Shear Wave Elastography in Breast Cancer: Unveiling Correlations With Histopathological Grades and Subtypes.

Objective This study explores the correlation between shear wave elastography (SWE) features and histopathological grades and subtypes in breast cancer, aiming to enhance diagnostic accuracy and personalized treatment strategies. Methods The study retrospectively analyzed 59 consecutive women with breast cancer who underwent breast ultrasound with SWE. SWE parameters and histopathologic information, including histological type and grade, were recorded. Qualitative and quantitative SWE findings were analyzed, and B-mode findings were evaluated. Sociodemographic and clinical factors and B-mode findings were assessed as predictors of elastography stiffness using logistic regression analysis. Results Of the 59 participants diagnosed with breast cancer, invasive ductal carcinoma of no special type (IDC-NST) was predominantly found in 50 (84.7%) cases, followed by invasive medullary carcinoma in 5 (8.5%) cases. The majority of participants belonged to the 50-59 age group, comprising 19 (32.2%) patients. Histopathological grading revealed grade II tumors in 27 (45.8%) cases and grade III tumors in 24 (40.7%) cases. Notably, grade III tumors exhibited higher tissue stiffness compared to grade II tumors. Out of 36 stiff lesions, 30 (83.3%%) were IDC-NST while 3 (8.3%) were invasive medullary carcinoma. A significant association was observed between higher histopathological grade (grade III) and increased tissue stiffness (p < 0.05). Furthermore, among participants with stiff lesions, 21 (58.3%) exhibited color defects while 4 (23.5%) cases with soft lesions also displayed color defects Conclusion The correlation between SWE findings and histopathological grades and subtypes underscores the potential of SWE as a valuable tool for predicting tumor aggressiveness and characterizing specific subtypes. SWE enhances diagnostic accuracy and complements traditional imaging modalities, holding promise for personalized treatment strategies.

Characteristics of regional lymph node metastasis in breast cancer and construction of a nomogram model based on ultrasonographic analysis: a retrospective study.

OBJECTIVE: The ultrasonographic characteristics of lymph node metastasis in breast cancer patients were retrospectively analyzed, and a predictive nomogram model was constructed to provide an imaging basis for better clinical evaluation. METHODS: B-mode ultrasound was used to retrospectively analyze the imaging characteristics of regional lymph nodes and tumors. Pathological examination confirmed the presence of lymph node metastasis in breast cancer patients. Univariable and multivariable logistic regression analyses were performed to analyze the risk factors for lymph node metastasis. LASSO regression analysis was performed to screen noninvasive indicators, and a nomogram prediction model was constructed for breast cancer patients with lymph node metastasis. RESULTS: A total of 187 breast cancer patients were enrolled, including 74 patients with lymph node metastasis in the positive group and 113 patients without lymph node metastasis in the negative group. Multivariate analysis revealed that pathological type (OR = 4.58, 95% CI: 1.44-14.6, p = 0.01), tumor diameter (OR = 1.37, 95% CI: 1.07-1.74, p = 0.012), spiculated margins (OR = 7.92, 95% CI: 3.03-20.67, p < 0.001), mixed echo of the breast tumor (OR = 37.09, 95% CI: 3.49-394.1, p = 0.003), and unclear lymphatic hilum structure (OR = 16.07, 95% CI: 2.41-107.02, p = 0.004) were independent risk factors for lymph node metastasis. A nomogram model was constructed for predicting breast cancer with lymph node metastasis, incorporating three significantly correlated indicators identified through LASSO regression analysis, namely, tumor spiculated margins, cortical thickness of lymph nodes, and unclear lymphatic hilum structure. The receiver operating characteristic (ROC) curve revealed that the area under the curve (AUC) was 0.717 (95% CI, 0.614-0.820) for the training set and 0.817 (95% CI, 0.738-0.890) for the validation set. The Hosmer-Lemeshow test results for the training set and the validation set were p = 0.9148 and p = 0.1648, respectively. The prediction nomogram has good diagnostic performance. CONCLUSIONS: B-mode ultrasound is helpful in the preoperative assessment of breast cancer patients with lymph node metastasis. The predictive nomogram model, which is based on logistic regression and LASSO regression analysis, is clinically safe, reliable, and highly practical.

