Ultrasound Strain Elastography Research Articles

Teacher-student guided knowledge distillation for unsupervised convolutional neural network-based speckle tracking in ultrasound strain elastography

Teacher-student guided knowledge distillation for unsupervised convolutional neural network-based speckle tracking in ultrasound strain elastography

Combined gray scale ultrasonography and doppler diagnostic tools with strain elastography in assessment of inflammatory bowel disease in pediatrics patients.

Intestinal changes in inflammatory bowel disease (IBD) are frequently observed on ultrasound. Invasive diagnostic procedures are often employed to differentiate between the main types of IBD and detect complications. Ultrasound Strain Elastography (SE) is a promising non-invasive technique for detecting intestinal changes and assessing inflammatory activity in pediatric IBD. This research aims to evaluate the diagnostic performance of conventional ultrasound, color Doppler, and SE in assessing inflammatory bowel disease in pediatric patients, both separately and in combination as additional tools. Forty patients (18 females and 22 males) initially diagnosed with IBD through clinical and endoscopic biopsy, along with 20 healthy controls, underwent conventional ultrasound, color Doppler, SE, and laboratory evaluations, including CBC, ESR, CRP, Fecal calprotectin, and assessment of IBD activity using PIBDAI. Conventional ultrasound, color Doppler, and SE significantly contributed to detecting disease activity and intestinal changes in IBD (p < 0.001; 95% CI 0.79-1.100), demonstrating better sensitivity in combination compared to each method individually. The combined approach showed 100% sensitivity, 84% specificity, 78.6% precision (Positive Predictive Value), 100% Negative Predictive Value, and an overall accuracy of 92%. The addition of Color Doppler and SE parameters to grayscale ultrasound provides diagnostic value comparable to endoscopy, histopathology, and laboratory markers in detecting inflammatory activity and intestinal changes in IBD. This combined approach can help avoid unnecessary invasive techniques for follow-up.

A Model Combining Conventional Ultrasound Characteristics, Strain Elastography and Clinicopathological Features to Predict Ki-67 Expression in Small Breast Cancer.

To establish a predictive model incorporating conventional ultrasound, strain elastography and clinicopathological features for Ki-67 expression in small breast cancer (SBC) which defined as maximum diameter less than2 cm. In this retrospective study, 165 SBC patients from our hospital were allocated to a high Ki-67 group (n = 104) and a low Ki-67 group (n = 61). Multivariate regression analysis was performed to identify independent indicators for developing predictive models. The area under the receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. The corresponding sensitivities and specificities of different models at the cutoff value were compared. Conventional ultrasound parameters (spiculated margin, absence of posterior shadowing and Adler grade 2-3), strain elastic scores and clinicopathological information (HER2 positive) were significantly correlated with high expression of Ki-67 in SBC (all p < .05). Model 2, which incorporated conventional ultrasound features and strain elastic scores, yielded good diagnostic performance (AUC = 0.774) with better sensitivity than model 1, which only incorporated ultrasound characteristics (78.85%vs. 55.77%, p = .000), with specificities of 77.05% and 62.30% (p = .035), respectively. Model 3, which incorporated conventional ultrasound, strain elastography and clinicopathological features, yielded better performance (AUC = 0.853) than model 1 (AUC = 0.694) and model 2 (AUC = 0.774), and the specificity was higher than model 1 (86.89% vs. 77.05%, p = .001). The predictive model combining conventional ultrasound, strain elastic scores and clinicopathological features could improve the predictive performance of Ki-67 expression in SBC.

Evaluation of testicular stiffness in boys with unilateral cryptorchidism after orchiopexy by ultrasound strain elastography.

