution parameter to estimate backscattered statistics for tissue characterization. In this prospective study, we explored the potential of TSI in characterizing FLLs and evaluated its diagnostic efficacy with that of SWE. METHODS: A total of 235 participants (265 FLLs; the study group) were enrolled to undergo abdominal examinations, which included data acquisition from B-mode, SWE, and raw radiofrequency data for TSI construction. The area under the receiver operating characteristic curve (AUROC) was used to evaluate performance. A dataset of 20 patients (20 FLLs; the validation group) was additionally acquired to further evaluate the efficacy of the TSI cutoff value in FLL characterization. RESULTS: In the study group, our findings revealed that while SWE achieved a success rate of 49.43 % in FLL measurements, TSI boasted a success rate of 100 %. In cases where SWE was effectively implemented, the AUROCs for characterizing FLLs using SWE and TSI stood at 0.84 and 0.83, respectively. For instances where SWE imaging failed, TSI achieved an AUROC of 0.78. Considering all cases, TSI presented an overall AUROC of 0.81. There was no statistically significant difference in AUROC values between TSI and SWE (p > 0.05). In the validation group, using a TSI cutoff value of 0.67, the AUROC for characterizing FLLs was 0.80. CONCLUSIONS: In conclusion, ultrasound TSI holds promise as a supplementary diagnostic tool to SWE for characterizing FLLs.

Acoustic radiation force impulse shear wave elastography quantifies upper limb muscle in patients with Duchenne muscular dystrophy.

We investigated whether the upper limb muscle stiffness quantified by the acoustic radiation force impulse shear wave elastography (ARFI/SWE) is a potential biomarker for age-related muscle alteration and functional decline in patients with Duchenne muscular dystrophy (DMD). 37 patients with DMD and 30 typically developing controls (TDC) were grouped by age (3-8, 9-11, and 12-18 years). ARFI/SWE measured the biceps and deltoid muscle's shear wave velocities (SWVs). Performance of Upper Limb Module (PUL 1.2 module) assessed muscle function in DMD patients. Mann Whitney test compared muscle SWVs between DMD and TDC, stratified by three age groups. We used analysis of variance with Bonferroni correction to compare muscle SWVs between DMD and TDC and correlated muscle SWVs with PUL results in the DMD group. Results showed that the SWVs of biceps differentiated DMD patients from TDC across age groups. Younger DMD patients (3-8 years) exhibited higher SWVs (p = 0.013), but older DMD patients (12-18 years) showed lower SWVS (p = 0.028) than same-aged TDC. DMD patients had decreasing biceps SWVs with age (p < 0.001), with no such age effect in TDC. The SWVs of deltoid and biceps positively correlated with PUL scores (r = 0.527 âˆ¼ 0.897, P < 0.05) and negatively correlated with PUL timed measures (r = -0.425 âˆ¼ -0.542, P < 0.05) in DMD patients. Our findings suggest that ARFI/SWE quantifying the SWVs in upper limb muscle could be a potential biomarker to differentiate DMD from TDC across ages and that DMD patients showed age-related muscle alteration and limb functional decline.

Quantitative transmastoid ultrasound for detecting middle ear effusion in pediatric patients.

BACKGROUND AND OBJECTIVE: Ultrasound has emerged as a promising modality for detecting middle ear effusion (MEE) in pediatric patients. Among different ultrasound techniques, ultrasound mastoid measurement was proposed to allow noninvasive detection of MEE by estimating the Nakagami parameters of backscattered signals to describe the echo amplitude distribution. This study further developed the multiregional-weighted Nakagami parameter (MNP) of the mastoid as a new ultrasound signature for assessing effusion severity and fluid properties in pediatric patients with MEE. METHODS: A total of 197 pediatric patients (n = 133 for the training group; n = 64 for the testing group) underwent multiregional backscattering measurements of the mastoid for estimating MNP values. MEE, the severity of effusion (mild to moderate vs. severe), and the fluid properties (serous and mucous) were confirmed through otoscopy, tympanometry, and grommet surgery and were compared with the ultrasound findings. The diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUROC). RESULTS: The training dataset revealed significant differences in MNPs between the control and MEE groups, between mild to moderate and severe MEE, and between serous and mucous effusion were observed (p < 0.05). As with the conventional Nakagami parameter, the MNP could be used to detect MEE (AUROC: 0.87; sensitivity: 90.16%; specificity: 75.35%). The MNP could further identify effusion severity (AUROC: 0.88; sensitivity: 73.33%; specificity: 86.87%) and revealed the possibility of characterizing fluid properties (AUROC: 0.68; sensitivity: 62.50%; specificity: 70.00%). The testing results demonstrated that the MNP method enabled MEE detection (AUROC = 0.88, accuracy = 88.28%, sensitivity = 92.59%, specificity = 84.21%), was effective in assessing MEE severity (AUROC = 0.83, accuracy = 77.78%, sensitivity = 66.67%, specificity = 83.33%), and showed potential for characterizing fluid properties of effusion (AUROC = 0.70, accuracy = 72.22%, sensitivity = 62.50%, specificity = 80.00%). CONCLUSIONS: Transmastoid ultrasound combined with the MNP not only leverages the strengths of the conventional Nakagami parameter for MEE diagnosis but also provides a means to assess MEE severity and effusion properties in pediatric patients, thereby offering a comprehensive approach to noninvasive MEE evaluation.

Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation of the liver tumor: A preliminary clinical validation.

Radiofrequency ablation (RFA) is an alternative treatment for early-stage hepatocellular carcinoma (HCC). The production of gas bubbles by RFA indicates threshold temperature of tissue necrosis and results in changes in backscattered energy (CBE) when ultrasound monitors RFA. In this study, ultrasound single-phase CBE imaging was used as a means of monitoring RFA of the liver tumor by analyzing the backscattering of ultrasound from gas bubbles in the liver. A total of 19 HCC patients were enrolled in the study. An ultrasound system was used during RFA to monitor the ablation process and acquire raw image data consisting of backscattered signals for single-phase CBE imaging. On the basis of single-phase CBE imaging, the area corresponding to the range of gas bubbles was compared with the tumor sizes and ablation zones estimated from computed tomography. During RFA, ultrasound single-phase CBE imaging enabled improved visualization of gas bubbles. Measured gas bubble areas by CBE were related to tumor size (the Spearman correlation coefficient r s = 0.86; p < 0.05); less dependent on the ablation zone. Approximately 95% of the data fell within the limits of agreement in Bland-Altman plots, and 58% of the data fell within the 95% CI. This study suggests that single-phase CBE imaging provides information about liver tumor size because of the abundant vessels in liver tumors that promote the generation of gas bubbles, which serve as natural contrast agents in RFAs to enhance ultrasound backscattering. Ultrasound single-phase CBE imaging may allow clinicians to determine if the required minimum RFA efficacy level is reached by assessing gas bubbles in the liver tumors.

Detection of microwave ablation coagulation areas using ultrasound Nakagami imaging based on Gaussian pyramid decomposition: A feasibility study.

In this paper, we explored the feasibility of using ultrasound Nakagami-m parametric imaging based on Gaussian pyramid decomposition (GPD) to detect microwave ablation coagulation areas. Monte Carlo simulation and phantom simulation results demonstrated that a 2-layer GPD model was sufficient to achieve the same m parameter estimation accuracy, smoothness and resolution as 3-layer and 4-layer. The performances of GPD, moment-based estimator (MBE) and window-modulated compounding (WMC) algorithms were compared in terms of parameter estimation, smoothness, resolution and contrast-to-noise (CNR). Results showed that the m parameter estimation obtained by GPD algorithm was better than that of MBE and WMC algorithms except the small window size (27 × 5). When using a window size of >3 pulse lengths, GPD algorithm could achieve better smoothness and CNR than MBE and WMC algorithms, but there was a certain loss of axial resolution. The computation time of GPD algorithm was less than that of WMC algorithm, while about 2.24 times that of MBE algorithm. Experimental results of porcine liver microwave ablation ex vivo (n = 20) illustrated that the average areas under the operating characteristic curve (AUCs) of Nakagami mGPD, mMBE and mWMC parametric imaging and homodyned-K (HK) α and k parametric imaging to detect coagulation areas were significantly improved by polynomial approximation (PAX). Kruskal-Wallis test showed that the accuracy of coagulation area detection obtained by PAX imaging of mGPD parameter had no significant difference with that of mMBE, mWMC, HK_α and HK_k parameters. This preliminary study suggested that Nakagami imaging based on GPD algorithm may have the potential to detect microwave ablation coagulation areas.

Stretch-Induced Healing of Injured Muscles Is Associated With Myogenesis and Decreased Fibrosis.