Value of Two-Dimensional Shear-Wave Elastography in Differentiating Pancreatic Steatosis From Pancreatic Fibrosis.

OBJECTIVES: Pancreatic steatosis (PS) and pancreatic fibrosis (PF) both show increased pancreatic echogenicity on conventional B-mode ultrasound. In this study, we assessed the applicability of two-dimensional shear-wave elastography (2D-SWE) for their discrimination. METHODS: We gathered data from 120 adults with valid 2D-SWE measurements, comprising 40 healthy individuals, 55 individuals diagnosed with PS via non-enhanced computed tomography (CT), and 25 patients clinically diagnosed with non-calcific chronic pancreatitis. The participants were divided into three groups: normal pancreas (NP), PS, and PF. pancreatic echogenicity, pancreatic stiffness, and CT values between groups were analyzed. RESULTS: The 2D-SWE and CT values among the NP, PS, and PF groups all showed significant differences (P < .001). For the diagnosis of PS and PF using 2D-SWE, the area under the curve (AUC) values were 0.9100 and 0.9940, respectively, with optimal cut-off values of 5.7 kPa for predicting PS and 8.2 kPa for predicting PF. CONCLUSIONS: The 2D-SWE technique enabled rapid and quantitative assessment of the hardness of hyperechoic pancreas visualized on conventional B-mode ultrasound, which holds certain value in distinguishing PS from PF.

A model combining BI-RADS® descriptors from pre-treatment B-mode breast ultrasound with clinicopathological tumor features shows promise in the prediction of residual disease after neoadjuvant chemotherapy.

PURPOSE: To create a simple model using standard BI-RADS® descriptors from pre-treatment B-mode ultrasound (US) combined with clinicopathological tumor features, and to assess the potential of the model to predict the presence of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. METHOD: 245 female BC patients receiving NAC between January 2017 and December 2019 were included in this retrospective study. Two breast imaging fellows independently evaluated representative B-mode tumor images from baseline US. Additional clinicopathological tumor features were retrieved. The dataset was split into 170 training and 83 validation cases. Logistic regression was used in the training set to identify independent predictors of residual disease post NAC and to create a model, whose performance was evaluated by ROC curve analysis in the validation set. The reference standard was postoperative histology to determine the absence (pathological complete response, pCR) or presence (non-pCR) of residual invasive tumor in the breast or axillary lymph nodes. RESULTS: 100 patients (40.8%) achieved pCR. Logistic regression demonstrated that tumor size, microlobulated margin, spiculated margin, the presence of calcifications, the presence of edema, HER2-positive molecular subtype, and triple-negative molecular subtype were independent predictors of residual disease. A model using these parameters demonstrated an area under the ROC curve of 0.873 in the training and 0.720 in the validation set for the prediction of residual tumor post NAC. CONCLUSIONS: A simple model combining standard BI-RADS® descriptors from pre-treatment B-mode breast US with clinicopathological tumor features predicts the presence of residual disease after NAC.

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.

B-mode Ultrasound Related Combined Predictive Indicators for Benign Versus Malignant Subpleural Pulmonary Lesions.

OBJECTIVE: The purpose of this study was to analyze the independent risk factors of malignant subpleural pulmonary lesions (SPLs) on B-mode ultrasound (US) images, to construct the combined predictive indicators, and to prospectively verify their predictive efficacy. METHODS: A total of 336 patients with SPLs were included in the prospective study, of whom the single-center included patients between September 2019 and December 2019 were the development cohort (DC) (n = 219); Patients who were concurrently enrolled in three centers between January and February 2020 were the validation cohort (VC) (n = 117). The clinical features and B-mode US parameters were collected. Based on the DC, a combined predictive indicators model was developed using binary logistic regression. Then the discrimination was verified externally in the VC. The reference criteria were from the comprehensive diagnosis of clinical-radiological-pathological made by two senior respiratory physicians. RESULTS: The combined predictive indicators model was finally constructed by five parameters: age, borderline, angle between the lesion border and thoracic wall, posterior echo of the lesion and invasion of the pleura. The fitting degree of the model was good (χ2 = 9.198, p = 0.326). The area under ROC curve of the model was 0.872 (DC) and 0.808 (VC), yielding a higher net benefit than individual risk factors. CONCLUSION: The combined predictive indicators are useful in the assessment of malignant SPLs and are a useful adjunct diagnostic tool, especially in primary healthcare settings in developing countries.