We assessed the stiffness of unilateral undescended testes after orchiopexy, examining its value in tracking histopathological changes and fertility potential during postoperative follow-up. Additionally, we explored the optimal timing for surgery based on testicular stiffness. Thirty-six boys who had been diagnosed with unilateral undescended testis and treated with orchiopexy were included in the study. Testicular stiffness was evaluated several times over respective follow-up periods by ultrasound strain elastography after orchiopexy. The strain ratios were measured as the ratios of the elasticities of the descended testis to those of the operated testes. The patients were divided into two groups based on the age at which they underwent orchiopexy:under < 2 years (Group A) and ≥ 2 years (Group B). The mean strain ratios were 0.90 ± 0.32 and 0.92 ± 0.20 in Groups A and B, respectively. In Group A, the strain ratio was constant regardless of postoperative months (r = 0.01, p = 0.99); however, in Group B, it tended to increase with postoperative months (r = 0.42, p = 0.07). Evaluation of testicular stiffness may be useful for the estimation of histopathological changes and fertility potential in boys with unilateral undescended testes at follow-up appointments after orchiopexy. Our data indicate that performing orchiopexy as early as possible may be recommended to avoid testicular damage.

Comparative analysis of mammary lump histology and elasto-graphy results at a tertiary hospital

In the majority of India's metropolitan populations, mammary carcinoma has become the commonest type of carcinoma. A non-invasive imaging method called mammary sono-elasto-graphy can reveal information about mammary lesions. Aims &amp; objectives: In the current research, we examined the diagnostic efficacy of elasto-graphy and histopathological findings of mammary lumps. Material and Methods: The current investigation involved Female patients had solid mammary lesions less than 3 cm in size that were visible on sonography. Classified as BI RADS 3 and 4 lesions, these lesions. Results: 252 female patients had U.S.G. elastography, followed by biopsy or surgery, and histopathology reports were available during the research period. Histopathologically, 104 (41.72%) samples were benign, and the remaining 148 (58.73%) were malignant. Age, B.I.R.A.D.S., Elastography Score, and Strain Ratio were all statistically higher in malignant cases than in benign patients (p 0.001). According to Histo-pathological analysis, fibroadenoma (77.03%) accounted for the majority of benign lesions, followed by Abscess (5.41%), sclerosing adenosis (1.35%), benign fibroepithelial lesion (6.76%), and fibrocystic disease (9.46%). Conversely, poorly differentiated invasive carcinoma (5.77%), invasive ductal carcinoma (67.31%), and invasive mucinous carcinoma (13.46%), IL.C. (5.77%), medullary carcinoma (1.92%), papillary carcinoma (1.92%), and phylloid (1.92%) made up the bulk of malignant cases, Excellent results were noticed with the combination of Ultrasound Score + Elastography Score + Strain Ratio, with scores of 96.00%, 96.05%, 96.03%, 94.12%, and 97.33%, respectively, for susceptibility, accuracy, diagnostic accuracy, and N.P.V. and PPV. Conclusion: The ability to distinguish between benign and malignant mammary masses using ultra-sound elasto-graphy, strain elasto-graphy, and ultra-sound score has good susceptibility, accuracy, and diagnostic accuracy.

Alternating direction method of multipliers for displacement estimation in ultrasound strain elastography.

Ultrasound strain imaging, which delineates mechanical properties to detect tissue abnormalities, involves estimating the time delay between two radio-frequency (RF) frames collected before and after tissue deformation. The existing regularized optimization-based time-delay estimation (TDE) techniques suffer from at least one of the following drawbacks: (1) The regularizer is not aligned with the tissue deformation physics due to taking only the first-order displacement derivative into account; (2) The -norm of the displacement derivatives, which oversmooths the estimated time-delay, is utilized as the regularizer; (3) The modulus function defined mathematically should be approximated by a smooth function to facilitate the optimization of -norm. Our purpose is to develop a novel TDE technique that resolves the aforementioned shortcomings of the existing algorithms. Herein, we propose employing the alternating direction method of multipliers (ADMM) for optimizing a novel cost function consisting of -norm data fidelity term and -norm first- and second-order spatial continuity terms. ADMM empowers the proposed algorithm to use different techniques for optimizing different parts of the cost function and obtain high-contrast strain images with smooth backgrounds and sharp boundaries. We name our technique ADMM for totaL variaTion RegUlarIzation in ultrasound STrain imaging (ALTRUIST). ALTRUIST's efficacy is quantified using absolute error (AE), Structural SIMilarity (SSIM), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and strain ratio (SR) with respect to GLUE, OVERWIND, and -SOUL, three recently published energy-based techniques, and UMEN-Net, a state-of-the-art deep learning-based algorithm. Analysis of variance (ANOVA)-led multiple comparison tests and paired -tests at overall significance level were conducted to assess the statistical significance of our findings. The Bonferroni correction was taken into account in all statistical tests. Two simulated layer phantoms, three simulated resolution phantoms, one hard-inclusion simulated phantom, one multi-inclusion simulated phantom, one experimental breast phantom, and three in vivo liver cancer datasets have been used for validation experiments. We have published the ALTRUIST code at http://code.sonography.ai. ALTRUIST substantially outperforms the four state-of-the-art benchmarks in all validation experiments, both qualitatively and quantitatively. ALTRUIST yields up to , , and SNR improvements and , , and CNR improvements over -SOUL, its closest competitor, for simulated, phantom, and in vivo liver cancer datasets, respectively, where the asterisk (*) indicates statistical significance. In addition, ANOVA-led multiple comparison tests and paired -tests indicate that ALTRUIST generally achieves statistically significant improvements over GLUE, UMEN-Net, OVERWIND, and -SOUL in terms of AE, SSIM map, SNR, andCNR. A novel ultrasonic displacement tracking algorithm named ALTRUIST has been developed. The principal novelty of ALTRUIST is incorporating ADMM for optimizing an -norm regularization-based cost function. ALTRUIST exhibits promising performance in simulation, phantom, and in vivoexperiments.