BACKGROUND: Alghouth therapeutic stretching exercise has been applied to accelerate the healing of injured skeletal muscles, mechanisms behind the mechanical stretch-induced muscle recovery remain unclear. PURPOSE: To examine stretch-associated antifibrotic and myogenic responses in injured muscles and to evaluate the feasibility of the ultrasonic Nakagami parametric index (NPI) in assessing muscle morphology during recovery. STUDY DESIGN: Controlled laboratory study. METHODS: Skeletal muscle fibrosis was induced in the right hind legs of 48 rats by making a posterior transverse incision in the gastrocnemius muscle; the left hind legs remained intact as a comparative normal reference. After surgery, the 48 rats were randomly divided into the stretch (S) and control (C) groups. The S group received stretching interventions on the injured hind leg from week 3 to week 7 after surgery, while the C group did not receive stretching throughout the study period. The muscle fibrosis percentage and the ultrasonic NPI were examined sequentially after surgery. Relative expressions of myogenesis-related proteins, including myoblast determination protein 1 (MyoD), myogenin, and embryonic myosin heavy chain (MHCemb), were also evaluated during the follow-up. RESULTS: Mean fibrosis percentages in the injured hind leg were approximately 25% at week 3 in both groups, but they were significantly decreased by approximately 20% from week 4 to the end of the follow-up in the S group only (all, P < .05). Upon injury, the NPI values of injured hind legs in both groups dramatically dropped. Within the S group, stretching increased the NPI values of injured hind legs, which approached those of control hind legs at weeks 6 and 7. The highest MyoD, myogenin, and MHCemb levels were observed at week 6 in both groups. The NPI values corresponded to the MyoD expression in the S group during the follow-up. CONCLUSION: Stretching induced a decrease in muscle fibrosis and an increase in myogenesis in injured muscles. The NPI values correspond to the myogenesis process. CLINICAL RELEVANCE: The NPI may be capable of continuously monitoring the injured skeletal muscle morphology during the healing process in clinical settings.

Quantifying Lower Limb Muscle Stiffness as Ambulation Function Declines in Duchenne Muscular Dystrophy with Acoustic Radiation Force Impulse Shear Wave Elastography.

Duchenne muscular dystrophy (DMD) is a progressive muscular disease, but validated imaging tools to quantify muscle microstructure alteration as mobility declines are lacking. We aimed to determine the feasibility of using acoustic radiation force impulse shear-wave elastography (ARFI/SWE) in the quantitative assessment of lower limb muscle stiffness in DMD patients. Shear wave velocities (SWVs) of lower limbs were measured in 39 DMD patients and 36 healthy controls aged 3-20 y. Mean SWV values of the controls and of the DMD patients at different ambulatory stages were compared using analysis of variance with Bonferroni correction. The DMD group had increased lower limb muscle stiffness compared with controls. Stiffness of the tibialis anterior and medial gastrocnemius muscle decreased from ambulatory to early non-ambulatory stages, whereas stiffness of the rectus femoris muscle increased from ambulatory to late non-ambulatory stages. We describe how SWV changes in lower limb muscles have the potential to predict ambulatory decline in DMD.

Utility of quantitative ultrasound in community screening for hepatic steatosis.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. Quantitative ultrasound facilitates clinical grading of hepatic steatosis (the early stage of NAFLD). However, the utility of quantitative ultrasound as a first-line method for community screening of hepatic steatosis remains unclear. Therefore, this study aimed to investigate the utility of quantitative ultrasound to screen for hepatic steatosis and for metabolic evaluation at the community level. In total, 278 participants enrolled from a community satisfied the study criteria. Each subject underwent anthropometric and biochemical examinations, and abdominal ultrasound imaging was performed to measure the controlled attenuation (CAP), integrated backscatter (IB), and information Shannon entropy (ISE). The assessment outcomes were compared with the fatty liver index (FLI), hepatic steatosis index (HSI), metabolic syndrome (MetS), and insulin resistance to evaluate the screening performance through the area under the receiver operating characteristic curve (AUROC) and Delong's test. Ultrasound ISE, CAP, and IB were effective in screening hepatic steatosis, MetS, and insulin resistance. In screening for hepatic steatosis, the AUROCs of ISE, CAP, and IB were 0.85, 0.83, and 0.80 (the cutoff FLI = 60), respectively, and 0.84, 0.75, 0.77 (the cutoff HSI = 36), respectively, and those for the evaluation of MetS and insulin resistance were 0.79, 0.75, 0.79, respectively, and 0.83, 0.76, 0.78, respectively. Delong's test revealed that ISE outperformed CAP and IB for the detection of hepatic steatosis and insulin resistance (P < .05). Based on the present results, ultrasound ISE is a potential imaging biomarker during first-line community screening of hepatic steatosis and insulin resistance.

