Association between myocardial layer-specific strain and high 10-year risk of atherosclerotic cardiovascular disease in hypertension-findings from the China-PAR project study.

Objectives: Myocardial layer-specific strain is a sensitive tool for detecting myocardial dysfunction. The objective of this study was to assess changes in the left ventricle (LV) function using myocardial layer-specific strain and its association with 10-year atherosclerotic cardiovascular disease risk (10Y-ASCVDR) in individuals with hypertension (HP). Methods: The parameters of LV structure, including layer-specific global longitudinal strain (GLSww, GLSendo, GLSmid, GLSepi) and layer-specific global circumferential strain (GCSww, GCSendo, GCSmid, GCSepi), were analyzed by two-dimensional speckle-tracking echocardiography in 239 hypertensive patients and 124 control subjects. In addition, participants were divided into low-risk (LR) and high-risk (HR) subgroups according to 10Y-ASCVDR scores . The correlation between myocardial layer-specific strain and 10Y-ASCVDR was further analyzed by the restricted cubic spline (RCS) function. Results: The values of GLSww, GLSepi, GLSmid, and GLSendo were significantly lower in HP patients with HR than in HP patients with LR and controls (p < 0.05). However, no significant differences in layer-specific GCS were observed between the groups (p > 0.05). RCS analysis revealed that 10Y-ASCVDR exhibited a significant J-shaped relationship with layer-specific GLS and GCS. After adjusting for confounding factors, GLSww (ß = 0.156, p = 0.042), GLSmid (ß = 0.161, p = 0.032), GCSendo (ß = 0.163, p = 0.024), and GCSmid (ß = -0.175, p = 0.030) were identified as independent influencing factors for high 10Y-ASCVDR. Conclusions: In hypertensive patients, myocardial layer-specific strain, especially GLS, sensitively detected LV dysfunction and showed a significant J-shaped relationship with 10Y-ASCVDR. GCSmid may have a compensatory effect on myocardial impairment. LV myocardial layer-specific strain may help to understand the early compensatory mechanisms of the myocardium in hypertension.

Central artery pulse pressure, not central arterial stiffness impact on all-cause mortality in patients with viral pneumonia infection.

OBJECTIVES: COVID-19 viral pneumonia can result in increased arterial stiffness, along with cardiac and systemic inflammatory responses. This study aimed to investigate the association between arterial stiffness, inflammation severity, and all-cause mortality in patients with COVID-19. METHODS: In this study, anthropometric data, pneumonia infection severity, and blood tests were analyzed. Arterial stiffness was assessed using the non-invasive assessment indices, including arterial velocity pulse index (AVI) and central arterial pulse pressure (CAPP). Infection volumes and percentages for the whole lungs, most lobes, and most segments were extracted from CT images using artificial intelligence-based quantitative analysis software. The relationship between arterial stiffness, central hemodynamics, and all-cause mortality was investigated. RESULTS: In multivariable Cox regression analysis, high CAPP was significantly associated with all-cause mortality (hazard ratio: 0.263, 95% CI, 0.073-0.945, p = 0.041). Whole lung infection percentages were independently associated with high CAPP, with an area under the curve (AUC) of 0.662 and a specificity of 89.09%. CONCLUSIONS: High CAPP, but not high AVI, demonstrated independent prognostic value for all-cause mortality in patients due to COVID-19 pneumonia infection. Evaluating this parameter could help in risk assessment and improve diagnostic and therapeutic strategies in viral pneumonia infections.

Unraveling Changes of Brachial Artery Residual Stress and Its Relationship to Cardiovascular Disease Risk Factors.