A clinical-radiomics nomogram based on multimodal ultrasound for predicting the malignancy risk in solid hypoechoic breast lesions.

In routine clinical examinations, solid hypoechoic breast lesions are frequently encountered, but accurately distinguishing them poses a challenge. This study proposed a clinical-radiomics nomogram based on multimodal ultrasound that enhances the diagnostic accuracy for solid hypoechoic breast lesions. This retrospective study analyzed ultrasound strain elastography (SE) and automated breast volume scanner images (ABVS) of 423 solid hypoechoic breast lesions from 423 female patients in our hospital between August 2019 and May 2022. They were assigned to the training (n=296) and validation (n=127) groups in a 7:3 ratio by generating random numbers. Radiomics features were extracted and screened from ABVS and SE images, followed by the calculation of the radiomics score (Radscore) based on these features. Subsequently, a nomogram was constructed through multivariate logistic regression to assess the malignancy risk in breast lesions by combining Radscore with Breast Imaging Reporting and Data System (BI-RADS) scores and clinical risk factors associated with breast malignant lesions. The diagnostic performance, calibration performance, and clinical usefulness of the nomogram were assessed by the area under the curve (AUC) of the receiver operating characteristic curve, the calibration curve, and the decision analysis curve, respectively. The diagnostic performance of the nomogram is significantly superior to that of both the clinical diagnostic model (BI-RADS model) and the multimodal radiomics model (SE+ABVS radiomics model) in training (AUC: 0.972 vs 0.930 vs 0.941) and validation group (AUC:0.964 vs 0.916 vs 0.933). In addition, the nomogram also exhibited a favorable goodness-of-fit and could lead to greater net benefits for patients. The nomogram enables a more effective assessment of the malignancy risk of solid hypoechoic breast lesions; therefore, it can serve as a new and efficient diagnostic tool for clinical diagnosis.

Elasticity of the Forearm Flexor-Pronator Muscles as a Risk Factor for Medial Elbow Injuries in Young Baseball Players: A Prospective Cohort Study of 314 Players

