Quantitative Ultrasound Methods Research Articles

Simultaneous grading diagnosis of liver fibrosis, inflammation, and steatosis using multimodal quantitative ultrasound and artificial intelligence framework.

Noninvasive, accurate, and simultaneous grading of liver fibrosis, inflammation, and steatosis is valuable for reversing the progression and improving the prognosis quality of chronic liver diseases (CLDs). In this study, we established an artificial intelligence framework for simultaneous grading diagnosis of these three pathological types through fusing multimodal tissue characterization parameters dug by quantitative ultrasound methods derived from ultrasound radiofrequency signals, B-mode images, shear wave elastography images, and clinical ultrasound systems, using the liver biopsy results as the classification criteria. One hundred forty-two patients diagnosed with CLD were enrolled in this study. The results show that for the classification of fibrosis grade ≥ F1, ≥ F2, ≥ F3, and F4, the highest AUCs were respectively 0.69, 0.82, 0.84, and 0.88 with single clinical indicator alone, and were 0.81, 0.83, 0.89, and 0.91 with the proposed method. For the classification of inflammation grade ≥ A2 and A3, the highest AUCs were respectively 0.66 and 0.76 with single clinical indicator alone and were 0.80 and 0.93 with the proposed method. For the classification of steatosis grade ≥ S1 and ≥ S2, the highest AUCs were respectively 0.71 and 0.90 with single clinical indicator alone and were 0.75 and 0.92 with the proposed method. The proposed method can effectively improve the grading diagnosis performance compared with the present clinical indicators and has potential applications for noninvasive, accurate, and simultaneous diagnosis of CLDs.

In-vivo high-frequency quantitative ultrasound-derived parameters of the anterior sclera correlated with level of myopia and presence of staphyloma.

A high-frequency point-of-care (POC) ultrasound instrument was used to evaluate the microstructural and biomechanical properties of the anterior sclera in vivo using parameters computed from quantitative ultrasound (QUS) methods. In this cross-sectional study, both eyes of 85 enrolled patients were scanned with the POC instrument and ultrasound data were processed to obtain QUS parameters. Pearson correlation and multi-linear regression were used to identify relationships between QUS parameters and refractive error (RE) or axial length. After categorising eyes based on RE, binary support vector machine (SVM) classifiers were trained using the QUS or ophthalmic parameters (anterior chamber depth, central corneal thickness, corneal power, and intraocular pressure) to classify each eye. Classifier performance was evaluated by computing the area under the receiver-operating characteristic curve (AUC). Individual QUS parameters correlated with RE and axial length (p < 0.05). Multi-linear regression revealed significant correlation between the set of QUS parameters and both RE (R = 0.49, p < 0.001) and axial length (R = 0.46, p = 0.001). Classifiers trained with QUS parameters achieved higher AUC (𝑝 = 0.06) for identifying myopic eyes (AUC = 0.71) compared to classifiers trained with ophthalmic parameters (AUC = 0.63). QUS-based classifiers attained the highest AUC when identifying highly myopic eyes (AUC = 0.77). QUS parameters correlate with progressing myopia and may be indicative of myopia-induced microstructural and biomechanical changes in the anterior sclera. These methods may provide critical clinical information complementary to standard ophthalmic measurements for predicting myopia progression and risk assessment for posterior staphyloma formation.

ULTRASOUND TECHNOLOGIES IN ALGORITHMS OF CHRONIC LIVER DISEASE MANAGEMENT

Aim. To improve the management algorithm of chronic hepatobiliary pathology by using ultrasound technologies to assess the structure of the liver. Materials and methods. The results of an anonymous electronic survey of 304 doctors using a tailored questionnaire and the authors' own experience of implementing quantitative ultrasound methods of liver assessment at the University Clinic of the Bogomolets National Medical University were analyzed. In accordance with the objective, an analysis of current international guidelines of relevant medical associations was performed. The study of the use of ultrasound diagnostics in the healthcare system of Ukraine was performed using data from open sources of the Ministry of Health of Ukraine and dashboards of the National Health Service of Ukraine (NHSU). Statistical analysis was performed using the MedStat program. The study was approved by the local ethics committee. Results. The availability of basic ultrasound diagnostics of hepatobiliary pathology is high and growing, while modern technologies for quantitative assessment of the liver structure are not sufficiently implemented in medical practice. An improved multilevel patient’s pathway with suspected steatotic liver disease is proposed. Conclusions. Significant limitations of the use of specialized liver examinations in medical practice may adversely affect the quality of medical care. Given the trends in the prevalence of chronic liver disease, the healthcare system needs additional technical equipment for healthcare facilities and focused continuing professional development activities for doctors to ensure the implementation of evidence-based management of chronic hepatobiliary pathology. An improved algorithm of interaction between doctors and the staged use of non-invasive diagnostic tests can help improve the medical care quality and the efficient use of human and financial resources of the healthcare system.