Background: Arterial pressure volume index (API) offers a non-invasive measurement of brachial artery residual stress. This study investigated API distribution characteristics and correlations with cardiovascular disease risk (CVD) factors in a large Chinese population sample. Methods: This cross-sectional study surveyed a total of 7620 participants. We analyzed the relationships between API and factors influencing CVD, using regression-based stepwise backward selection and restrictive cubic spline models to express relationships as standardized beta values. Results: Multiple linear regression analysis identified many independent factors influencing API including age, sex, body mass index (BMI), pulse pressure (PP), heart rate (HR), hemoglobin, uric acid (UA), estimated glomerular filtration rate (eGFR), triglyceride (TC), and a history of hypertension. Notably, API values increased at 33 and escalated with advancing age. Increases in API were associated with rises in PP and UA increases, particularly when PP reached 60 mmHg and the UA reached 525 units. Conversely, API was found to decrease with elevated HR and eGFR. Furthermore, there was a significant inverted U-shaped relationship between API and BMI. Conclusions: This study was the first to describe API distribution characteristics in a large sample of the Chinese population, providing references for evaluating API changes in the assessment of residual stress variations in diverse diseases. Notably, API displayed a U-shaped relationship with age and was closely related to traditional CVD risk factors, underscoring its potential as a non-invasive tool for risk assessment in vascular health. Clinical Trial Registration: This research was registered with the China Clinical Trial Registration Center (Registration Number: ChiCTR2000035937).

Relation of myocardial dysfunction to biomarkers, COVID-19 severity and all-cause mortality.

AIMS: The COVID-19 infection has been described as affecting myocardial injury. However, the relation between left ventricular global longitudinal strain (GLS), global circumferential strain (GCS) and global radial strain (GRS), disease severity and all-cause mortality in COVID-19 is unclear. METHODS AND RESULTS: The study consisted of 220 patients with COVID-19, including 127 (57.5%) with mild, 43 (19.5%) with moderate and 50 (22.7%) with severe/critical conditions. Myocardial dysfunction was analysed by GLS, GCS and GRS using two-dimensional speckle-tracking echocardiography. Hazard ratios and Kaplan-Meier curves were produced to assess the association between strains and cardiac biomarker indices with a composite outcome of all-cause mortality. With an average follow-up period of 11 days, 19 patients reached the endpoint (death). Significant associations were found for the three strain parameters and the levels of blood urea nitrogen (BUN) (r = 0.206, 0.221 and 0.355, respectively). Cardiac troponin I (cTnI) was closely related to the GLS and GCS (r = 0.240 and 0.324, respectively). In multivariable Cox regression, GCS > -21.6% was associated with all-cause death {hazard ratio, 4.007 [95% confidence interval (CI), 11.347-11.919]}. CONCLUSIONS: GLS, GCS and GRS are significantly related to myocardial dysfunction in patients with COVID-19. Worsening GCS poses an increased risk of death in COVID-19.

Prospective study of AI-assisted prediction of breast malignancies in physical health examinations: role of off-the-shelf AI software and comparison to radiologist performance.

Objective: In physical health examinations, breast sonography is a commonly used imaging method, but it can lead to repeated exams and unnecessary biopsy due to discrepancies among radiologists and health centers. This study explores the role of off-the-shelf artificial intelligence (AI) software in assisting radiologists to classify incidentally found breast masses in two health centers. Methods: Female patients undergoing breast ultrasound examinations with incidentally discovered breast masses were categorized according to the 5th edition of the Breast Imaging Reporting and Data System (BI-RADS), with categories 3 to 5 included in this study. The examinations were conducted at two municipal health centers from May 2021 to May 2023.The final pathological results from surgical resection or biopsy served as the gold standard for comparison. Ultrasonographic images were obtained in longitudinal and transverse sections, and two junior radiologists and one senior radiologist independently assessed the images without knowing the pathological findings. The BI-RADS classification was adjusted following AI assistance, and diagnostic performance was compared using receiver operating characteristic curves. Results: A total of 196 patients with 202 breast masses were included in the study, with pathological results confirming 107 benign and 95 malignant masses. The receiver operating characteristic curve showed that experienced breast radiologists had higher diagnostic performance in BI-RADS classification than junior radiologists, similar to AI classification (AUC = 0.936, 0.806, 0.896, and 0.950, p < 0.05). The AI software improved the accuracy, sensitivity, and negative predictive value of the adjusted BI-RADS classification for the junior radiologists' group (p< 0.05), while no difference was observed in the senior radiologist group. Furthermore, AI increased the negative predictive value for BI-RADS 4a masses and the positive predictive value for 4b masses among radiologists (p < 0.05). AI enhances the sensitivity of invasive breast cancer detection more effectively than ductal carcinoma in situ and rare subtypes of breast cancer. Conclusions: The AI software enhances diagnostic efficiency for breast masses, reducing the performance gap between junior and senior radiologists, particularly for BI-RADS 4a and 4b masses. This improvement reduces unnecessary repeat examinations and biopsies, optimizing medical resource utilization and enhancing overall diagnostic effectiveness.