Background: Young baseball players with medial elbow injuries are known to have high forearm flexor-pronator muscle elasticity; however, the causal relationship between forearm muscle elasticity and the occurrence of medial elbow injuries remains unclear. Purpose/Hypothesis: The purpose of this study was to determine whether the forearm flexor-pronator muscle elasticity is a risk factor for medial elbow injury in young baseball players. It was hypothesized that high flexor carpi ulnaris (FCU) elasticity would be a risk factor for medial elbow injuries. Study Design: Cohort study; Level of evidence, 2. Methods: Young baseball players (aged 9-12 years) with no history of elbow injuries underwent examination during which the strain ratios (SRs) of the pronator teres, flexor digitorum superficialis, and FCU muscles were measured using ultrasound strain elastography as an index of elasticity. Additionally, the participants completed a questionnaire assessing age, height, weight, months of experience as a baseball player, position in baseball, number of training days per week, number of throws per day, and elbow pain during throwing; then the range of motion of the shoulder and hip internal/external rotation were measured. One year after the baseline measurements, the occurrence of new medial elbow injuries was evaluated. Multivariate logistic regression analysis was subsequently conducted to determine risk factors for medial elbow injuries. Cutoff points for significant SR values obtained from the multivariate logistic regression analysis were calculated using the receiver operating characteristic curve. Results: Of the 314 players, 76 (24.2%) were diagnosed with medial elbow injury. Multivariate logistic regression analysis showed that a 0.1 increase in the SR of the FCU muscle (odds ratio [OR], 1.211; 95% CI, 1.116-1.314) and number of throws per day (OR, 1.012; 95% CI, 1.001-1.022) were significantly associated with medial elbow injuries. Receiver operating characteristic curve analyses revealed that the optimal cutoff for the SR of the FCU muscle was 0.920 (area under the curve, 0.694; sensitivity, 75.0%; specificity, 56.7%). Conclusion: Increased FCU elasticity is a risk factor for medial elbow injury. Evaluation of the FCU elasticity may be useful in identifying young baseball players at high risk of medial elbow injuries and may facilitate prevention of medial elbow injury. As shown by the results of multivariate logistic regression analysis, FCU elasticity itself may be useful in identifying young baseball players at high risk of elbow injuries. However, we believe that other factors, such as the number of pitches per day, need to be considered to improve its accuracy.

Patellar Tendon Elasticity and Temperature Following after a 448 Kilohertz Radiofrequency Intervention on Active Healthy Subjects: An Open Controlled Clinical Trial.

The purpose of this study was to analyze the changes in the elasticity and temperature of the patellar tendon produced by the application of a radiofrequency at 448 kHz (CRMR) just after and 7 days after the intervention. An open controlled clinical trial was used with participants being recruited from a private clinic. The experimental group (n = 22) received a 448 kHz CRMR treatment while the control group (n = 22) did not receive any type of intervention. Quantitative ultrasound strain elastography (SEL) and thermography were used to collect data from 4 different areas of the patellar tendon. These areas were measured at the start (T0), just after (T1), and seven days after (T2) the intervention. There were thermal changes immediately after the intervention (p < 0.001). In addition, when the measurements were collected just after the intervention and seven days after they were analyzed, significant changes (p < 0.001) in temperature were observed in the tendons of both groups. Finally, a low but significant association (r = 0.434, p < 0.04) was observed between the elastic properties of the tendon at its insertion in the patella and thermal changes just after the 448 kHz intervention.

Predicting BRAFV600E mutations in papillary thyroid carcinoma using six machine learning algorithms based on ultrasound elastography

The most common BRAF mutation is thymine (T) to adenine (A) missense mutation in nucleotide 1796 (T1796A, V600E). The BRAFV600E gene encodes a protein-dependent kinase (PDK), which is a key component of the mitogen-activated protein kinase pathway and essential for controlling cell proliferation, differentiation, and death. The BRAFV600E mutation causes PDK to be activated improperly and continuously, resulting in abnormal proliferation and differentiation in PTC. Based on elastography ultrasound (US) radiomic features, this study seeks to create and validate six distinct machine learning algorithms to predict BRAFV6OOE mutation in PTC patients prior to surgery. This study employed routine US strain elastography image data from 138 PTC patients. The patients were separated into two groups: those who did not have the BRAFV600E mutation (n = 75) and those who did have the mutation (n = 63). The patients were randomly assigned to one of two data sets: training (70%), or validation (30%). From strain elastography US images, a total of 479 radiomic features were retrieved. Pearson's Correlation Coefficient (PCC) and Recursive Feature Elimination (RFE) with stratified tenfold cross-validation were used to decrease the features. Based on selected radiomic features, six machine learning algorithms including support vector machine with the linear kernel (SVM_L), support vector machine with radial basis function kernel (SVM_RBF), logistic regression (LR), Naïve Bayes (NB), K-nearest neighbors (KNN), and linear discriminant analysis (LDA) were compared to predict the possibility of BRAFV600E. The accuracy (ACC), the area under the curve (AUC), sensitivity (SEN), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV), decision curve analysis (DCA), and calibration curves of the machine learning algorithms were used to evaluate their performance. ① The machine learning algorithms' diagnostic performance depended on 27 radiomic features. ② AUCs for NB, KNN, LDA, LR, SVM_L, and SVM_RBF were 0.80 (95% confidence interval [CI]: 0.65–0.91), 0.87 (95% CI 0.73–0.95), 0.91(95% CI 0.79–0.98), 0.92 (95% CI 0.80–0.98), 0.93 (95% CI 0.80–0.98), and 0.98 (95% CI 0.88–1.00), respectively. ③ There was a significant difference in echogenicity,vertical and horizontal diameter ratios, and elasticity between PTC patients with BRAFV600E and PTC patients without BRAFV600E. Machine learning algorithms based on US elastography radiomic features are capable of predicting the likelihood of BRAFV600E in PTC patients, which can assist physicians in identifying the risk of BRAFV600E in PTC patients. Among the six machine learning algorithms, the support vector machine with radial basis function (SVM_RBF) achieved the best ACC (0.93), AUC (0.98), SEN (0.95), SPEC (0.90), PPV (0.91), and NPV (0.95).

