Bone Health in Premenopausal Women with Coeliac Disease: An Observational Study.

Low bone mineral density (BMD) is common in adults with coeliac disease (CD), even in individuals adhering to a gluten-free diet (GFD). Women are more likely to have low BMD and have an increased risk of osteoporosis, so women with pre-existing low BMD related to CD are at an even higher risk. BMD assessed by dual X-ray absorptiometry (DXA) and bone quality assessed through quantitative ultrasound (QUS) were investigated in 31 premenopausal women with CD consuming a GFD, and 39 matched healthy controls from the Lower North Island, New Zealand. In addition, bone metabolism and nutrient status were assessed, and four-day diet diaries were used to estimate nutrient intake. No statistically significant differences were found in BMD assessed by DXA between the two groups at the hip, lumbar spine or forearm. However, the parameters measured by the QUS were significantly lower in CD participants. Dietary data indicated significantly lower intakes of energy, dietary fibre, magnesium and phosphorus in women with CD, likely as a result of a reduced intake of wholegrain foods, and suggested that both groups had inadequate intake of calcium. No significant differences were demonstrated in biochemical parameters. BMD and bone biomarkers indicated no differences between coeliac and healthy women in New Zealand. However, these findings suggest that QUS may be more sensitive for the coeliac population, due to the disease's affect on the trabecular bone, and warrant further research.

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

BACKGROUND: 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. 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). RESULTS: 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). CONCLUSIONS: 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.

Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.

BACKGROUND: It was essential to identify individuals at high risk of fragility fracture and prevented them due to the significant morbidity, mortality, and economic burden associated with fragility fracture. The quantitative ultrasound (QUS) showed promise in assessing bone structure characteristics and determining the risk of fragility fracture. AIMS: To evaluate the performance of a multi-channel residual network (MResNet) based on ultrasonic radiofrequency (RF) signal to discriminate fragility fractures retrospectively in postmenopausal women, and compared it with the traditional parameter of QUS, speed of sound (SOS), and bone mineral density (BMD) acquired with dual X-ray absorptiometry (DXA). METHODS: Using QUS, RF signal and SOS were acquired for 246 postmenopausal women. An MResNet was utilized, based on the RF signal, to categorize individuals with an elevated risk of fragility fracture. DXA was employed to obtain BMD at the lumbar, hip, and femoral neck. The fracture history of all adult subjects was gathered. Analyzing the odds ratios (OR) and the area under the receiver operator characteristic curves (AUC) was done to evaluate the effectiveness of various methods in discriminating fragility fracture. RESULTS: Among the 246 postmenopausal women, 170 belonged to the non-fracture group, 50 to the vertebral group, and 26 to the non-vertebral fracture group. MResNet was competent to discriminate any fragility fracture (OR = 2.64; AUC = 0.74), Vertebral fracture (OR = 3.02; AUC = 0.77), and non-vertebral fracture (OR = 2.01; AUC = 0.69). After being modified by clinical covariates, the efficiency of MResNet was further improved to OR = 3.31-4.08, AUC = 0.81-0.83 among all fracture groups, which significantly surpassed QUS-SOS (OR = 1.32-1.36; AUC = 0.60) and DXA-BMD (OR = 1.23-2.94; AUC = 0.63-0.76). CONCLUSIONS: This pilot cross-sectional study demonstrates that the MResNet model based on the ultrasonic RF signal shows promising performance in discriminating fragility fractures in postmenopausal women. When incorporating clinical covariates, the efficiency of the modified MResNet is further enhanced, surpassing the performance of QUS-SOS and DXA-BMD in terms of OR and AUC. These findings highlight the potential of the MResNet as a promising approach for fracture risk assessment. Future research should focus on larger and more diverse populations to validate these results and explore its clinical applications.

Dynamic contrast enhanced ultrasound in differential diagnosis of hepatocellular carcinoma: A systematic review and meta-analysis.