Metrology of Supraspinatus Tendon Thickness in Swimmers with Tendinopathy Using Ultrasound Imaging: An Intra- and Inter-Rater Reliability Study.

Objective: This study aimed to assess the relative and absolute intra- and inter-rater reliability of supraspinatus tendon (SST) thickness. Materials: Thirty adolescent swimmers with supraspinatus (SS) tendinopathy (n = 15) and a control-matched group (n = 15) were evaluated. Tendon thickness was measured according to four different measure procedures, i.e., (1) at 15 mm, (2) at 10, 20, and 30 mm, (3) at 10, 15, and 20 mm, and (4) 5 and 10 mm lateral to the most hyperechogenic reference point of the biceps tendon. Each examiner took two US images for the test measurements with a 10 min rest period. After 30 min, the subjects underwent retest measurements that were also repeated 1 week later. Results: SST thickness was greater in swimmers with SS tendinopathy compared with the matched control group for each procedure and rater (p < 0.001). Intra- and inter-rater reliability was good to excellent (ICC2.3: 0.78-0.98 and 0.83-0.97, respectively) in both groups. The lowest intra- and inter-rater reliability was found in procedures no. 2 and 4 (ICC2.3: 0.78 and 0.83). However, procedure no. 3 was the most reliable with the lowest error rate (ICC2.3: 0.92-0.97; SEM: 0.05-0.10 mm; MDC: 0.14-0.28 mm). Conclusions: The study confirmed the diagnostic value of ultrasound in SS tendinopathy. A multiple-reference-point procedure including a simple methodology (10, 15, and 20 mm from biceps tendon), was defined as the most reliable, expressed by the highest intra- and inter-rater ICCs.

Influence of age, sex, bodyweight, and training on echocardiographic measurements in healthy mixed-breed donkeys.

The donkey has always been a notable working animal and its importance as a companion animal has been growing over the last few years. However, there are only a few studies about cardiology in this species. Therefore, this study aimed to evaluate the influence of age, sex, training, and bodyweight on cardiac dimension in mixed-breed donkeys. Forty-five clinically and para-clinically healthy mixed-breed donkeys were included, and B-mode and M-mode echocardiographic measurements were recorded. Multivariate linear regression analysis was performed to identify the effect of age, sex, bodyweight, and training on cardiac measurements. Most of the echocardiographic measurements showed a strong statistically significant correlation with bodyweight. Linear regression analysis between echocardiographic measurements and bodyweight was performed to obtain the values of the intercept and slope of the linear equation to calculate the echocardiographic measurements as a function of bodyweight. This is the first study reporting a strong linear correlation between echocardiographic measurements and bodyweight and reporting a correlation between training and echocardiographic parameters in donkeys, suggesting that this variable should be considered when assessing cardiac dimensions in these animals.

Simulating federated learning for steatosis detection using ultrasound images.

We aimed to implement four data partitioning strategies evaluated with four federated learning (FL) algorithms and investigate the impact of data distribution on FL model performance in detecting steatosis using B-mode US images. A private dataset (153 patients; 1530 images) and a public dataset (55 patient; 550 images) were included in this retrospective study. The datasets contained patients with metabolic dysfunction-associated fatty liver disease (MAFLD) with biopsy-proven steatosis grades and control individuals without steatosis. We employed four data partitioning strategies to simulate FL scenarios and we assessed four FL algorithms. We investigated the impact of class imbalance and the mismatch between the global and local data distributions on the learning outcome. Classification performance was assessed with area under the receiver operating characteristic curve (AUC) on a separate test set. AUCs were 0.93 (95% CI 0.92, 0.94) for source-based partitioning scenario with FedAvg, 0.90 (95% CI 0.89, 0.91) for a centralized model, and 0.83 (95% CI 0.81, 0.85) for a model trained in a single-center scenario. When data was perfectly balanced on the global level and each site had an identical data distribution, the model yielded an AUC of 0.90 (95% CI 0.88, 0.92). When each site contained data exclusively from one single class, irrespective of the global data distribution, the AUC fell in the range of 0.34-0.70. FL applied to B-mode US images provide performance comparable to a centralized model and higher than single-center scenario. Global data imbalance and local data heterogeneity influenced the learning outcome.