In Vivo Validation of an In Situ Calibration Bead as a Reference for Backscatter Coefficient Calculation

ObjectiveThe study described here was aimed at assessing the capability of quantitative ultrasound (QUS) based on the backscatter coefficient (BSC) for classifying disease states, such as breast cancer response to neoadjuvant chemotherapy and quantification of fatty liver disease. We evaluated the effectiveness of an in situ titanium (Ti) bead as a reference target in calibrating the system and mitigating attenuation and transmission loss effects on BSC estimation. MethodsTraditional BSC estimation methods require external references for calibration, which do not account for ultrasound attenuation or transmission losses through tissues. To address this issue, we used an in situ Ti bead as a reference target, because it can be used to calibrate the system and mitigate the attenuation and transmission loss effects on estimation of the BSC. The capabilities of the in situ calibration approach were assessed by quantifying consistency of BSC estimates from rabbit mammary tumors (N = 21). Specifically, mammary tumors were grown in rabbits and when a tumor reached ≥1 cm in size, a 2 mm Ti bead was implanted in the tumor as a radiological marker and a calibration source for ultrasound. Three days later, the tumors were scanned with an L-14/5 38 array transducer connected to a SonixOne scanner with and without a slab of pork belly placed on top of the tumors. The pork belly acted as an additional source of attenuation and transmission loss. QUS parameters, specifically effective scatterer diameter (ESD) and effective acoustic concentration (EAC), were calculated using calibration spectra from both an external reference phantom and the Ti bead. ResultsFor ESD estimation, the 95% confidence interval between measurements with and without the pork belly layer was 6.0, 27.4 using the in situ bead and 114, 135.1 with the external reference phantom. For EAC estimation, the 95% confidence intervals were –8.1, 0.5 for the bead and –41.5, –32.2 for the phantom. These results indicate that the in situ bead method has reduced bias in QUS estimates because of intervening tissue losses. ConclusionThe use of an in situ Ti bead as a radiological marker not only serves its traditional role but also effectively acts as a calibration target for QUS methods. This approach accounts for attenuation and transmission losses in tissue, resulting in more accurate QUS estimates and offering a promising method for enhanced disease state classification in clinical settings.

Single and multiple scattering quantitative ultrasound methods in muscle

Increased intramuscular fat—or fatty infiltration (FI)—often develops as a consequence of various musculoskeletal and neuromuscular disorders. FI is an important factor for the assessment and intervention of surgical candidacy. Therefore, there is a need for an accessible, non-invasive quantitative, and objective evaluation of FI in muscle. We can exploit the complexity of ultrasound wave propagation in heterogeneous media to extract quantitative features of the fat distribution in muscle. From finite-difference time-domain simulations conducted with maps created from magnetic resonance imaging scans of healthy and injured shoulders, we acquire radiofrequency (RF) ultrasound data. Single and multiple scattering (SS and MS) components of the RF data are separated by using singular value decomposition and eigenvalue thresholding. Spectral and envelope quantitative ultrasound (QUS) parameters are computed from the SS component. MS-based QUS parameters are obtained by extracting the diffusion constant and tracking the SS intensity decay rate. We investigate the relationship between SS and MS-based QUS parameters and an increasing FI, because more FI will lead to more multiple scattering and modified ultrasonic signatures.

Spectral-based quantitative ultrasound for assessing vision degrading myodesopsia

The presence of clinically significant vitreous opacities, referred to as vision degrading myodesopsia (VDM), reduces contrast sensitivity (CS), and visual quality of life. Quantitative ultrasound (QUS) methods operating on grayscale B-mode images were previously developed and validated for quantifying vitreous echodensities. Although a subsequent study comparing the QUS methods across clinical scanners demonstrated no change in QUS efficacy, the methods are sensitive to differences in system parameters and B-mode image formation unless the backscatter data is normalized. Technological advancements in clinical scanners allow for easy access to raw radiofrequency (RF) data for more advanced processing methods. Here, we develop QUS methods that exploit RF echo data to generate robust user- and system-independent parameters for quantifying vitreous echodensities based on the echo signal power spectrum (PS). However, the sparsity of echodensities in the vitreous body is incompatible with underlying assumptions of QUS methods based on measurements of the backscatter coefficient or envelope statistics. We, therefore, implement QUS methods that parameterize the PS and correlate these parameters with visual function as measured by CS. Results from this study are the first step toward developing and validating robust, user-, and system-independent QUS methods for evaluating VDM.