BACKGROUND: Non-invasive differential diagnosis between hepatocellular carcinoma (HCC) and other liver cancer (i.e. cholangiocarcinoma or metastasis) is highly challenging and definitive diagnosis still relies on histological exam. The patterns of enhancement and wash-out of liver nodules can be used to stratify the risk of malignancy only in cirrhotic patients and HCC frequently shows atypical features. Dynamic contrast-enhanced ultrasound (DCEUS) with standardized software could help to overcome these obstacles, providing functional and quantitative parameters and potentially improving accuracy in the evaluation of tumor perfusion. AIM: To explore clinical evidence regarding the application of DCEUS in the differential diagnosis of liver nodules. METHODS: A comprehensive literature search of clinical studies was performed to identify the parameters of DCEUS that could relate to histological diagnosis. In accordance with the study protocol, a qualitative and quantitative analysis of the evidence was planned. RESULTS: Rise time was significantly higher in HCC patients with a standardized mean difference (SMD) of 0.83 (95%CI: 0.48-1.18). Similarly, other statistically significant parameters were mean transit time local with a SMD of 0.73 (95%CI: 0.20-1.27), peak enhancement with a SMD of 0.37 (95%CI: 0.03-0.70), area wash-in area under the curve with a SMD of 0.47 (95%CI: 0.13-0.81), wash-out area under the curve with a SMD of 0.55 (95%CI: 0.21-0.89) and wash-in and wash-out area under the curve with SMD of 0.51 (95%CI: 0.17-0.85). SMD resulted not significant in fall time and wash-in rate, but the latter presented a trend towards greater values in HCC compared to intrahepatic cholangiocarcinoma. CONCLUSION: DCEUS could improve non-invasive diagnosis of HCC, leading to less liver biopsy and early treatment. This quantitative analysis needs to be applied on larger cohorts to confirm these preliminary results.

The Biomechanics of Musculoskeletal Tissues during Activities of Daily Living: Dynamic Assessment Using Quantitative Transmission-Mode Ultrasound Techniques.

The measurement of musculoskeletal tissue properties and loading patterns during physical activity is important for understanding the adaptation mechanisms of tissues such as bone, tendon, and muscle tissues, particularly with injury and repair. Although the properties and loading of these connective tissues have been quantified using direct measurement techniques, these methods are highly invasive and often prevent or interfere with normal activity patterns. Indirect biomechanical methods, such as estimates based on electromyography, ultrasound, and inverse dynamics, are used more widely but are known to yield different parameter values than direct measurements. Through a series of literature searches of electronic databases, including Pubmed, Embase, Web of Science, and IEEE Explore, this paper reviews current methods used for the in vivo measurement of human musculoskeletal tissue and describes the operating principals, application, and emerging research findings gained from the use of quantitative transmission-mode ultrasound measurement techniques to non-invasively characterize human bone, tendon, and muscle properties at rest and during activities of daily living. In contrast to standard ultrasound imaging approaches, these techniques assess the interaction between ultrasound compression waves and connective tissues to provide quantifiable parameters associated with the structure, instantaneous elastic modulus, and density of tissues. By taking advantage of the physical relationship between the axial velocity of ultrasound compression waves and the instantaneous modulus of the propagation material, these techniques can also be used to estimate the in vivo loading environment of relatively superficial soft connective tissues during sports and activities of daily living. This paper highlights key findings from clinical studies in which quantitative transmission-mode ultrasound has been used to measure the properties and loading of bone, tendon, and muscle tissue during common physical activities in healthy and pathological populations.

Simulation of ultrasound backscatter coefficient measurement using the finite element method.