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (grade I and II) and high-grade (grade III and IV) clear cell renal cell carcinoma (ccRCC). METHODS: A retrospective study was conducted using CEUS images of 177 Fuhrmangraded ccRCCs (93 low-grade and 84 high-grade) from May 2017 to December 2020. A total of 6412 CEUS images were captured from the videos and normalized for subsequent analysis. A deep learning model using the RepVGG architecture was proposed to differentiate between low-grade and high-grade ccRCC. The model's performance was evaluated based on sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve (AUC). Class activation mapping (CAM) was used to visualize the specific areas that contribute to the model's predictions. RESULTS: For discriminating high-grade ccRCC from low-grade, the deep learning model achieved a sensitivity of 74.8%, specificity of 79.1%, accuracy of 77.0%, and an AUC of 0.852 in the test set. CONCLUSION: The deep learning model based on CEUS images can accurately differentiate between low-grade and high-grade ccRCC in a non-invasive manner.

Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ.

OBJECTIVE: To investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment. METHODS: Consecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established. RESULTS: A total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867. CONCLUSION: Multi-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.

Predictive value of contrast-enhanced ultrasonography and ultrasound elastography for management of BI-RADS category 4 nonpalpable breast masses.

PURPOSE: The objective of this study was to investigate the independent risk factors and associated predictive values of contrast-enhanced ultrasound (CEUS), shear wave elastography (SWE), and strain elastography (SE) for high-risk lesions (HRL) and malignant tumors (MT) among nonpalpable breast masses classified as BI-RADS category 4 on conventional ultrasound. METHODS: This prospective study involved consecutively admitted patients with breast tumors from January 2018, aiming to explore the management of BI-RADS category 4 breast tumors using CEUS and elastography. We conducted a retrospective review of patient data, focusing on those with a history of a nonpalpable mass as the primary complaint. Pathologic findings after surgical resection served as the gold standard. The CEUS arterial-phase indices were analyzed using contrast agent arrival-time parametric imaging processing mode, while quantitative and qualitative indices were examined on ES images. Independent risk factors were identified through binary logistic regression multifactorial analysis. The predictive efficacy of different modalities was compared using a receiver operating characteristics curve. Subsequently, a nomogram for predicting the risk of HRL/MT was established based on a multifactorial logistic regression model. RESULTS: A total of 146 breast masses from 146 patients were included, comprising 80 benign tumors, 12 HRLs, and 54 MTs based on the final pathology. There was no significant difference in pathologic size between the benign and HRL/MT groups [8.00(6.25,10.00) vs. 9.00(6.00,10.00), P = 0.506]. The diagnostic efficacy of US plus CEUS exceeded that of US plus SWE/SE for BI-RADS 4 nonpalpable masses, with an AUC of 0.954 compared to 0.798/0.741 (P ï¼œ 0.001). Further stratified analysis revealed a more pronounced improvement for reclassification of BI-RADS 4a masses (AUC: 0.943 vs. 0.762/0.675, P ï¼œ 0.001) than BI-RADS 4b (AUC:0.950 vs. 0.885/0.796, P＞0.05) with the assistance of CEUS than SWE/SE. Employing downgrade CEUS strategies resulted in negative predictive values ranging from 95.2 % to 100.0 % for BI-RADS 4a and 4b masses. Conversely, using upgrade nomogram strategies, which included the independent predictive risk factors of irregular enhanced shape, poor defined enhanced margin, earlier enhanced time, increased surrounding vessels, and presence of contrast agent retention, the diagnostic performance achieved an AUC of 0.947 with good calibration. CONCLUSION: After investigating the potential of CEUS and ES in improving risk assessment and diagnostic accuracy for nonpalpable BI-RADS category 4 breast masses, it is evident that CEUS has a more significant impact on enhancing classification compared to ES, particularly for BI-RADS 4a subgroup masses. This finding suggests that CEUS may offer greater benefits in improving risk assessment and diagnostic accuracy for this specific subgroup of breast masses.

