Search

To assess the feasibility and performance of Turbulence (Tur) index as a quantitative tool for carotid artery flow turbulence; to detect and compare the blood flow patterns of common carotid artery (CCA) and carotid bulb (CB) at different ages and cardiac phases in healthy adults, and thus interpret the evolvement of etiology difference between CCA and CB. Carotid flow characteristics of 40 healthy volunteers were evaluated quantitatively by a high‐frame rate vector flow imaging. Three types of flow patterns were defined depending on the distributive range of complex flow during systole in CB. Comparison of mean Tur value in CCA and CB at different age groups and cardiac phases was performed. And the correlation between Tur value and the diameter ratio of proximal internal carotid artery to common carotid artery (DRpro‐ica/cca) was tested. Mean Tur values in CB were remarkably higher than that in CCA, whether during systole or diastole (P< .001). Meanwhile Tur values in CB during systole were significantly higher than that during diastole (P< .001). Flow complexity of CB showed variations among 40 participants especially in systole, whereas the flow pattern of CCA was relatively consistent. Mean Tur values were positively correlated with DRpro‐ica/cca in CB (ρ= 0.69, P< .05). V Flow imaging provided a reliable method—Tur, for quantitative analysis of carotid blood flow. It had potential to be further applied in distinguishing complex hemodynamic characteristics in high‐risk people of carotid diseases for the risk stratification of cardiovascular events.

Purpose To assess whether gray-scale ultrasound (US) based radiomic features can help distinguish HER2 expressions (ie, HER2-overexpressing, HER2-low-expressing, and HER2-zero-expressing) in breast cancer.Materials and Methods This retrospective study encompassed female breast cancer patients who underwent US examinations at two distinct centers from February 2021 to July 2023. Tumor segmentation and radiomic feature extraction were performed on grayscale US images. Decision Tree analysis was employed to simultaneously evaluate feature importance, and the Least Absolute Shrinkage and Selection Operator technique was utilized for feature selection to construct the radiomic signature. The Area Under the Curve (AUC) of the Receiver Operating Characteristic curve was employed to assess the performance of the radiomic features. Multivariate logistic regression was used to identify independent predictors for distinguishing HER2 expression in the dataset.Results The training set comprised 292 patients from Center 1 (median, 51 years; interquartile range [IQR]: 45-61), while the external validation set included 131 patients from Center 2 (median, 51 years; IQR: 45-62). In the external validation dataset, the radiomic features achieved AUC of 0.76 for distinguishing between HER2-low and positive tumors versus HER2-zero tumors. The AUC for differentiating HER2-low (1+) from HER2-zero tumors was 0.74, and for distinguishing HER2-low (2+) from HER2-zero tumors, the AUC was 0.77. In the multivariate analysis assessing HER2-low and HER2-positive versus HER2-zero tumors, internal echoes (P = .029) and margins (P < .001) emerged as independent predictive factors.Conclusion The radiomic signature and tumor descriptors from gray-scale US may predict distinct HER2 expressions of breast cancers with therapeutic implications.

The success of gene therapy depends largely on the development of gene vectors and effective gene delivery systems. It has been demonstrated that cationic microbubbles can be loaded with negatively charged plasmid DNA and thus improve gene transfection efficiency. In this study, we developed dual-targeting cationic microbubbles conjugated with iRGD peptides(Cyclo(Cys-Arg-Gly-Asp-Lys-Gly-Pro-Asp-Cys)) and CCR2 (chemokine (C–C motif) receptor 2) antibodies (MBiRGD/CCR2) for ultrasound molecular imaging and targeted tumor gene therapy. The ultrasound molecular imaging experiments showed that there were significantly enhanced ultrasound molecular imaging signals in the tumor that received MBiRGD/CCR2, compared with those that received MBiRGD, MBCCR2, or MBcontrol. As a therapy plasmid, pGPU6/GFP/Neo-shAKT2, carrying an expression cassette for the human AKT2RNA interference sequence, was used. Our results demonstrated that MBiRGD/CCR2had a significantly higher gene transfection efficiency than MBiRGD, MBCCR2, or MBcontrolunder ultrasound irradiation, resulting in much lower AKT2protein expression and stronger tumor growth inhibition effects in vivoand in vitro. In conclusion, our study demonstrated a novel gene delivery system viaMBiRGD/CCR2for ultrasound molecular-imaging-guided gene therapy of breast cancer.

This study aimed to evaluate the clinical value of the elastographic Q‐analysis score (EQS) in assisting real‐time elastography‐ and transrectal US‐guided prostate biopsy. A total of 125 patients with 301 lesions were enrolled in this study; all were confirmed by pathologic results. The patients underwent transrectal US and elastographic examinations before biopsy. Elastographic Q‐analysis score analysis software was used for measuring the mean EQS of the elastic images. First, the suspicious regions on elastography underwent biopsy. Then 12‐core systematic prostate biopsy was performed. An EQS curve was used to calculate the mean EQS, and a receiver operating characteristic curve was drawn to find the cutoff point for the EQS to predict prostate cancer. Of the 301 lesions in this study, 125 were malignant, and 176 were benign. The mean EQS values of benign and malignant lesions ± SD were 1.47 ± 0.75 and 2.98 ± 1.06, respectively. The difference was statistically significant (P< .05). The area under the receiver operating characteristic curve was 0.87. When the cutoff point was 1.95 for diagnosing malignant and benign lesions, the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio were 83.5%, 84.4%, 76.8%, 89.2%, 5.35, and 0.20. The EQS could be used as a way to predict benign and malignant lesions and thus could serve as guidance for adding targeted biopsy.