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 (αNCA and kNCA) imaging was compared with NCA-based Nakagami (mNCA) imaging and NCA-based cumulative echo decorrelation (CEDNCA) 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 αNCA, kNCA, mNCA, and CEDNCA 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 αNCA, kNCA, mNCA, and CEDNCA 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 αNCA, kNCA, mNCA, and CEDNCA 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.

Ultrasound Backscatter Envelope Statistics Parametric Imaging for Liver Fibrosis Characterization: A Review.

Early detection and diagnosis of liver fibrosis is of critical importance. Currently the gold standard for diagnosing liver fibrosis is biopsy. However, liver biopsy is invasive and associated with sampling errors and can lead to complications such as bleeding. Therefore, developing noninvasive imaging techniques for assessing liver fibrosis is of clinical value. Ultrasound has become the first-line tool for the management of chronic liver diseases. However, the commonly used B-mode ultrasound is qualitative and can cause interobserver or intraobserver difference. Ultrasound backscatter envelope statistics parametric imaging is an important group of quantitative ultrasound techniques that have been applied to characterizing different kinds of tissue. However, a state-of-the-art review of ultrasound backscatter envelope statistics parametric imaging for liver fibrosis characterization has not been conducted. In this paper, we focused on the development of ultrasound backscatter envelope statistics parametric imaging techniques for assessing liver fibrosis from 1998 to September 2019. We classified these techniques into six categories: constant false alarm rate, fiber structure extraction technique, acoustic structure quantification, quantile-quantile probability plot, the multi-Rayleigh model, and the Nakagami model. We presented the theoretical background and algorithms for liver fibrosis assessment by ultrasound backscatter envelope statistics parametric imaging. Then, the specific applications of ultrasound backscatter envelope statistics parametric imaging techniques to liver fibrosis evaluation were reviewed and analyzed. Finally, the pros and cons of each technique were discussed, and the future development was suggested.

Characterization of limb lymphedema using the statistical analysis of ultrasound backscattering.

BACKGROUND: Lymphedema is a disease in which tissue swelling is caused by interstitial fluid retention in subcutaneous tissue. It is caused by a compromised lymphatic system. Lymphoscintigraphy is the current and primary modality used to assess lymphatic system dysfunction. Ultrasound elastography is a complementary tool used for evaluating the tissue stiffness of the lymphedematous limb. Tissue stiffness implies the existence of changes in tissue microstructures. However, ultrasound features related to tissue microstructures are neglected in clinical assessments of lymphedematous limbs. In this study, we aimed to evaluate the lymphedematous diagnostic values of ultrasound Nakagami and entropy imaging, which are, respectively, model- and nonmodel-based backscattered statistical analysis methods for scatterer characterization. METHODS: A total of 60 patients were recruited, and lymphoscintigraphy was used to score the patient's clinical severity of each of their limb lymphedema (0: normal; 1: partial lymphatic obstruction; and 2: total lymphatic obstruction). We performed ultrasound examinations to acquire ultrasound backscattered signals for B-mode, Nakagami, and entropy imaging. The envelope amplitude, Nakagami, and entropy values, as a function of the patients' lymphatic obstruction grades, were expressed in terms of their median and interquartile range (IQR). The values were then used in both an independent t test and a receiver operating characteristic (ROC) curve analysis. RESULTS: For each increase in a patient's score from 0 to 2, the envelope amplitude values were 405.44 (IQR: 238.72-488.17), 411.52 (IQR: 298.53-644.25), and 476.37 (IQR: 348.86-648.16), respectively. The Nakagami parameters were 0.16 (IQR: 0.14-0.22), 0.26 (IQR: 0.23-0.34), and 0.24 (IQR: 0.16-0.36), respectively, and the entropy values were 4.55 (IQR: 4.41-4.66), 4.86 (IQR: 4.78-4.99), and 4.87 (IQR: 4.81-4.97), respectively. The P values between the normal control and lymphedema groups obtained from B-mode and Nakagami analysis were larger than 0.05; whereas that of entropy imaging was smaller than 0.05. The areas under the ROC curve for B-mode, Nakagami, and entropy imaging were 0.64 (sensitivity: 70%; specificity: 47.5%), 0.75 (sensitivity: 70%; specificity: 75%), and 0.94 (sensitivity: 95%; specificity: 87.5%), respectively. CONCLUSIONS: The current findings demonstrated the diagnostic values of ultrasound Nakagami and entropy imaging techniques. In particular, the use of non-model-based entropy imaging enables for improved performance when characterizing limb lymphedema.