Predicting axillary metastasis in breast cancer using lymphatic contrast-enhanced ultrasound-guided fine-needle aspiration of one lymph node.

OBJECTIVES: Fine-needle aspiration (FNA) is a microinvasive method to diagnose lymph nodes. This study aims to determine the capability of lymphatic contrast-enhanced ultrasound (LCEUS)-guided FNA in predicting the axillary metastasis with the target of one lymph node (LN) in patients with breast cancer. METHODS: LCEUS was prospectively performed in 105 patients with breast cancer. The most suspicious LN was targeted based on the characters of LCEUS. FNA was performed in the LN, followed by localization using a guide wire. The detection of lymph cells and/or tumour cells was recognized as a puncture success. Cytologic diagnosis was compared with histologic diagnosis of wire-marked LN for diagnosing accuracy and compared with histologic diagnosis of axillary LNs for predicting accuracy. RESULTS: LCEUS-guided FNA was performed in all 105 female patients who underwent axillary dissection. The puncture success rates were 74.3%, 91.4%, and 97.1% for three sequential groups (P = .010). In diagnosing LN metastasis, the sensitivity, specificity, and accuracy values of LCEUS-guided FNA were 89.7%, 100%, and 95.7%, respectively. In predicting axillary metastasis, the sensitivity, specificity, and accuracy values of LCEUS-guided FNA were 81.4%, 100%, and 91.3%, respectively. CONCLUSIONS: The microinvasive LCEUS-guided FNA of one lymph node can be an accurate method and may help predict axillary metastasis in patients with breast cancer. ADVANCES IN KNOWLEDGE: This study presented that LCEUS combined with FNA would be practical in clinic. The characters of LCEUS could indicate the suspicious LNs and promote the accuracy in predicting axillary metastasis.

Sequence and directivity in cardiac muscle injury of COVID-19 patients: an observational study.

Objective: To compare cardiac function indicators between mild and moderate to severe COVID-19 patients and to try to identify the sequence and directivity in cardiac muscle injury of COVID-19 patients. Methods: From December 2022 to January 2023, all patients with laboratory-confirmed SARS-CoV-2 infection in Shanghai General Hospital Jiading Branch were enrolled. The clinical classification was stratified into mild, moderate, or severe groups. We collected the clinical and laboratory information, transthoracic echocardiographic and speckle-tracking echocardiographic parameters of patients and compared the differences among different groups. Results: The values of echocardiographic parameters in mild group were lower than that in moderate or severe group (P < 0.05) except LVEF. The values of LVEF of mild and moderate group were higher than severe group (P < 0.05). There were no significant differences between moderate and severe group. Positive correlations were observed between left ventricular global longitudinal strain (LVGLS) and myoglobin (r = 0.72), E/e' and age (r = 0.79), E/e' and BNP (r = 0.67). The multivariate analysis shows that SpO2 (OR = 0.360, P = 0.02), LVGLS (OR = 3.196, P = 0.003) and E/e' (OR = 1.307, P = 0.036) were the independent risk factors for mild cases progressing to moderate or severe. According to the receiver operating characteristic (ROC) curves, when all the COVID-19 patients was taken as the sample size, the area under the curve (AUC) of the LVGLS was the highest (AUC = 0.861). The AUC of the LVGLS was higher than LVGCS (AUC = 0.565, P < 0.001). Conclusion: When mild COVID-19 progresses to moderate or severe, both systolic and diastolic functions of the heart are impaired. LVGLS was the independent risk factor for mild cases progressing to moderate or severe cases. Longitudinal changes may manifest earlier than circumferential changes as myocardial disease progresses in COVID-19.

Uncoupling of the center-to-periphery arterial stiffness gradient and pulse pressure amplification in viral pneumonia infection.