Ultrasound backscatter coefficient (BSC) measurement is a method for assessing tissue morphology that can inform on pathologies such as cancer. The BSC measurement is, however, limited by the accuracy with which the investigator can normalise their results to account for frequency dependent effects of diffraction and attenuation whilst performing such measurements. We propose a simulation-based approach to investigate the potential sources of error in assessing the BSC. Presented is a tool for the 2D Finite Element (FE) simulation mimicking a BSC measurement using the planar reflector substitution method in reduced dimensionality. The results of this are verified against new derivations of BSC equations also in reduced dimensionality. These new derivations allow computation of BSC estimates based on the scattering from a 2D scattering area, a line reference reflector and a theoretical value for the BSC of a 2D distribution of scatterers. This 2D model was designed to generate lightweight simulations that allow rapid investigation of the factors associated with BSC measurement, allowing the investigator to generate large data sets in relatively short time scales. Under the conditions for an incoherent scattering medium, the simulations produced BSC estimates within 6% of the theoretical value calculated from the simulation domain, a result reproduced across a range of source f-numbers. This value of error compares well to both estimated errors from other simulation based approaches and to physical experiments. The mathematical and simulation models described here provide a theoretical and experimental framework for continued investigation into factors affecting the accuracy of BSC measurements.

Ultrasound screening of paediatric non-alcoholic fatty liver disease (NAFLD): A critical literature review.

INTRODUCTION: Paediatric NAFLD is an increasing global health concern, which can be effectively managed with early detection. Screening, using accurate, affordable, and accessible tests is recommended, however, there is currently no consensus on the most appropriate tests. Although ultrasound techniques are widely used, their performance against reference tests have not been fully assessed. METHODS: A literature search of related databases for peer-reviewed original articles published from January 2010-March 2024 was conducted. Appropriate tools were used to systematise and document the search results and selected studies were quality assessed and critically appraised. Extracted data was subjected to thematic analysis and narrative synthesis. RESULTS: Eighteen articles met the inclusion criteria. B-mode and Quantitative ultrasound techniques were compared against MR spectroscopy, MRI-PDFF and Liver biopsy. CONCLUSION: Liver echogenicity and Steato-scores were the B-mode methods used. The former was less effective, with a maximum reported sensitivity of 70%. The latter reached up to 100% sensitivity, and >80% specificity. Ultrasound performed better with moderate-severe steatosis. There was not enough evidence to support steatosis grading, possibly due to small sample sizes and lack of established cut-off values. QUS (Quantitative Ultrasound)) methods including Continuous Attenuation Parameter (CAP), Attenuation Coefficient (AC), Ultrasound derived fat fraction (UDFF), Tissue Scatter Imaging (TSI) Hepato-Renal Index (HRI), Heterogeneity Index (HIA), Computer Assisted Ultrasound (CAUS) and Picture Archiving and Communication System (PACS-based Image analysis performed better than B-mode methods. Although QUS demonstrated excellent performance, with sensitivity and specificity of up to 100%, this will require further verification before implementation in practice. PRACTICE IMPLICATIONS: Ultrasound techniques can effectively be used for paediatric NAFLD screening, especially in higher-risk subjects. The steato-scores method is currently recommendable for this, with excellent potential for the use of QUS, after cut-off values and validation requirements have been addressed.

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.

Diagnostic performance of quantitative ultrasonography for hepatic steatosis in a health screening program: a prospective single-center study.

PURPOSE: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) as the reference standard. METHODS: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses. RESULTS: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (ß=7.134), hepatic fibrosis (ß=4.808), alanine aminotransferase (ß=0.202), triglyceride levels (ß=0.027), and diabetes mellitus (ß=3.710). CONCLUSION: QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Methodology exploration and reproducibility evaluation of TAI and TSI for quantitative ultrasound assessment of hepatic steatosis.