Cutoff Values of Acoustic Radiation Force Impulse Two-Location Measurements in Different Etiologies of Liver Fibrosis.

BACKGROUND: Acoustic radiation force impulse (ARFI) imaging is a popular modality to measure liver fibrosis. ARFI selects optimal locations for measurement under imaging guiding. However, there are concerns on study locations and observers bias. To decrease the variations, ARFI at two locations was measured with standardized protocol. This study attempted to establish its cutoff values according to Metavir fibrosis score in different etiologies. METHODS: A consecutive series of patients who received liver histology study were prospectively enrolled. All cases had hemogram, liver biochemistry, viral markers, and ARFI two-location measurements within 4 weeks of histology study. A standardized protocol was performed by single technologist. We excluded patients with alanine aminotransferase >5x upper limit normal. RESULTS: Five hundred and ten patients that included 153 seronegative for both HBsAg and anti-HCV Non-B non-C (NBNC), 33 autoimmune liver diseases (AILD), 261 chronic hepatitis B (CHB), and 63 chronic hepatitis C (CHC) were enrolled. About 83% of NBNC patients had fat cell >5%. For diagnosis of liver cirrhosis, the area under receiver operating characteristic curve of NBNC, AILD, CHB, and CHC groups was 0.937, 0.929, 0.784, and 0.937; the cutoff values for mean ARFI were 1.788, 2.095, 1.455, and 1.710 m/s, respectively. The sensitivity and specificity are both over 0.818 for patients with nonalcoholic fatty liver diseases, CHC, and AILD, but the corresponding data are only 0.727-0.756 in CHB. The Fibrosis-4 Score is as good as ARFI on fibrosis assessment in NBNC. CONCLUSION: The performance of ARFI two-location measurement is excellent in NBNC, AILD, and CHC, but is only satisfactory in CHB.

Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging.

Breast cancer is one of the most common cancers among women worldwide. Ultrasound imaging has been widely used in the detection and diagnosis of breast tumors. However, due to factors such as limited spatial resolution and speckle noise, classification of benign and malignant breast tumors using conventional B-mode ultrasound still remains a challenging task. H-scan is a new ultrasound technique that images the relative size of acoustic scatterers. However, the feasibility of H-scan ultrasound imaging in the classification of benign and malignant breast tumors has not been investigated. In this paper, we proposed a new method based on H-scan ultrasound imaging to classify benign and malignant breast tumors. Backscattered ultrasound radiofrequency signals of 100 breast tumors were used (48 benign and 52 malignant cases). H-scan ultrasound images were constructed with the radiofrequency signals by matched filtering using Gaussian-weighted Hermite polynomials. Experimental results showed that benign breast tumors had more red components, while malignant breast tumors had more blue components in H-scan ultrasound images. There were significant differences between the RGB channels of H-scan ultrasound images of benign and malignant breast tumors. We conclude H-scan ultrasound imaging can be used as a new method for classifying benign and malignant breast tumors.

A review of ultrasound detection methods for breast microcalcification.

Breast microcalcifications are one of the important imaging features of early breast cancer and are a key to early breast cancer diagnosis. Ultrasound imaging has been widely used in the detection and diagnosis of breast diseases because of its low cost, nonionizing radiation, and real-time capability. However, due to factors such as limited spatial resolution and speckle noise, it is difficult to detect breast microcalcifications using conventional B-mode ultrasound imaging. Recent studies show that new ultrasound technologies improved the visualization of microcalcifications over conventional B-mode ultrasound imaging. In this paper, a review of the literature on the ultrasonic detection methods of microcalcifications was conducted. The reviewed methods were broadly divided into high-frequency B-mode ultrasound imaging techniques, B-mode ultrasound image processing techniques, ultrasound elastography techniques, time reversal techniques, high spatial frequency techniques, second-order ultrasound field imaging techniques, and photoacoustic imaging techniques. The related principles and research status of these methods were introduced, and the characteristics and limitations of the various methods were discussed and analyzed. Future developments of ultrasonic breast microcalcification detection are suggested.

Hepatic steatosis assessment using ultrasound homodyned-K parametric imaging: the effects of estimators.