Single and multiple scattering quantitative ultrasound methods in the lung

Lung ultrasound images are qualitative and rely on subjective interpretation for diagnosis. Ideally, quantitative ultrasound (QUS) methods applied to lung ultrasound data would provide biomarkers associated with specific diseases in an absolute fashion. While QUS methods are successful in numerous organ systems in preclinical and clinical applications, their direct application to lung ultrasound data requires taking multiple scattering (MS) into account. This presentation shows QUS methods independently exploiting MS and single scattering (SS) components of radio-frequency (RF) data, acquired from lungs from rodent models of pulmonary edema and fibrosis. SS and MS components were obtained using singular value decomposition and eigenvalue thresholding. Spectral and envelope QUS parameters were computed from the SS component. MS-based QUS parameters were obtained by extracting the diffusion constant and tracking the SS intensity decay rate. Stepwise linear discriminant analyses using only three QUS parameters yielded strong correlations between wet-to-dry ratio in healthy and pulmonary edema rats. Strong correlations were also obtained between QUS parameters and modified histological Ashcroft scores in healthy and pulmonary fibrosis rats. These results demonstrate the value of QUS parameters obtained from SS and MS approaches for assessing lung diseases with high specificity and sensitivity. [Supported in part by R21HL154156 and W81XWH1810101.]

Machine Independence of Ultrasound-Based Quantification of Vitreous Echodensities.

Quantitative ultrasound (QUS) provides objective indices of Vision Degrading Myodesopsia (VDM) that correlate with contrast sensitivity (CS). To date, QUS methods were only tested on a single ultrasound machine. Here, we evaluate whether QUS measurements are machine independent. In this cross-sectional study, 47 eyes (24 subjects; age = 53.2 ± 14.4 years) were evaluated with Freiburg acuity contrast testing (%Weber), and ultrasonography using 2 machines: one with a 15-MHz single-element transducer and one with a 5-ring, 20-MHz annular-array. Images were acquired from each system in sequential scans. Artifact-free, log-compressed envelope data were processed to yield three parameters (mean amplitude, M; energy, E; and percentage filled by echodensities, P50) and a composite score (C). A B-mode normalization method was applied to the 20-MHz datasets to match QUS parameters at both frequencies. Statistical analyses were performed to evaluate correlations among CS, E, M, P50, and C for both machines. QUS parameters from each machine correlated with CS (R ≥ 0.57, P < 0.001) and there was correlation between machines (R ≥ 0.84, P < 0.001). Correlations between CS and QUS parameters were statistically similar for both machines (P ≥ 0.14) except when the 20-MHz data were normalized (P = 0.04). Reproducibility of QUS parameters computed from 20-MHz data were satisfactory (52.3%-96.3%) with intraclass correlation values exceeding 0.80 (P < 0.001). The high correlation between QUS parameters from both machines combined with a statistically similar correlation to CS suggests QUS is an effective, machine-independent, quantitative measure of vitreous echodensities. QUS may be applied across clinical ophthalmic ultrasound scanners and imaging frequencies to effectively evaluate VDM.

Skeletal Muscle Assessment Using Quantitative Ultrasound: A Narrative Review.

Ultrasound (US) is an important imaging tool for skeletal muscle analysis. The advantages of US include point-of-care access, real-time imaging, cost-effectiveness, and absence of ionizing radiation. However, US can be highly dependent on the operator and/or US system, and a portion of the potentially useful information carried by raw sonographic data is discarded in image formation for routine qualitative US. Quantitative ultrasound (QUS) methods provide analysis of the raw or post-processed data, revealing additional information about normal tissue structure and disease status. There are four QUS categories that can be used on muscle and are important to review. First, quantitative data derived from B-mode images can help determine the macrostructural anatomy and microstructural morphology of muscle tissues. Second, US elastography can provide information about muscle elasticity or stiffness through strain elastography or shear wave elastography (SWE). Strain elastography measures the induced tissue strain caused either by internal or external compression by tracking tissue displacement with detectable speckle in B-mode images of the examined tissue. SWE measures the speed of induced shear waves traveling through the tissue to estimate the tissue elasticity. These shear waves may be produced using external mechanical vibrations or internal "push pulse" ultrasound stimuli. Third, raw radiofrequency signal analyses provide estimates of fundamental tissue parameters, such as the speed of sound, attenuation coefficient, and backscatter coefficient, which correspond to information about muscle tissue microstructure and composition. Lastly, envelope statistical analyses apply various probability distributions to estimate the number density of scatterers and quantify coherent to incoherent signals, thus providing information about microstructural properties of muscle tissue. This review will examine these QUS techniques, published results on QUS evaluation of skeletal muscles, and the strengths and limitations of QUS in skeletal muscle analysis.