Background and aim: New quantitative ultrasound techniques can be used to quantify hepatic steatosis, including tissue attenuation imaging (TAI), tissue scatter -distribution imaging (TSI), and the hepatorenal index (HRI). However, the measurement norms and the effects of fasting on these measurements remain unclear. The present study performed a methodological exploration and investigated the reliability of these measurements. Methods: In total, 103 participants were prospectively recruited for ultrasonography and magnetic resonance imaging (MRI) scans. For the TAI and TSI data, the upper (2 cm), middle (4 cm) and lower (6 cm) areas determined according to the depth of the region of interest from the liver capsule, were sampled three times. Correlation analyses were performed to compare the measurements of TAI, TSI, and HRI with the controlled attenuation parameter (CAP) or MRI-proton density fat fraction (MRI-PDFF). Intra- and inter-operator repeatability was assessed using intraclass correlation coefficients. The effects of fasting on these measurements were then compared. Results: The TAI and TSI measurements obtained from the upper and middle depths exhibited stronger correlations with the CAP measurements than those obtained from the lower depth. Specifically, the mean TAI had a significant positive correlation with MRI-PDFF (r = 0.753, P < 0.0001). TAI and TSI measurements exhibited excellent intra- (0.933 and 0.925, respectively) and inter- (0.896 and 0.766, respectively) examiner reliability. However, the correlation between HRI and CAP measurements was only 0.281, with no significant correlation with MRI-PDFF, and intra- and inter-examiner reproducibility of 0.458 and 0.343, respectively. Fasting did not affect these measurements. Conclusions: TAI and TSI measurements demonstrated good intra- and interobserver reliability and correlated well with CAP and MRI-PDFF measurements. However, in practice-based clinical applications, the sampling depth should be controlled within 2-4 cm of the hepatic capsule; no fasting is required before the examination.

Application of Quantitative Ultrasonography and Artificial Intelligence for Assessing Severity of Fatty Liver: A Pilot Study.

Non-alcoholic fatty liver disease (NAFLD), prevalent among conditions like obesity and diabetes, is globally significant. Existing ultrasound diagnosis methods, despite their use, often lack accuracy and precision, necessitating innovative solutions like AI. This study aims to validate an AI-enhanced quantitative ultrasound (QUS) algorithm for NAFLD severity assessment and compare its performance with Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF), a conventional diagnostic tool. A single-center cross-sectional pilot study was conducted. Liver fat content was estimated using an AI-enhanced quantitative ultrasound attenuation coefficient (QUS-AC) of Barreleye Inc. with an AI-based QUS algorithm and two conventional ultrasound techniques, FibroTouch Ultrasound Attenuation Parameter (UAP) and Canon Attenuation Imaging (ATI). The results were compared with MRI-PDFF values. The intraclass correlation coefficient (ICC) was also assessed. Significant correlation was found between the QUS-AC and the MRI-PDFF, reflected by an R value of 0.95. On other hand, ATI and UAP displayed lower correlations with MRI-PDFF, yielding R values of 0.73 and 0.51, respectively. In addition, ICC for QUS-AC was 0.983 for individual observations. On the other hand, the ICCs for ATI and UAP were 0.76 and 0.39, respectively. Our findings suggest that AC with AI-enhanced QUS could serve as a valuable tool for the non-invasive diagnosis of NAFLD.

Unsupervised Learning-Based Measurement of Ultrasonic Axial Transmission Velocity in Neonatal Bone.