OBJECTIVES: Arterial stiffness is a common manifestation of viral pneumonia infections, including COVID-19. Nevertheless, the relationship between the center-to-periphery arterial stiffness gradient and pulse pressure amplification (PPA) in infectious diseases remains unclear. This study aimed to investigate this relationship utilizing arterial pressure volume index (API) and arterial velocity pulse index (AVI) ratio. METHODS: API/AVI and PPA were measured in 219 participants with COVID-19 and 374 normal participants. Multiple linear regression was used to assess the association of API/AVI and PPA, and restricted cubic spline was used to investigate the non-linear relationship between API/AVI and PPA. Receiver operating characteristic curve (ROC) analysis was used to evaluate the effects of API/AVI in identifying COVID-19 infection and severe stage. RESULTS: There was a significant J-shaped relationship between API/AVI and PPA in COVID-19 group, while a M-shaped relationship was observed in normal group. API/AVI decreased rapidly as PPA decreased until API/AVI decreased slowly at PPA of 1.07, and then API/AVI decreased slowly again at PPA of 0.78. ROC results showed that API/AVI demonstrated excellent accuracy in identifying COVID-19 infection (AUC = 0.781) and a high specificity (84.88%) in identifying severe stage. CONCLUSIONS: There was a J-shaped association between the API/AVI and PPA in viral infected patients, while a M-shaped relationship in the normal participants. API/AVI is better for identifying infected and uninfected patients, with a high specificity in identifying those in severe stages of the disease. The attenuation or reversal of API/AVI may be associated with the loss of PPA coupling.

The kinetic quantitative characteristics of non-mass breast lesions with contrast-enhanced ultrasound: a prospective study.

OBJECTIVE: To characterize non-mass breast lesions (NML) quantitatively by contrast-enhanced ultrasound (CEUS) and to evaluate its additional diagnostic value based on the Breast Imaging Reporting and Data System (BI-RADS) categories. METHODS: A prospective study was performed among consecutive patients with NMLs. All lesions were examined by grayscale ultrasound and CEUS and diagnosed on pathology. Standard mammograms were obtained in the patients over 30 years old. Three independent radiologists assessed the features on grayscale ultrasound and mammograms and classified NMLs according to BI-RADS categories. Combined with the quantitative analysis in CEUS, the BI-RADS categories were reassessed, and the sensitivity, specificity, positive-predictive value, negative-predictive value and area under the receiver operating characteristic curve (AUC) were calculated for the evaluation of the diagnostic performance. RESULTS: 30 benign and 24 malignant NMLs were finally enrolled in this study, with ductal carcinoma in situ being the majority of malignant (15/24). Average contrast signal intensity (AI), wash-in rate (WiR) and enhancement intensity at 40 s (I40) were found to be the most efficient kinetic parameters to diagnose malignant NMLs. Combined with the cut-off values of 205.2 for AI, 127.8 for WiR and 136.4 for I40, the diagnostic accuracy was improved (AUC = 0.904), with the sensitivity of 95.8% and the specificity of 70.0%. CONCLUSION: The results suggested that hyperenhancement and rapid wash-in and wash-out are the characteristics of malignant NMLs. The kinetic analysis using CEUS can reflect hypervascular nature of malignant NMLs, thus improving the diagnostic performance combined with grayscale ultrasound. ADVANCES IN KNOWLEDGE: In this study, we quantified the enhancement characteristics of non-mass breast lesions with CEUS. We revealed that the combination of CEUS and conventional ultrasound provided higher sensitivity for diagnosing malignant NMLs.

Value of an expanded range of lesions on contrast-enhanced ultrasound for the diagnosis of hypervascular breast masses.