This study retrospectively evaluated the prognostic performance of the ultrasound elastographic Q‐analysis score (EQS) combined with the Prostate Imaging Reporting and Data System (PI‐RADS) for malignancy risk stratification in prostate nodules based on transrectal ultrasound–magnetic resonance imaging fusion imaging. Sixty‐two patients who were suspected to have PCa between October 2017 and May 2018 in our hospital were retrospectively evaluated. The performance of the EQS and PI‐RADS was evaluated by patients’ receiver operating characteristic curves in differentiating malignant and benign prostate nodules. The combination of the EQS and PI‐RADS methods for prostate imaging was evaluated. Sixty‐two prostate nodules in 62 patients were included. All of the patients underwent biopsy; 29 cases were prostate cancer, and the rest were benign prostate lesions. Both the EQS and PI‐RADS were significantly higher in malignant nodules than in benign nodules. The sensitivity, specificity, area under the curve, positive likelihood ratio, negative likelihood ratio, positive predictive value, negative predictive value, and Youden index of an EQS cutoff of 2.05 were 86.2%, 81.8%, 85.9%, 4.73, 0.169, 80.6%, 87.1%, and 68%, respectively. The corresponding numbers for a PI‐RADS cutoff of 4 were 82.7%, 69.7%, 84.2%, 2.72, 0.25, 70.6%, 82.1%, and 52.4%. The “tandem” method had a higher diagnostic specificity (87.9%), positive likelihood ratio (6.55), and positive predictive value (85.1%). The “parallel” method had a higher diagnostic sensitivity (96.5%), negative likelihood ratio (0.06), and negative predictive value (95.2%). both the EQS and PI‐RADS had good diagnostic performance in differentiating between malignant and benign prostate lesions. The combination of the EQS and PI‐RADS improved the diagnostic performance to a certain degree.

Evaluating the value of screening breast masses by separate or combined use of multimodal Sound Touch Elastography. Women with 159 masses (mean size, 14.86 ± 6.57 mm; range, 5.30–30.00 mm) were enrolled in the study. The pathology results were adopted as diagnostic standards. The abilities of Young's modulus (E), shear modulus (G), and shear wave (C) to differentiate malignant and benign breast masses based on receiver operating characteristic curves were evaluated, and the optimal cutoff values were obtained. Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated. Then, the values were combined to perform an overall analysis of Sound Touch Elastography using evidence‐based medicine, construct forest plots, and calculate areas under the summary receiver operating characteristic curves, pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic scores. A total of 159 masses with a mean size of 14.86 ± 6.57 mm (range, 5.30–30.00 mm) were included. For the various parameters, the diagnostic values were as follows: Gmax> Emax> Cmax> Csd> Esd> Gsd> Emean> Gmean> Cmean. There were no significant differences in Emin, Gmin, or Cmin. When the 9 parameters were combined, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic scores and areas under the summary receiver operating characteristic curves were 84% (95% confidence interval [CI], 79%–88%), 82% (95% CI, 80%–84%), 4.75 (95% CI, 4.15–5.43), 0.20 (95% CI, 0.15–0.25), 3.19 (95% CI, 2.84–3.54) and 90.2% (95% CI, 87%–92%), respectively. Sound Touch Elastography can be recognized as a new ultrasound‐based diagnostic method for differentiation between benign and malignant breast masses.

Hepatic fibrosis is a common pathological process in many chronic liver diseases. TXNDC5 has been shown to be involved in the progression of renal and pulmonary fibrosis. However, the role of TXNDC5 in hepatic fibrosis is unknown. The purpose of this study is to explore the role and mechanism of TXNDC5 in hepatic fibrosis.

Multimodal ultrasound has demonstrated its power in the clinical assessment of rheumatoid arthritis (RA). However, for radiologists, it requires strong experience. In this paper, we propose a rheumatoid arthritis knowledge guided (RATING) system that automatically scores the RA activity and generates interpretable features to assist radiologists' decision-making based on deep learning. RATING leverages the complementary advantages of multimodal ultrasound images and solves the limited training data problem with self-supervised pretraining. RATING outperforms all of the existing methods, achieving an accuracy of 86.1% on a prospective test dataset and 85.0% on an external test dataset. A reader study demonstrates that the RATING system improves the average accuracy of 10 radiologists from 41.4% to 64.0%. As an assistive tool, not only can RATING indicate the possible lesions and enhance the diagnostic performance with multimodal ultrasound but it can also enlighten the road to human-machine collaboration in healthcare.

To review the diagnostic accuracy of transvaginal ultrasound (TVS) in the preoperative detection of uterosacral ligaments (USL) in patients with clinical suspicion of deep infiltrating endometriosis (DIE).