OBJECTIVES: To develop a robust algorithm for estimating ultrasonic axial transmission velocity from neonatal tibial bone, and to investigate the relationships between ultrasound velocity and neonatal anthropometric measurements as well as clinical biochemical markers of skeletal health. METHODS: This study presents an unsupervised learning approach for the automatic detection of first arrival time and estimation of ultrasonic velocity from axial transmission waveforms, which potentially indicates bone quality. The proposed method combines the ReliefF algorithm and fuzzy C-means clustering. It was first validated using an in vitro dataset measured from a Sawbones phantom. It was subsequently applied on in vivo signals collected from 40 infants, comprising 21 males and 19 females. The extracted neonatal ultrasonic velocity was subjected to statistical analysis to explore correlations with the infants' anthropometric features and biochemical indicators. RESULTS: The results of in vivo data analysis revealed significant correlations between the extracted ultrasonic velocity and the neonatal anthropometric measurements and biochemical markers. The velocity of first arrival signals showed good associations with body weight (ρ = 0.583, P value <.001), body length (ρ = 0.583, P value <.001), and gestational age (ρ = 0.557, P value <.001). CONCLUSION: These findings suggest that fuzzy C-means clustering is highly effective in extracting ultrasonic propagating velocity in bone and reliably applicable in in vivo measurement. This work is a preliminary study that holds promise in advancing the development of a standardized ultrasonic tool for assessing neonatal bone health. Such advancements are crucial in the accurate diagnosis of bone growth disorders.

Effect of a 3-Month Single-Drug Approach Using Rivaroxaban for Symptomatic Proximal Deep Vein Thrombosis.

Background: Factor Xa inhibitors, such as rivaroxaban, are increasing the convenience of treatment for deep vein thrombosis (DVT). Limited evidence exists regarding clot evaluation at 3 months after treatment for DVT. Methods and Results: We retrospectively analyzed the clinical course of symptomatic proximal DVT in patients who received 3 months of anticoagulation treatment at our hospital. Patients treated with the rivaroxaban single-drug approach were classified as group A (n=42). Patients treated with unfractionated heparin (UFH) or subcutaneous fondaparinux followed by vitamin K antagonist comprised group B (n=60) as an historical cohort. The quantitative ultrasound thrombosis (QUT) score was used to quantify clot burden before and after treatment. No significant differences were observed in patient characteristics between the groups. Serum D-dimer levels in both groups significantly improved after treatment. Clot volume assessed using QUT also reduced significantly in both groups. The QUT score in groups A and B improved from 7.5 [4.8, 12.0] to 3.0 [1.8, 5.0; P=0.000] and 7.0 [4.0, 9.8] to 3.0 [2.0, 5.0; P=0.000], respectively. The change in QUT (∆QUT) was significantly greater in group A compared with group B (-4.5 [-8.25, -2.0] vs. -2.0 [-6.0, 0.0]; P=0.005). Conclusions: We were able to demonstrate the effectiveness of DVT treatment using rivaroxaban over a period of 3 months from onset, in terms of clot regression evaluated using the QUT score.

Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility study.

Background: In patients with locally advanced breast cancer (LABC) receiving neoadjuvant chemotherapy (NAC), quantitative ultrasound (QUS) radiomics can predict final responses early within 4 of 16-18 weeks of treatment. The current study was planned to study the feasibility of a QUS-radiomics model-guided adaptive chemotherapy. Methods: The phase 2 open-label randomized controlled trial included patients with LABC planned for NAC. Patients were randomly allocated in 1:1 ratio to a standard arm or experimental arm stratified by hormonal receptor status. All patients were planned for standard anthracycline and taxane-based NAC as decided by their medical oncologist. Patients underwent QUS imaging using a clinical ultrasound device before the initiation of NAC and after the 1st and 4th weeks of treatment. A support vector machine-based radiomics model developed from an earlier cohort of patients was used to predict treatment response at the 4th week of NAC. In the standard arm, patients continued to receive planned chemotherapy with the treating oncologists blinded to results. In the experimental arm, the QUS-based prediction was conveyed to the responsible oncologist, and any changes to the planned chemotherapy for predicted non-responders were made by the responsible oncologist. All patients underwent surgery following NAC, and the final response was evaluated based on histopathological examination. Results: Between June 2018 and July 2021, 60 patients were accrued in the study arm, with 28 patients in each arm available for final analysis. In patients without a change in chemotherapy regimen (53 of 56 patients total), the QUS-radiomics model at week 4 of NAC that was used demonstrated an accuracy of 97%, respectively, in predicting the final treatment response. Seven patients were predicted to be non-responders (observational arm (n=2), experimental arm (n=5)). Three of 5 non-responders in the experimental arm had chemotherapy regimens adapted with an early initiation of taxane therapy or chemotherapy intensification, or early surgery and ended up as responders on final evaluation. Conclusion: The study demonstrates the feasibility of QUS-radiomics adapted guided NAC for patients with breast cancer. The ability of a QUS-based model in the early prediction of treatment response was prospectively validated in the current study. Clinical trial registration: clinicaltrials.gov, ID NCT04050228.

Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions.

Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns, such as scatterer concentrations and arrangements. In this study, we proposed a machine learning approach to integrate the strength of multimodality quantitative ultrasound envelope statistics imaging techniques and applied it to detecting microwave ablation induced thermal lesions in porcine liver ex vivo. The quantitative ultrasound parameters included were homodyned-K α which is a scatterer clustering parameter related to the effective scatterer number per resolution cell, Nakagami m which is a shape parameter of the envelope probability density function, and Shannon entropy which is a measure of signal uncertainty or complexity. Specifically, the homodyned-K log10(α), Nakagami-m, and horizontally normalized Shannon entropy parameters were combined as input features to train a support vector machine (SVM) model to classify thermal lesions with higher scatterer concentrations from normal tissues with lower scatterer concentrations. Through heterogeneous phantom simulations based on Field II, the proposed SVM model showed a classification accuracy above 0.90; the area accuracy and Dice score of higher-scatterer-concentration zone identification exceeded 83% and 0.86, respectively, with the Hausdorff distance <26. Microwave ablation experiments of porcine liver ex vivo at 60-80 W, 1-3 min showed that the SVM model achieved a classification accuracy of 0.85; compared with single log10(α),m, or hNSE parametric imaging, the SVM model achieved the highest area accuracy (89.1%) and Dice score (0.77) as well as the smallest Hausdorff distance (46.38) of coagulation zone identification. We concluded that the proposed multimodality quantitative ultrasound envelope statistics imaging based SVM approach can enhance the capability to characterize tissue scatterer distribution patterns and has the potential to detect the thermal lesions induced by microwave ablation.

Post-mortem Tissue Degassing Using Positive Pressure Is Superior to Negative Pressure.

OBJECTIVE: To compare the effectiveness of positive pressure (PP) and negative pressure (NP) for reducing gas inclusions in biological tissues in preparation for acoustic imaging. METHODS: Eighteen pieces of porcine liver in degassed saline were included in this study. For the PP group (n = 9 samples), a wristwatch waterproof tester was used to pressurize samples to 0.41 MPa (59 psi) for 10 min. For the NP group (n = 9 samples), a desiccator at -0.08 MPa (-12 psi) was used for 30 min. Backscatter coefficients (BSCs) were calculated over the central frequency range of the backscattered spectra and paired-samples t-tests were performed. RESULTS: Utilization of PP resulted in a decrease in BSC for all samples, indicating less gas post-PP (pre-PP -13.0 ± 4.3 dB [mean ± SD], post-PP -18.9 ± 5.0 dB, p = .001). Utilization of NP resulted in an increase in BSC for the majority of samples (pre-NP -14.6 ± 6.0 dB, post-NP -13.1 ± 5.3 dB, p = .177). CONCLUSION: Utilization of a simple PP chamber consistently resulted in a decrease in tissue gas, at lower pressures than previously reported. The vacuum method is ineffective, may result in a paradoxical increase in tissue gas, and may not be recommended for tissue degassing.

Sex- and Age-Specific Prevalence of Osteopenia and Osteoporosis: Sampling Survey.