Evaluation of embryo-foetal biometry and its correlation with parturition date in Toy Poodle bitches.

Estimating the parturition date in dogs is challenging due to their reproductive peculiarities that. Ultrasonographic examination serves as a tool for studying embryo/foetal biometry and estimating the time of parturition by measuring foetal and extra-foetal structures. However, due to reproductive differences among various dog breeds, such estimates may have a non-significant pattern, representing inaccuracies in the estimated date of birth. This study aimed to monitor pregnant Toy Poodle bitches and establish relationships between ultrasonographically measured foetal and extra-foetal dimensions and the remaining time until parturition. Eighteen pregnant Toy Poodle bitches were subjected to weekly ultrasonographic evaluations and measurements of the inner chorionic cavity diameter, craniocaudal length (CCL), biparietal diameter (BPD), diameter of the deep portion of diencephalo-telencephalic vesicle (DPTV), abdominal diameter, thorax diameter (TXD), placental thickness and the renal diameter (REND). These parameters were retrospectively correlated with the date of parturition and linear regressions were established between gestational measurements and days before parturition (DBP). All analyses were conducted using the Statistical Package for Social Sciences (IBM® SPSS®) program at a 5% significance level. The foetal measurements that showed a high correlation (r) and reliability (R2) with DBP were BPD [(DBP = [15.538 × BPD] - 39.756), r = .97 and R2 = .93], TXD [(DBP = [8.933 × TXD] - 32.487), r = .94 and R2 = .89], DPTV [(DBP = [34.580 × DPTV] - 39.403), r = .93 and R2 = .86] and REND [(DBP = [13.735 × REND] - 28.937), r = .91 and R2 = .82]. This statistically validates the application of these specific formulas to estimate the parturition date in Toy Poodle bitches.

Assessment of Thermal and Mechanical Indices as Acoustic Output Parameters Used in Obstetric Ultrasound in Saudi Arabia.

BACKGROUND: Patient safety is paramount in ultrasound procedures, particularly in obstetric ultrasounds involving both the mother and fetus. The thermal and mechanical indices (TI and MI) serve as crucial indicators of the acoustic output during ultrasound. Clinicians and specialists must know these indices and ensure they are within safe ranges. This study aimed to assess the parameters of acoustic output power employed in obstetric ultrasound (thermal and mechanical index). METHODOLOGY: A cross-sectional observational study conducted at Maternity and Children's Hospital in Al-Madina Al-Munawwarah, the data was collected from obstetric scanning of 411 pregnant females using a data collection sheet including gravida and women's age, gestational age, scan mode, scan time, and thermal and mechanical index (TI and MI) values. RESULTS: The study found that there were significant differences in safety indices measurement between different modes; in Pulsed Doppler, mean Thermal Index Bone (TIb) had the highest value (1.60±0.40), and the Mechanical Index (MI) was the lowest (0.68±0.33). There were insignificant differences in safety indices values in different modes in different trimesters. The thermal indices of soft tissue and bony structure (TIs and TIb) of brightness mode (B-mode) were constant in all trimesters, but the MI in the first trimester was lower than in the other trimesters. CONCLUSION: This study found significant differences in TIs, TIb, and MI in different modes of obstetric ultrasound. Pulsed Doppler ultrasonography had the highest TIb value and a lower MI value. The ultrasound acoustic exposure output parameters were within the standard's recommended limit.

Exploring the Relationship Between Serum Phosphate Levels and Carotid Intima-Media Thickness in Chronic Kidney Disease Patients: A Correlational Analysis.