High-frequency ultrasound point-of-care device to quantify myopia-induced microstructural changes in the anterior sclera.

To develop a point-of-care (POC) device using high-frequency ultrasound (US) for evaluating microstructural changes in the anterior sclera associated with myopia. The proposed POC device must satisfy four primary requirements for effective clinical use: the measurement component is handheld; the software must be simple and provide real-time feedback; patient safety and health data security requirements set forth by relevant governing bodies must be satisfied and the measurement data must have sufficient signal-to-noise ratio (SNR) and repeatability. Radiofrequency (RF) echo data acquired by the POC device will be processed using our quantitative US methods to characterise tissue microstructure and biomechanical properties. All stated requirements have been met in the developed POC device. The high-frequency transducer is housed in a custom, 3D-printed, pen-like holder that allows for easy measurements of the anterior sclera. Custom software provides a simple interface for data acquisition, real-time data display and secure data storage. Exposimetry measurements of the US pressure field indicate device compliance with United States Food and Drug Administration limits for ophthalmic US. In vivo measurements on a volunteer suggest the RF data SNR and acquisition consistency are suitable for quantitative analysis. A fully functioning POC device using high-frequency US has been created for evaluating the microstructure of the anterior sclera. Planned studies using the POC device to scan the eyes of myopia patients will help clarify how the anterior sclera microstructure may be affected by myopia. If effective, this portable, inexpensive and user-friendly system could be an important part of routine eye examinations.

Classification of Metastatic Lymph Nodes In Vivo Using Quantitative Ultrasound at Clinical Frequencies.

Quantitative ultrasound (QUS) methods characterizing the backscattered echo signal have been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods have been successful in detecting metastases in surgically excised lymph nodes (LNs), but limited evidence exists regarding the efficacy of QUS for evaluating LNs in vivo at clinical frequencies (2-10 MHz). In this study, a clinical scanner and 10-MHz linear probe were used to collect radiofrequency (RF) echo data of LNs in vivo from 19 cancer patients. QUS methods were applied to estimate parameters derived from the backscatter coefficient (BSC) and statistics of the envelope-detected RF signal. QUS parameters were used to train classifiers based on linear discriminant analysis (LDA) and support vector machines (SVMs). Two BSC-based parameters, scatterer diameter and acoustic concentration, were the most effective for accurately detecting metastatic LNs, with both LDA and SVMs achieving areas under the receiver operating characteristic (AUROC) curve ≥0.94. A strategy of classifying LNs based on the echo frame with the highest cancer probability improved performance to 88% specificity at 100% sensitivity (AUROC=0.99). These results provide encouraging evidence that QUS applied at clinical frequencies may be effective at accurately identifying metastatic LNs in vivo, helping in diagnosis while reducing unnecessary biopsies and surgical treatments.

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.

Comparison of Quantitative Ultrasound Methods to Classify Dystrophic and Obese Models of Skeletal Muscle.

In this study, we compared multiple quantitative ultrasound metrics for the purpose of differentiating muscle in 20 healthy, 10 dystrophic and 10 obese mice. High-frequency ultrasound scans were acquired on dystrophic (D2-mdx), obese (db/db) and control mouse hindlimbs. A total of 248 image features were extracted from each scan, using brightness-mode statistics, Canny edge detection metrics, Haralick features, envelope statistics and radiofrequency statistics. Naïve Bayes and other classifiers were trained on single and pairs of features. The a parameter from the Homodyned K distribution at 40 MHz achieved the best univariate classification (accuracy=85.3%). Maximum classification accuracy of 97.7% was achieved using a logistic regression classifier on the feature pair of a2 (K distribution) at 30 MHz and brightness-mode variance at 40MHz. Dystrophic and obese mice have muscle with distinct acoustic properties and can be classified to a high level of accuracy using a combination of multiple features.