BACKGROUND: Osteopenia and osteoporosis are posing a long-term influence on the aging population's health contributing to a higher risk of mortality, loss of autonomy, hospitalization, and huge health system costs and social burden. Therefore, more pertinent data are needed to demonstrate the current state of osteoporosis. OBJECTIVE: This sampling survey seeks to assess the trends in the prevalence of osteopenia and osteoporosis in a Chinese Han population. METHODS: A community-based cross-sectional study involving 16,377 participants used a multistage sampling method. Bone mineral density was measured using the quantitative ultrasonic densitometry. Student t test and Mann-Whitney U test were used to test the difference between normally and nonnormally distributed quantitative variables between male and female participants. A chi-square (χ2) test was used to compare categorized variables. Stratified analysis was conducted to describe the prevalence rates of osteoporosis (T score ≤-2.5) and osteopenia (T score -2.5 to -1.0) across age, sex, calcium intake, and menopause. A direct standardization method was used to calculate the age-standardized prevalence rates of osteoporosis and osteopenia. T-score was further categorized into quartiles (T1-T4) by age- and sex-specified groups. RESULTS: The prevalence rates of osteopenia and osteoporosis were 40.5% (6633/16,377) and 7.93% (1299/16,377), respectively, and the age-standardized prevalence rates were 27.32% (287,877,129.4/1,053,861,940) and 3.51% (36,974,582.3/1,053,861,940), respectively. There was an increase in osteopenia and osteoporosis prevalence from 21.47% (120/559) to 56.23% (754/1341) and 0.89% (5/559) to 17.23% (231/1341), respectively, as age increased from 18 years to 75 years old. The prevalence rates of osteopenia and osteoporosis were significantly higher in female participants (4238/9645, 43.94% and 1130/9645, 11.72%) than in male participants (2395/6732, 35.58% and 169/6732, 2.51%; P<.001), and in postmenopausal female participants (3638/7493, 48.55% and 1053/7493, 14.05%) than in premenopausal female participants (538/2026, 26.55% and 53/2026, 2.62%; P<.001). In addition, female participants with a history of calcium intake had a lower osteoporosis prevalence rate than female participants without any history of calcium intake in all age groups (P=.004). From low quartile to high quartile of T-score, the prevalence of diabetes mellitus (752/4037, 18.63%; 779/4029, 19.33%; 769/3894, 19.75%; and 869/3879, 22.4%) and dyslipidemia (2228/4036, 55.2%; 2304/4027, 57.21%; 2306/3891, 59.26%; and 2379/3878, 61.35%) were linearly increased (P<.001), while the prevalence of cancer (112/4037, 2.77%; 110/4029, 2.73%; 103/3894, 2.65%; and 77/3879, 1.99%) was decreased (P=.03). CONCLUSIONS: Our data imply that as people age, osteopenia and osteoporosis are more common in females than in males, particularly in postmenopausal females than in premenopausal females, and bone mineral density significantly affects the prevalence of chronic diseases. These findings offer information that can be applied to intervention programs meant to prevent or lessen the burden of osteoporosis in China.

Characterization of the in vivo transient responses of the femoral cartilage by means of quantitative ultrasound imaging techniques.

BACKGROUND: Quantitative ultrasound (QUS) techniques are new diagnostic tools able to identify changes in structural and material properties of the investigated tissue. For the first time, we evaluated the capability of QUS techniques in determining the in vivo transient changes in knee joint cartilage after a stressful task. METHODS: An ultrasound scanner collecting B-mode and radiofrequency data simultaneously was used to collect data from the femoral cartilage of the right knee in 15 participants. Cartilage thickness (CTK), ultrasound roughness index (URI), average magnitude ratio (AMR), and Nakagami parameters (NA) were evaluated before, immediately after and every 5 min up to 45 min a stressful task (30 min of running on a treadmill with a negative slope of 5%). RESULTS: CTK was affected by time (main effect: p < 0.001). Post hoc test showed significant differences with CTK at rest, which were observed up to 30 min after the run. AMR and NA were affected by time (p < 0.01 for both variables), while URI was unaffected by it. For AMR, post hoc test showed significant differences with rest values in the first 35 min of recovery, while NA was increased compared to rest values in all time points. CONCLUSION: Data suggest that a single running trial is not able to modify the integrity of the femoral cartilage, as reported by URI data. In vivo evaluation of QUS parameters of the femoral cartilage (NA, AMR, and URI) are able to characterize changes in cartilage properties over time.