Background: Breast cancer lesions show an expanded range on contrast-enhanced ultrasound (CEUS). Here, we quantitatively analyze this index to explore its effective cutoff value for distinguishing benign and malignant lesions and the corresponding diagnostic performance and investigate its role in prognostic assessment of malignant lesions. Methods: Consecutive patients who underwent CEUS for breast lesions during the period from September 2017 to June 2019 were included. Original CEUS images were selected, displayed in dual-frame mode, and measured when enhancement of the lesion reached its peak. The longitudinal diameter, transverse diameter, and area of the lesion on the two-dimensional images and the corresponding postenhancement images were measured to calculate six indicators: longitudinal diameter increment, transverse diameter increment, area increment, percent increase in longitudinal diameter, percent increase in transverse diameter, and percent increase in area increment. With postoperative pathology as the gold standard, the cutoff values for distinguishing benign and malignant lesions and the correlations of these indicators with pathological subtypes and pathological grades were evaluated. Results: Malignant lesions showed a more significantly expanded range after enhancement compared to benign lesions, especially in terms of area increase. When the cutoff value of the area increment was set at 0.47 cm2 for distinguishing between benign and malignant lesions, the area under the curve (AUC) was 0.945, and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 90.1%, 91.5%, 90.9%, 87.2%, and 93.5%, respectively. The pathologically measured maximum diameter of malignant masses correlated with the percent increase in transverse diameter, area increment, and percent increase in area increment. The longitudinal diameter increment in the luminal A group was significantly smaller than that in the human epidermal growth factor receptor 2 (HER2)+ group. The percent increase in transverse diameter was helpful for predicting the pathological grade of malignant masses. When the cutoff value of the percent increase in transverse diameter was set at 10.84% for pathological grading, the AUC was 0.623, and the sensitivity was 90.8%. Conclusions: Indicators related to the expanded lesion range on CEUS are helpful in differential diagnosis of benign and malignant lesions and in prognostic assessment of pathological grades.

Contrast-Enhanced Ultrasonography for Transabdominal and Transrectal Ultrasound in Staging Cervical Cancer: A Reliability Study.

OBJECTIVE: This retrospective study aimed to evaluate the consistency of transrectal contrast-enhanced ultrasonography (TR-CEUS) with post-operative pathology and the value of contrast-enhanced ultrasonography (CEUS) in staging surgically treated cervical cancer when combined with conventional ultrasonography (US). METHODS: From October 2020 to March 2023, hospitalized patients with stage IB and II cervical cancer confirmed by total hysterectomy were consecutively enrolled. The standard images of US and CEUS by transabdominal (TA-US/CEUS) and transrectal (TR-US/CEUS) approaches and magnetic resonance imaging (MRI) were acquired, on which the size and stage of the tumors were evaluated, and the consistency of results with the pathological specimen was analyzed. RESULTS: Thirty-nine patients with cervical cancer were finally enrolled in this study. The results showed that CEUS significantly improved the reliability of TA-US in evaluating tumor diameter; the intraclass correlation coefficient (ICC) was from 0.672 to 0.735. TR-US indicated good reliability with or without the addition of CEUS (ICC = 0.796 and 0.780). In terms of tumor staging, CEUS improved the consistency of transabdominal (weighted κ values from 0.689 to 0.731) and transrectal staging of tumors (κ from 0.758 to 0.785), and the staging of TR-US combined with TR-CEUS had the highest consistency with post-operative results, similar to MRI (κ, respectively 0.785 and 0.789). CEUS can reflect the heterogeneity of the tumor. Heterogeneous enhancement and perfusion defects were more common in >2 cm cervical cancer (50%, 20/40 and 52.5%, 21/40), respectively, and perfusion defects were more common in moderately to poorly differentiated tumors (66.67%, 20/30). CONCLUSION: For stage IB and IIA cervical cancer, CEUS can aid in assessing the International Federation for Gynecology and Obstetrics staging of tumors alongside TA-US and TR-US. The combination of TR-US and TR-CEUS has shown good consistency with pathology in the staging of cervical cancer, comparable to that of MRI.

Relative contributions of arterial stiffness to cardiovascular disease risk score in Chinese women in framingham and China-PAR model.

Background: Arterial stiffness played an important role in the development of cardiovascular disease (CVD) events. The aim of this study was to verify the relative importance of arterial stiffness for different CVD risk scores in a large sample of Chinese women. Methods: We measured arterial velocity pulse index (AVI) and CVD risk scores in 2220 female participants (mean age 57 years). Framingham Risk Score (FRS), and the prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) were used to estimate CVD risk, respectively. The relationships between AVI and risk scores were investigated by linear regressions and restricted cubic spline (RCS) analysis. To determine the relative importance of AVI in predicting CVD risk scores, random forest analysis was used. Results: There was a significant positive correlation between AVI and FRS, China-PAR in all subgroup groups stratified by age, blood pressure and BMI. AVI showed higher importance in predicting CVD risk scores in FRS model, compared with these traditional risk factors. In China-PAR model, although AVI was not as predictive as SBP, it had better predictive power than many known risk factors such as lipids. Furthermore, AVI had significant J-shaped associations both with FRS and China-PAR scores. Conclusions: AVI was significantly associated with CVD risk score. In FRS and China-PAR model, AVI showed relatively high importance in predicting CVD risk scores. These findings may support the use of arterial stiffness measurements in CVD risk assessment.