Spatially Variant Ultrasound Attenuation Mapping Using a Regularized Linear Least-Squares Approach

Quantitative ultrasound methods aim to estimate the acoustic properties of the underlying medium, such as the attenuation and backscatter coefficients, and have applications in various areas including tissue characterization. In practice, tissue heterogeneity makes the coefficient estimation challenging. In this work, we propose a computationally efficient algorithm to map spatial variations of the attenuation coefficient. Our proposed approach adopts a fast, linear least-squares strategy to fit the signal model to data from pulse-echo measurements. As opposed to existing approaches, we directly estimate the attenuation map, that is, the local attenuation coefficient at each axial location by solving a joint estimation problem. In particular, we impose a physical model that couples all these local estimates and combine it with a smooth regularization to obtain a smooth map. Compared to the conventional spectral log difference method and the more recent ALGEBRA approach, we demonstrate that the attenuation estimates obtained by our method are more accurate and better correlate with the ground-truth attenuation profiles over a wide range of spatial and contrast resolutions.

In vivo assessment of lymph nodes using quantitative ultrasound on a clinical scanner: A preliminary study

Quantitative ultrasound (QUS) methods evaluating the backscattered echo signal provide a means to infer the microstructural properties of soft tissues. High-frequency (≥20 MHz) QUS has been used to detect metastases in excised human lymph nodes (LNs), but limited evidence exists about the efficacy of conventional-frequency QUS for characterizing LNs in vivo using a standard clinical scanner. In this study, 11 LNs from 11 patients with known primary tumors were scanned in vivo using a GE Logiq E9 scanner with a 10-MHz linear array. Metastatic status was determined by fine needle aspiration. Echo frames were processed using QUS methods to compute five parameters from the backscattered echo power spectrum and four from histograms of the echo envelope values. The spectral slope was found to be significantly higher in metastatic nodes (p &amp;lt; 0.001), whereas benign nodes exhibited significantly lower values of spectral intercept (p &amp;lt; 0.001), midband fit (p = 0.004), scatterer diameter (ESD, p &amp;lt; 0.001), and acoustic concentration (EAC, p = 0.003). A linear discriminator operating on ESD and EAC correctly differentiated benign and metastatic nodes with sensitivity of 0.89, specificity of 0.83, and area under the ROC curve of 0.91. These preliminary results demonstrate the feasibility of characterizing LNs in vivo at conventional frequencies using a clinical scanner.

THE EFFECT OF SPORTS IN PROMOTING THE ENHANCEMENT OF ADULT BONE DENSITY

ABSTRACT Introduction: Exercise is an important part of osteoporosis treatment. A moderate amount of exercise can improve bone metabolism, improve bone biomechanics and increase bone density. Objective: To study the effects of different sports on adult bone mineral density. Methods: We selected volunteers to perform different exercises and used quantitative ultrasound and bioelectrical impedance methods to test the volunteers. Results: Exercise can increase the content of lean body mass in body composition and reduce body fat percentage. The calcaneal bone mineral density of physical education students is positively correlated with low body weight. Conclusion: Exercise can promote the bone mineral density of young adults. Stronger weight-bearing exercises can better promote the increase of bone density. Level of evidence II; Therapeutic studies - investigation of treatment results.

In vivo assessment of pulmonary edema and fibrosis in rats using separation of single and multiple scattering contributions and quantitative ultrasound

The application of spectral quantitative ultrasound (QUS) and envelope statistical methods to lung ultrasound is complicated due to the presence of multiple scattering (MS). In this study, the relationship between QUS assessment of lung disease and scattering regime was explored by applying QUS to lung ultrasound data, where the single scattering (SS) and MS components were separated. Data were acquired by a Verasonics Vantage ultrasound scanner from 15 healthy rats, 19 edematous rats, and 20 fibrotic rats. SS and MS components of the data were separated by a random matrix theory approach. Spectral QUS and envelope statistical parameters were then estimated from the SS and MS data separately. Initial results were obtained using the healthy and pulmonary edema data, where the extracted QUS parameters were correlated to the wet-to-dry (W/D) weight ratio, a gold standard measurement of edema. Several QUS parameters were significantly correlated to W/D ratio for both the SS and MS data, and the highest correlation coefficient was 0.53 using the SS data and 0.48 using the MS data. These results demonstrate the utility of QUS for assessing lung disease and provide further insight on the effects of SS and MS on spectral QUS and envelope statistical parameters.

Multiparametric Quantitative US Examination of Liver Fibrosis: A Feature-Engineering and Machine-Learning Based Analysis.