Canine prostatic serum esterase and strain and 2D-shear wave sonoelastography for evaluation of normal prostate in dogs: Preliminary results.

Canine prostatic serum esterase (CPSE) is considered a useful tool to identify prostate disorders in dogs, with increasing interest in ultrasound (US)-based sonoelastography to non-invasively detect prostate disorders. Since no report is available about a possible correlation between these diagnostic tools, we aimed to investigate a possible correlation between strain elastography (SE) and 2D-shear wave elastography (SWE) and CPSE. Twenty-one dogs were included and, on each animal, CPSE was evaluated followed by a complete US examination and SE and 2D-SWE application. Healthy dogs were identified based on the CPSE results. All the dogs included were characterized by normal CPSE values (<52.3 ng/mL) and normal US prostate appearance. The prostate was characterized by intermediate stiffness with SE (pattern III - 84.7% for the left lobe and 79.27% for the right lobe) and softer than the abdominal wall (SR 0.6 for the left lobe and 0.56 for the right lobe), with low values for both m/s and kilopascals (kPa) for 2D-SWE, pointing that the healthy tissue is not hard. 2D-SWE results were, respectively, 13.51 ± 5.55 kPa and 2.31 ± 0.42 m/s for the left lobe and 18.05 ± 6.47 kPa and 2.39 ± 0.43 m/s for the right lobe. The significant difference between the right and left measurements expressed with kPa, not evidenced with m/s, can be considered indicative of m/s as the most reliable measurement to be considered regarding the prostate parenchyma. Even though no linear correlation was detected between CPSE and elastography values, these preliminary results evidence that the healthy prostates were characterized by a similar elastographic pattern, thus pointing that these techniques can be potentially useful to be applied in case of prostatic disorders to improve the accuracy of the final diagnosis in a non-invasive way.

Three-Dimensional Freehand Ultrasound Strain Elastography Based on the Assessment of Endogenous Motion: Phantom Study

Three-Dimensional Freehand Ultrasound Strain Elastography Based on the Assessment of Endogenous Motion: Phantom Study

Ultrasound Strain Elastography Reliability in the Assessment of the Plantar Fascia and Its Relationship with the Plantar Thickness in Healthy Adults: An Intra and Interobserver Reliability Study in Novice Evaluators.

This study was aimed at verifying both the intraobserver and interobserver reliability of measuring plantar fascia stiffness for a given image in healthy active adults. This study is reported following the Guidelines of Reporting Reliability and Agreement Studies. A total of 20 plantar fascia from healthy volunteers were analyzed. The thickness of the plantar fascia was measured vertically from the anterior edge of the inferior calcaneal border to the inferior border of the plantar fascia and the ultrasound elastography measurement was taken at the calcaneal insertion of the plantar fascia with the region of interest one centimeter away from the insertion. The ultrasound strain elastography measurements: the right intraobserver 1 showed an ICC value of 0.9 and the left intraobserver 1 showed an ICC value of 0.78, while the right intraobserver 2 showed an ICC value of 0.91 and the left intraobserver 2 showed an ICC value of 0.83. Interobserver measurements showed excellent reliability with a right ICC value of 0.8 and a left ICC value of 0.9 for the plantar fascia thickness measurements. The results of this study showed a strong correlation between left and right plantar fascia thickness. The intraobserver reliability was excellent for both plantar fascia ultrasound strain elastography and thickness measurements, with interobserver measurements showing excellent reliability.