Background Compelling observational data suggest that heightened levels of fasting blood phosphate are linked to a higher likelihood of cardiovascular disease, spanning across both the general populace and individuals grappling with chronic kidney disease (CKD). This study aimed to explore the possible correlation between carotid intima-media thickness (CIMT) and blood phosphate levels among those afflicted with chronic renal dysfunction. Objective The primary goal of this study is to determine the potential association between blood phosphate levels and CIMT in patients with CKD. Methodology In the department of nephrology, prospective research was conducted among patients who had a history of CKD. A total of 30 patients were included, with 20 males and 10 females. Every case had a thorough physical examination and history. Every patient underwent a laboratory evaluation, which included measurements of the CIMT and renal function testing. At a distance of 1 cm from the carotid bulb, the CIMT was measured using B-mode ultrasonography. After compilation, the data were examined. Results The majority of the patients, according to this study, were male and over 50 years old. The Stage II patients in the study had a higher mean systolic blood pressure; however, the difference was not statistically significant. Patients with Stage V (D) disease exhibited higher diastolic blood pressure, but not statistically significant. An increase in the mean serum creatinine level that was statistically significant was linked to Stage V (D) renal disease. A higher mean blood urea was linked to Stage V (D) sickness; however, this relationship was not statistically significant. There was no statistical difference in the mean serum calcium levels between the different stages of renal disease. Higher mean blood phosphate levels were linked to Stage III renal disease, but not in a statistically meaningful way. Although it was higher in Stage IV kidney disease, the mean CIMT was not statistically significant between the stages of renal illness. Conclusions Although a positive correlation was shown, a direct relationship between serum phosphate levels was not established by this investigation. The severity of renal disease has been demonstrated to correlate with elevated serum phosphate levels.

A triple kidney: Coexistence of normal left kidney and mal-rotated horseshoe anomaly: A rare case report.

The occurrence of triple kidneys, involving a normal kidney and a malrotation horseshoe kidney, is an extremely infrequent condition. This case report demonstrates a triple, mal-rotated horseshoe kidneys coexist with an upper junction stone, alongside a normal left kidney showing normal Doppler vascularity, as observed in an ultrasound examination for 18-year-old male complaints of diffuse periumbilical pain and burning micturition. Laboratory investigation revealed normal creatinine level, and presence of urinary tract infection. Management option for this case are antibiotic therapy and surgical intervention for horseshoe kidney stone. Regular monitoring of kidney function, other radiographic imaging studies, and follow-up to assess the efficacy of the treatment, and detect any further complications are essential.

Application and visualization study of an intelligence-assisted classification model for common eye diseases using B-mode ultrasound images.

Aim: Conventional approaches to diagnosing common eye diseases using B-mode ultrasonography are labor-intensive and time-consuming, must requiring expert intervention for accuracy. This study aims to address these challenges by proposing an intelligence-assisted analysis five-classification model for diagnosing common eye diseases using B-mode ultrasound images. Methods: This research utilizes 2064 B-mode ultrasound images of the eye to train a novel model integrating artificial intelligence technology. Results: The ConvNeXt-L model achieved outstanding performance with an accuracy rate of 84.3% and a Kappa value of 80.3%. Across five classifications (no obvious abnormality, vitreous opacity, posterior vitreous detachment, retinal detachment, and choroidal detachment), the model demonstrated sensitivity values of 93.2%, 67.6%, 86.1%, 89.4%, and 81.4%, respectively, and specificity values ranging from 94.6% to 98.1%. F1 scores ranged from 71% to 92%, while AUC values ranged from 89.7% to 97.8%. Conclusion: Among various models compared, the ConvNeXt-L model exhibited superior performance. It effectively categorizes and visualizes pathological changes, providing essential assisted information for ophthalmologists and enhancing diagnostic accuracy and efficiency.

Automated analysis of pectoralis major thickness in pec-fly exercises: evolving from manual measurement to deep learning techniques.