Quantitative ultrasound (QUS), which attempts to extract quantitative features from the US radiofrequency (RF) or envelope data for tissue characterization, is becoming a promising technique for noninvasive assessments of liver fibrosis. However, the number of feature variables examined and finally used in the existing QUS methods is typically small, limiting the diagnostic performance. Therefore, this paper devises a new multiparametric QUS (MP-QUS) method which enables the extraction of a large number of feature variables from US RF signals and allows for the use of feature-engineering and machine-learning based algorithms for liver fibrosis assessment. In the MP-QUS, eighty-four feature variables were extracted from multiple QUS parametric maps derived from the RF signals and the envelope data. Afterwards, feature reduction and selection were performed in turn to remove the feature redundancy and identify the best combination of features in the reduced feature set. Finally, a variety of machine-learning algorithms were tested for fibrosis classification with the selected features, based on the results of which the optimal classifier was established. The performance of the proposed MP-QUS method for staging liver fibrosis was evaluated on an animal model, with histologic examination as the reference standard. The mean accuracy, sensitivity, specificity and area under the receiver-operating-characteristic curve achieved by MP-QUS are respectively 83.38%, 86.04%, 80.82%, and 0.891 for recognizing significant liver fibrosis, and 85.50%, 88.92%, 85.24%, and 0.924 for diagnosing liver cirrhosis. The proposed MP-QUS method paves a way for its future extension to assess liver fibrosis in human subjects.

In vivo pulse-echo measurement of apparent broadband attenuation and Q factor in cortical bone: a preliminary study

Quantitative ultrasound (QUS) methods have been introduced to assess cortical bone health at the radius and tibia through the assessment of cortical thickness (Ct.Th), cortical porosity and bulk wave velocities. Ultrasonic attenuation is another QUS parameter which is not currently used. We assessed the feasibility of in vivo measurement of ultrasonic attenuation in cortical bone with a broadband transducer with 3.5 MHz center frequency. Echoes from the periosteal and endosteal interfaces were fitted with Gaussian pulses using sparse signal processing. Then, the slope of the broadband ultrasonic attenuation (Ct.nBUA) in cortical bone and quality factor were calculated with a parametric approach based on the center-frequency shift. Five human subjects were measured at the one-third distal radius with pulse-echo ultrasound, and reference data was obtained with high-resolution x-ray peripheral computed tomography (Ct.Th and cortical volumetric bone mineral density (Ct.vBMD)). Ct.Th was used in the calculation of Ct.nBUA while is obtained solely from ultrasound data. The values of Ct.nBUA (6.7 ± 2.2 dB MHz−1 .cm−1) and (8.6 ± 3.1%) were consistent with the literature data and were correlated to Ct.vBMD (, , RMSE = 0.56 dB.MHz−1.cm−1, and , , RMSE = 0.76%). This preliminary study suggests that the attenuation of an ultrasound signal propagating in cortical bone can be measured in vivo at the one-third distal radius and that it provides an information on bone quality as attenuation values were correlated to Ct.vBMD. It remains to ascertain that Ct.nBUA and measured here exactly reflect the true (intrinsic) ultrasonic attenuation in cortical bone. Measurement of attenuation may be considered useful for assessing bone health combined with the measurement of Ct.Th, porosity and bulk wave velocities in multimodal cortical bone QUS methods.

In vivo assessment of pulmonary fibrosis and edema in rodents using the backscatter coefficient and envelope statistics.

Quantitative ultrasound methods based on the backscatter coefficient (BSC) and envelope statistics have been used to quantify disease in a wide variety of tissues, such as prostate, lymph nodes, breast, and thyroid. However, to date, these methods have not been investigated in the lung. In this study, lung properties were quantified by BSC and envelope statistical parameters in normal, fibrotic, and edematous rat lungs in vivo. The average and standard deviation of each parameter were calculated for each lung as well as the evolution of each parameter with acoustic propagation time within the lung. The transport mean free path and backscattered frequency shift, two parameters that have been successfully used to assess pulmonary fibrosis and edema in prior work, were evaluated in combination with the BSC and envelope statistical parameters. Multiple BSC and envelope statistical parameters were found to provide contrast between control and diseased lungs. BSC and envelope statistical parameters were also significantly correlated with fibrosis severity using the modified Ashcroft fibrosis score as the histological gold standard. These results demonstrate the potential for BSC and envelope statistical parameters to improve the diagnosis of pulmonary fibrosis and edema as well as monitor pulmonary fibrosis.