Comparative evaluation of ultrasound strain elastography and diffusion weighted magnetic resonance imaging in differentiating malignant from benign thyroid nodules

Comparative evaluation of ultrasound strain elastography and diffusion weighted magnetic resonance imaging in differentiating malignant from benign thyroid nodules

Peritumoural Strain Elastography of Newly Diagnosed Breast Tumours: Does Maximum Peritumoural Halo Depth Correlate with Tumour Differentiation and Grade?

To evaluate the diagnostic utility of the maximum ultrasound strain elastography (SE) halo depth in newly diagnosed and histologically confirmed breast lesions, a retrospective study approval was granted by the local Ethical Review Board. Overall, the maximum strain elastography peritumoural halos (SEPHmax)-the maximum distance between the SE stiffening area and the B-mode lesion size-in 428 cases with newly diagnosed breast lesions were retrospectively analysed alongside patient age, affected quadrant, tumour echogenicity, size, acoustic shadowing, and vascularity. Statistical analysis included an ordinary one-way ANOVA to compare the SEPHmax between BI-RADS 2, 3, and 5 groups and between tumour grades 1, 2, and 3. A binary regression analysis was used to determine the correlation between tumour malignancy and the above-mentioned demographic and imaging factors. SEPHmax was significantly higher in BI-RADS 5 tumours (5.5 ± 3.9 mm) compared to BI-RADS 3 (0.9 ± 1.7 mm, p < 0.0001) and 2 (0.6 ± 1.4 mm, p < 0.0001). The receiver operating characteristic area under the curve was 0.933 for the detection of BI-RADS 5 lesions. Furthermore, tumour grades 2 (5.6 ± 3.6 mm, p = 0.001) and 3 (6.8 ± 4.2 mm, p < 0.0001) exhibited significantly higher SEPHmax than grade 1 tumours (4.0 ± 3.9 mm). Similarly, St. Gallen Ki67-stratified low-risk (p = 0.005) and intermediate-risk (p = 0.013) tumours showed smaller SEPHmax than high-risk tumours. Multivariate analysis revealed a significant correlation between malignant differentiation and SEPHmax (standardized regression coefficient 3.17 [95% confidence interval (CI) 2.42-3.92], p < 0.0001), low tumour echogenicity (1.68 [95% CI 0.41-3.00], p = 0.03), and higher patient age (0.89 [95% CI 0.52-1.26], p < 0.0001). High SEPHmax is a strong predictor for tumour malignancy and a higher tumour grade and can be used to improve tumour characterisation before histopathological evaluation. It may also enable radiologists to identify lesions warranting observation rather than immediate biopsy.

Convolutional Neural Network-Based Speckle Tracking for Ultrasound Strain Elastography: An Unsupervised Learning Approach

Accurate and computationally efficient motion estimation is a critical component of real-time ultrasound strain elastography (USE). With the advent of deep-learning neural network models, a growing body of work has explored supervised convolutional neural network (CNN)-based optical flow in the framework of USE. However, the above-said supervised learning was often done using simulated ultrasound data. The research community has questioned whether simulated ultrasound data containing simple motion can train deep-learning CNN models that can reliably track complex in vivo speckle motion. In parallel with other research groups' efforts, this study developed an unsupervised motion estimation neural network (UMEN-Net) for USE by adapting a well-established CNN model named PWC-Net. Our network's input is a pair of predeformation and postdeformation radio frequency (RF) echo signals. The proposed network outputs both axial and lateral displacement fields. The loss function consists of a correlation between the predeformation signal and the motion-compensated postcompression signal, smoothness of the displacement fields, and tissue incompressibility. Notably, an innovative correlation method known as the globally optimized correspondence (GOCor) volumes module developed by Truong et al. was used to replace the original Corr module to enhance our evaluation of signal correlation. The proposed CNN model was tested using simulated, phantom, and in vivo ultrasound data containing biologically confirmed breast lesions. Its performance was compared against other state-of-the-art methods, including two deep-learning-based tracking methods (MPWC-Net++ and ReUSENet) and two conventional tracking methods (GLUE and BRGMT-LPF). In summary, compared with the four known methods mentioned above, our unsupervised CNN model not only obtained higher signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) for axial strain estimates but also improved the quality of the lateral strain estimates.