BACKGROUND: The homodyned-K (HK) distribution is an important statistical model for describing ultrasound backscatter envelope statistics. HK parametric imaging has shown potential for characterizing hepatic steatosis. However, the feasibility of HK parametric imaging in assessing human hepatic steatosis in vivo remains unclear. METHODS: In this paper, ultrasound HK µ parametric imaging was proposed for assessing human hepatic steatosis in vivo. Two recent estimators for the HK model, RSK (the level-curve method that uses the signal-to-noise ratio (SNR), skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on the first moment of the intensity and two log-moments, namely X- and U-statistics), were investigated. Liver donors (n=72) and patients (n=204) were recruited to evaluate hepatic fat fractions (HFFs) using magnetic resonance spectroscopy and to evaluate the stages of fatty liver disease (normal, mild, moderate, and severe) using liver biopsy with histopathology. Livers were scanned using a 3-MHz ultrasound to construct µ RSK and µ XU images to correlate with HFF analyses and fatty liver stages. The µ RSK and µ XU parametric images were constructed using the sliding window technique with the window side length (WSL) =1-9 pulse lengths (PLs). The diagnostic values of the µ RSK and µ XU parametric imaging methods were evaluated using receiver operating characteristic (ROC) curves. RESULTS: For the 72 participants in Group A, the µ RSK parametric imaging with WSL =2-9 PLs exhibited similar correlation with log10(HFF), and the µ RSK parametric imaging with WSL = 3 PLs had the highest correlation with log10(HFF) (r=0.592); the µ XU parametric imaging with WSL =1-9 PLs exhibited similar correlation with log10(HFF), and the µ XU parametric imaging with WSL =1 PL had the highest correlation with log10(HFF) (r=0.628). For the 204 patients in Group B, the areas under the ROC (AUROCs) obtained using µ RSK for fatty stages ≥ mild (AUROC1), ≥ moderate (AUROC2), and ≥ severe (AUROC3) were (AUROC1, AUROC2, AUROC3) = (0.56, 0.57, 0.53), (0.68, 0.72, 0.75), (0.73, 0.78, 0.80), (0.74, 0.77, 0.79), (0.74, 0.78, 0.79), (0.75, 0.80, 0.82), (0.74, 0.77, 0.83), (0.74, 0.78, 0.84) and (0.73, 0.76, 0.83) for WSL =1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. The AUROCs obtained using µ XU for fatty stages ≥ mild, ≥ moderate, and ≥ severe were (AUROC1, AUROC2, AUROC3) = (0.75, 0.83, 0.81), (0.74, 0.80, 0.80), (0.76, 0.82, 0.82), (0.74, 0.80, 0.84), (0.76, 0.80, 0.83), (0.75, 0.80, 0.84), (0.75, 0.79, 0.85), (0.75, 0.80, 0.85) and (0.73, 0.77, 0.83) for WSL = 1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. CONCLUSIONS: Both the µ RSK and µ XU parametric images are feasible for evaluating human hepatic steatosis. The WSL exhibits little impact on the diagnosing performance of the µ RSK and µ XU parametric imaging. The µ XU parametric imaging provided improved performance compared to the µ RSK parametric imaging in characterizing human hepatic steatosis in vivo.

Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation.

Radiofrequency (RF) ablation (RFA) is the most commonly used minimally invasive procedure for thermal ablation of liver tumors. Ultrasound not only provides real-time feedback of the electrode location for RFA guidance but also enables visualization of the tissue temperature. Changes in backscattered energy (CBE) have been widely applied to ultrasound temperature imaging for assessing thermal ablation. Pilot studies have revealed that significant shadowing features appear in CBE imaging and are caused by the electrode and RFA-induced gas bubbles. To resolve this problem, the current study proposed ultrasound single-phase CBE imaging based on positive CBE values. An in vitro model with tissue samples derived from the porcine tenderloin was used to validate the proposed method. During RFA with various electrode lengths, ultrasound scans of tissue samples were obtained using a clinical ultrasound scanner equipped with a convex array transducer of 3 MHz. Raw image data comprising 256 scan lines of backscattered RF signals were acquired for B-mode, conventional CBE, and single-phase CBE imaging by using the proposed algorithmic scheme. The ablation sizes estimated using CBE imaging and gross examinations were compared to calculate the correlation coefficient. The experimental results indicated that single-phase CBE imaging largely suppressed artificial CBE information in the shadowed region. Moreover, compared with conventional CBE imaging, single-phase CBE imaging provided a more accurate estimation of ablation sizes (the correlation coefficient was higher than 0.8).