Effect of denosumab on inflammation and bone health in active Charcot foot: A phase II randomised controlled trial.

AIMS: We aimed to investigate the effect of denosumab on pedal bone health and clinical resolution in active Charcot foot (CN). METHODS: This multicentre open-label phase 2 randomised controlled trial recruited adults with diabetes mellitus and active CN within 3 months of onset. Participants were randomised to standard care alone, or with denosumab 60 mg subcutaneously. Denosumab was administered at baseline and again at 6 months, unless foot temperature had normalised (i.e. <2 °C compared to contralateral foot). Co-primary outcomes were change in calcaneal Stiffness Index and foot temperature normalisation over 18 months. RESULTS: Twelve participants per group were analysed; mean age 58 ± 11 years, 83 % male and 92 % had type 2 diabetes. Active CN duration was median 8 (IQR 7-12) weeks. Ninety-two percent were Eichenholtz stage 1 and 96 % involved the midfoot. After 1-month, median decline in Stiffness Index was less in the denosumab verses standard care group (0.5 [IQR -1.0 to 3.9] vs -2.8 [-8.5 to -1.0], p = 0.008). At 18-months, 92 % of the denosumab group attained foot temperature normalisation versus 67 % of the standard care group (p = 0.13). CONCLUSIONS: Denosumab ameliorated the early decline in calcaneal Stiffness Index associated with active CN. However, no difference in normalisation of foot temperature was observed.

New point-of-care calcaneal ultrasound densitometer (Osteosys BeeTLE) compared to standard dual-energy X-ray absorptiometry (DXA).

Dual-energy X-ray absorptiometry (DXA) represents the gold standard for measuring bone mineral density (BMD). However, its size and bulkiness limit its use in mass screening. Portable and easily accessible instruments are more suitable for this purpose. We conducted a study to assess the repeatability, sensitivity, accuracy, and validation of a new ultrasound densitometer for the calcaneus (OsteoSys BeeTLe) compared to standard DXA. BMD (g/cm2) was measured at the femoral and lumbar spine levels using DXA (Discovery Acclaim (Hologic, Waltham, MA, USA) or Lunar Prodigy (GE Healthcare, Madison, WI, USA) devices). Bone Quality Index (BQI, a dimensionless measure of bone quality derived from measures of SOS [Speed Of Sound] and BUA [broadband ultrasound attenuation]) was measured with OsteoSys BeeTLe. The Bland-Altman test and simple linear regression were used to evaluate the association between values measured with the two instruments. Additionally, the ability of the T-score calculated with BeeTLe to identify patients with previous osteoporotic fractures was tested using ROC curves. A total of 201 patients (94.5% females) with a mean age of 62.1 ± 10.2 were included in the study. The BeeTLe instrument showed a coefficient of variation (CV, in 75 repeated measurements) of 1.21%, which was not statistically different from the CV of DXA (1.20%). We found a significant association between BQI and BMD at the femoral neck (r2 = 0.500, p < 0.0001), total femur (r2 = 0.545, p < 0.0001), and lumbar spine (r2 = 0.455, p < 0.0001). T-scores bias were 0.215 (SD 0.876), 0.021 (SD 0.889) and 0.523 (SD 0.092), for femoral neck, total hip and lumbar spine respectively. AUC for discriminating fracture and non-fractured patients were not significantly different with OsteoSys BeeTLe and standard DXA. In this preliminary study, BeeTLe, a new point-of-care ultrasound densitometer, demonstrated good repeatability and performance similar to DXA. Therefore, its use can be proposed in screening for osteoporosis.