This study addresses a limitation of prior research on pectoralis major (PMaj) thickness changes during the pectoralis fly exercise using a wearable ultrasound imaging setup. Although previous studies used manual measurement and subjective evaluation, it is important to acknowledge the subsequent limitations of automating widespread applications. We then employed a deep learning model for image segmentation and automated measurement to solve the problem and study the additional quantitative supplementary information that could be provided. Our results revealed increased PMaj thickness changes in the coronal plane within the probe detection region when real-time ultrasound imaging (RUSI) visual biofeedback was incorporated, regardless of load intensity (50% or 80% of one-repetition maximum). Additionally, participants showed uniform thickness changes in the PMaj in response to enhanced RUSI biofeedback. Notably, the differences in PMaj thickness changes between load intensities were reduced by RUSI biofeedback, suggesting altered muscle activation strategies. We identified the optimal measurement location for the maximal PMaj thickness close to the rib end and emphasized the lightweight applicability of our model for fitness training and muscle assessment. Further studies can refine load intensities, investigate diverse parameters, and employ different network models to enhance accuracy. This study contributes to our understanding of the effects of muscle physiology and exercise training.

Optical coherence tomography Angio-B mode for early detection of myopic choroidal neovascularization and treatment with Bevacizumab.

Purpose: The purpose of this case report is to outline the management of a 41-year-old female with pathological myopia and type II choroidal neovascularization (CNV) diagnosed by optical coherence tomography angiography (OCT-A) angio-B mode. Observations: The early detection of CNV with OCT-A angio-B mode and treatment with intra-vitreous injections of Bevacizumab contributed to the amelioration of her vision to 20/20, a better visual acuity than she had prior to treatment. Conclusions and importance: This case report suggests that an OCT-A scan may reveal the initial formation of abnormal vasculature before pathological changes are evident in structural OCT, allowing for prompt treatment and resolution in patients with myopic CNV.

iATT liver fat quantification for steatosis grading by referring to MRI proton density fat fraction: a multicenter study.

BACKGROUND: Several preliminary reports have suggested the utility of ultrasound attenuation coefficient measurements based on B-mode ultrasound, such as iATT, for diagnosing steatotic liver disease. Nonetheless, evidence supporting such utility is lacking. This prospective study aimed to investigate whether iATT is highly concordant with magnetic resonance imaging (MRI)-based proton density fat fraction (MRI-PDFF) and could well distinguish between steatosis grades. METHODS: A cohort of 846 individuals underwent both iATT and MRI-PDFF assessments. Steatosis grade was defined as grade 0 with MRI-PDFF < 5.2%, grade 1 with 5.2% MRI-PDFF < 11.3%, grade 2 with 11.3% MRI-PDFF < 17.1%, and grade 3 with MRI-PDFF of 17.1%. The reproducibility of iATT and MRI-PDFF was evaluated using the Bland-Altman analysis and intraclass correlation coefficients, whereas the diagnostic performance of each steatosis grade was examined using receiver operating characteristic analysis. RESULTS: The Bland-Altman analysis indicated excellent reproducibility with minimal fixed bias between iATT and MRI-PDFF. The area under the curve for distinguishing steatosis grades 1, 2, and 3 were 0.887, 0.882, and 0.867, respectively. A skin-to-capsula distance of ≥ 25 mm was identified as the only significant factor causing the discrepancy. No interaction between MRI-logPDFF and MRE-LSM on iATT values was observed. CONCLUSIONS: Compared to MRI-PDFF, iATT showed excellent diagnostic accuracy in grading steatosis. iATT could be used as a diagnostic tool instead of MRI in clinical practice and trials. Trial registration This study was registered in the UMIN Clinical Trials Registry (UMIN000047411).

Sonographic methods to predict type 2 diabetes patients with sarcopenia: B mode ultrasound and shear wave elastography.