Preoperative strain ultrasound elastography can predict occult central cervical lymph node metastasis in papillary thyroid cancer: a single-center retrospective study.

To determine whether preoperative ultrasound elastography can predict occult central cervical lymph node metastasis (CCLNM) in patients with papillary thyroid cancer. This retrospective study included 541 papillary thyroid cancer patients with clinically negative lymph nodes prior to surgery between July 2019 and December 2021. Based on whether CCLNM was present on postoperative pathology, patients were categorized as CCLNM (+) or CCLNM (-). Preoperative clinical data, conventional ultrasound features, and ultrasound elastography indices were compared between the groups. Univariate and multivariate logistic regression analysis were performed to identify the independent predictors of occult CCLNM. A total of 36.60% (198/541) patients had confirmed CCLNM, while 63.40% (343/541) did not. Tumor location, bilaterality, multifocality, echogenicity, margin, shape, vascularity, capsule contact, extrathyroidal extension, aspect ratio, and shear wave elasticity parameters were comparable between the groups (all P > 0.05). Univariate analysis showed statistically significant differences between the two groups in age, sex, tumor size, calcification, capsule invasion, and strain rates ratio in strain ultrasound elastography (all P < 0.05). In multivariate logistic regression analysis, the independent predictors of occult CCLNM were age (OR = 0.975, 95% CI = 0.959-0.991, P = 0.002), sex (OR = 1.886, 95% CI = 1.220-2.915, P = 0.004), tumor size (OR = 1.054, 95% CI = 1.014-1.097, P = 0.008), and strain rates ratio (OR = 1.178, 95% CI = 1.065-1.304, P = 0.002). Preoperative strain ultrasound elastography can predict presence of occult CCLNM in papillary thyroid cancer patients and help clinicians select the appropriate treatment strategy.

Sonoelastographic Evaluation of Pelvic Adnexal Masses and its Association with Clinicopathological Findings at a Tertiary Care Centre in Western Uttar Pradesh, India

Introduction: Despite advancements in cross-sectional aging techniques, ultrasonography continues to remain the first-line imaging modality for the preoperative assessment of pelvic adnexal masses. Ultrasound strain elastography is a novel technique that can characterise adnexal lesions based on their tissue stiffness and when used in conjunction with conventional USG, it may increase the precision of diagnosis and can act as a cost-effective viable ancillary tool. Aim: To assess the role of strain sonoelastography in characterising the adnexal lesion as benign or malignant. Materials and Methods: This cross-sectional study was conducted in the Department of Radiodiagnosis, Teerthankar Mahaveer Medical College and Research Centre (TMMC&amp;RC), Moradabad, Uttar Pradesh, India, for a period of 18 months (January 2020 to June 2021) and consisted of 110 patients with clinical suspicion of adnexal mass, who were evaluated on SIEMENS Acuson S 3000 scanner (from the total of 130 cases). Various morphological features of mass (size, laterality, consistency, echogenicity and internal contents) were assessed on Gray scale and vascularity was assessed on colour doppler Ultrasonography (USG). Subsequently, real time strain elastography (eSie touch) was performed to assess the tissue stiffness. Elasticity was indicated on a colour-coded elastogram map, with blue areas denoting hard tissue, green areas suggesting intermediate tissue, and red portions denoting soft tissues. The sonographic findings were compared with histopathological diagnosis. Sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) were calculated for Gray scale sonography in combination with Doppler (conventional ultrasound techniques) and in conjunction with elastography. The Chi-square test was applied for comparing the frequency and p-value less than 0.05 was considered to be significant. Results: The mean age of study population was 36.35±14.82 years. On histopathology out of 110 patients, 95 (86.36%) had benign adnexal lesions and 15 (13.64%) had malignant adnexal lesions. The youngest patient was 16-year-old and eldest was 70 years and the mean age of the study population was 36.35 years. When conventional ultrasound technique was used alone for differentiating benign and malignant adnexal masses the sensitivity was 96.7%, specificity was 83%, PPV was 96.7% and NPV was 83% while on addition of sonoelastography the sensitivity increased to 98.9%, specificity increased to 93%, PPV increased to 98.9% and NPV increased to 93.7%. Conclusion: Conventional ultrasound techniques should be combined with sonoelastography in a diagnostic system to achieve better characterisation and differentiation of benign and malignant adnexal masses.

Sonographic and elastographic findings after arthroscopic rotator cuff repair: a comparison with clinical results.

We assessed the relationship between early postoperative clinical outcomes of arthroscopic rotator cuff repair (ARCR) and observations obtained by postsurgical ultrasound (US) and strain elastography (SE) of repaired supraspinatus tendons (SSTs). This retrospective study included 42 cases in which the patient underwent ARCR followed by postoperative US and SE. The Korean Shoulder Scoring (KSS) system was used to assess preoperative and postoperative conditions. The thickness of the repaired SST and subdeltoid fluid was measured by US. SE scores were classified into four grades (1 to 4) according to elasticity of repaired SST. In addition, SE scores were divided into two groups: soft (SE scores of 1 and 2) and hard (SE scores of 3 and 4). The relationship between clinical outcomes and US parameters and SE scores was determined by KSS. Postoperative SE scores observed by two readers correlated significantly with function (p = 0.021 and p = 0.021, respectively) and muscle strength (p = 0.008 and p = 0.015, respectively). SE scores were significantly correlated with a difference value of muscle strength of KSS scores (p = 0.002 and p = 0.014). In a comparison of hard and soft groups of repaired SSTs, function (p = 0.008 and p = 0.010, respectively) and muscle strength (p = 0.002 and p = 0.014, respectively) in postoperative KSS scores were statistically higher in the hard SE scores than the soft SE scores. The difference value of function (p = 0.021 and p = 0.021,) and muscle strength (p = 0.008 and p = 0.015) of KSS scores was significantly higher in the hard SE scores. Postoperative SE scores of repaired tendons correlated significantly with muscle strength and function after ARCR. Postoperative US images including thickness of repaired tendon and subdeltoid fluid did not correlate with clinical outcome. SE evaluations of repaired SST may provide important information about postoperative muscle strength and function.

Ultrafast Myocardial Principal Strain Ultrasound Elastography During Stress Tests: In Vitro Validation and In Vivo Feasibility.

Objective myocardial contractility assessment during stress tests aims to improve the diagnosis of myocardial ischemia. Tissue Doppler imaging (TDI) or optical flow (OF) speckle tracking echocardiography (STE) has been used to quantify myocardial contractility at rest. However, this is more challenging during stress tests due to image decorrelation at high heart rates. Moreover, stress tests imply a high frame rate which leads to a limited lateral field of view. Therefore, a large lateral field-of-view robust ultrafast myocardial regularized OF-TDI principal strain estimator has been developed for high-frame-rate echocardiography of coherently compounded transmitted diverging waves. The feasibility and accuracy of the proposed estimator were validated in vitro (using sonomicrometry as the gold standard) and in vivo stress experiments. Compared with OF strain imaging, the proposed estimator improved the accuracy of principal major and minor strains during stress tests, with an average contrast-to-noise ratio improvement of 4.4 ± 2.7 dB ( p -value < 0.01). Moreover, there was a significant correlation and a very close agreement between the proposed estimator and sonomicrometry for tested heart rates between 60 and 180 beats per minute (bpm). The averages ± standard deviations (STD) of R2 and biases ± STD between them were 0.96 ± 0.04 ( p -value < 0.01) and 0.01 ± 0.03% in the axial direction, respectively; and 0.94 ± 0.02 ( p -value < 0.01) and 0.04 ± 0.06% in the lateral direction, respectively. These results suggest that the proposed estimator could be useful clinically to provide an accurate and quantitative 2-D large lateral field-of-view myocardial strain assessment at high heart rates during stress echocardiography.