BACKGROUND: Type 2 diabetes accelerates the loss of muscle mass and strength. Sarcopenia is also one of the chronic complications of diabetes. OBJECTIVE: To investigate the clinical value of B mode ultrasound (BMUS) and shear wave elastography (SWE) for predicting type 2 diabetic sarcopenia. METHODS: We recorded Skeletal Muscle Mass Index (ASMI), grip strength, muscle thickness (MT), pinna angle (PA), fascicle length (FL), and the difference of Young's modulus in the relaxed states and tense states (ΔSWE). The correlations between clinical indicators and ultrasound characteristics were compared. A diagnostic model of sarcopenia was developed to assess the independent correlates and evaluate the diagnostic efficacy of sarcopenia. RESULTS: ASMI was significantly and positively correlated with MT and ΔSWE (r = 0.826, 0.765, P < 0.01), and grip strength was significantly and positively correlated with MT and ΔSWE (r = 0.797, 0.818, P < 0.01). MT was the most significant predictor of sarcopenia (OR = 4.576, P < 0.001), and the cut-off value of MT was 11.4 mm (AUC: 0.952). CONCLUSION: BMUS and SWE can quantitatively assess muscle mass and strength, and are effective methods to predict the occurrence of sarcopenia in elderly patients with type 2 diabetes.

Normalized Spatial Autocorrelation in Ultrasound B-Mode Imaging for Point-Scatterer Detection.

OBJECTIVE: Point-scatterer detection plays a key role in medical ultrasound B-mode imaging. Speckle noise and insufficient spatial resolution are important factors affecting point-scatterer detection. To address this issue, normalized spatial autocorrelation in ultrasound B-mode imaging (NSACB) is proposed. METHODS: First, the acquired data are pre-processed by adding Gaussian white noise (GWN) with a certain signal-to-Gaussian white noise ratio (SGWNR). Next, normalized spatial autocorrelation is applied to the pre-processed data, and the data are divided into several new signals with different spatial lags. Then, the new signals are performed unsigned delay multiply and sum. Finally, the NSACB beamformed data are bandpass filtered by extracting the frequency component around twice the center frequency. Simulated and in vitro experiments were designed for validation. RESULTS: Simulations revealed that the lateral resolution of NSACB measured by the -6-dB mainlobe width can reach as high as 11.11% of delay and sum (DAS), 25.01% of filtered delay multiply and sum (F-DMAS) and 50% of LAG-FDMAS-SCF. The sidelobe level of the NSACB can be reduced at most by 28 dB. Experimental results of simple and complex scatterer phantoms indicate the image resolution of the proposed NSACB can even reach up to 18.76% of DAS, 27.28% of F-DMAS and 14.29% of LAG-FDMAS-SCF. Compared with these methods, the proposed NSACB can reduce the sidelobe level at least by 18 dB. CONCLUSION: Although the proposed method causes loss of the ability to observe hypo-echoic structures, these results suggest future work to determine the ability to detect breast microcalcifications, kidney stones, biopsy needle tracking and other scenarios requiring scatterer detection.

B-mode ultrasound to elastography synthesis using multiscale learning.

Elastography is a promising diagnostic tool that measures the hardness of tissues, and it has been used in clinics for detecting lesion progress, such as benign and malignant tumors. However, due to the high cost of examination and limited availability of elastic ultrasound devices, elastography is not widely used in primary medical facilities in rural areas. To address this issue, a deep learning approach called the multiscale elastic image synthesis network (MEIS-Net) was proposed, which utilized the multiscale learning to synthesize elastic images from ultrasound data instead of traditional ultrasound elastography in virtue of elastic deformation. The method integrates multi-scale features of the prostate in an innovative way and enhances the elastic synthesis effect through a fusion module. The module obtains B-mode ultrasound and elastography feature maps, which are used to generate local and global elastic ultrasound images through their correspondence. Finally, the two-channel images are synthesized into output elastic images. To evaluate the approach, quantitative assessments and diagnostic tests were conducted, comparing the results of MEIS-Net with several deep learning-based methods. The experiments showed that MEIS-Net was effective in synthesizing elastic images from B-mode ultrasound data acquired from two different devices, with a structural similarity index of 0.74 ± 0.04. This outperformed other methods such as Pix2Pix (0.69 ± 0.09), CycleGAN (0.11 ± 0.27), and StarGANv2 (0.02 ± 0.01). Furthermore, the diagnostic tests demonstrated that the classification performance of the synthetic elastic image was comparable to that of real elastic images, with only a 3 % decrease in the area under the curve (AUC), indicating the clinical effectiveness of the proposed method.