The predictive models based on multimodality ultrasonography for the differential diagnosis of thyroid nodules smaller than 10 mm.

OBJECTIVE: The objective of this study was to establish a multimodality ultrasound prediction model based on conventional ultrasound (Con-US), shear wave elastography (SWE), and strain elastography (SE) and contrast-enhanced ultrasound (CEUS) and to explore their diagnostic values for thyroid nodules ≤ 10 mm. METHODS: This retrospective study included 198 thyroid nodules (maximum diameter≤10 mm) in 198 thyroid surgery patients who were examined preoperatively with above-mentioned methods. The pathological findings of the thyroid nodules were used as the gold standard, and there were 72 benign nodules and 126 malignant nodules. The multimodal ultrasound prediction models were developed by logistic regression analysis based on the ultrasound image appearances. The diagnostic efficacy of these prediction models was then compared and internally cross-validated in a fivefold manner. RESULTS: The specific features on CEUS (enhancement boundary, enhancement direction and decreased nodule area) and the parenchyma-to-nodule strain ratio (PNSR) on SE and SWE ratio were included in the prediction model. The Model one combining American College of Radiology Thyroid Imaging Reporting and Data Systems (ACR TI-RADS) score with PNSR and SWE ratio had the highest sensitivity (92.8%), while the Model three combining TI-RADS score with PNSR, SWE ratio and specific CEUS indicators had the highest specificity, accuracy, and AUC (90.2%,91.4%, and 0.958, respectively). CONCLUSION: The multimodality ultrasound predictive models effectively improved the differential diagnosis of thyroid nodules smaller than 10 mm. ADVANCES IN KNOWLEDGE: For the differential diagnosis of thyroid nodules ≤ 10 mm, both ultrasound elastography and CEUS could be effective complements to ACR TI-RADS.

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

Objective: To determine whether preoperative ultrasound elastography can predict occult central cervical lymph node metastasis (CCLNM) in patients with papillary thyroid cancer. Methods: 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. Results: 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). Conclusion: Preoperative strain ultrasound elastography can predict presence of occult CCLNM in papillary thyroid cancer patients and help clinicians select the appropriate treatment strategy.

Can pre-operative ultrasound elastography predict aggressive features of solitary papillary thyroid carcinoma?

OBJECTIVE: To investigate whether pre-operative ultrasound elastography (USE) can be used to predict aggressive features of solitary papillary thyroid carcinomas (PTCs). METHODS: Clinical and USE indices were retrospectively analyzed in 487 patients with surgically confirmed solitary PTCs. The patients were grouped per aggressive features on pathologic testing. Univariate and binary logistic regression analyses were performed to explore independent risk factors of aggressive features. RESULTS: Univariate analysis revealed standard deviation (SD) values of the tumor shear-wave velocity (SWV) were associated with capsular invasion (p < 0.05). Further, shear-wave elasticity and SWV ratios correlated with extrathyroidal extension (all p < 0.05). The tumor shear-wave elasticity and SWV SD values were associated with cervical lymph node metastasis (CLNM) (all p < 0.05). Binary logistic regression analysis identified location and capsule contact as independent predictive risk factors for capsular invasion (all p < 0.05); size for extrathyroidal extension (all p < 0.05); and sex, age, margin, and suspected CLNM for CLNM (all p < 0.05). However, pre-operational USE indexes were not independent predictors of aggressive features (all p > 0.05). CONCLUSION: Pre-operative USE indices were not independent risk factors of aggressive features of solitary PTCs. Thus, USE may have a limited value for predicting the aggressive features of PTC. ADVANCES IN KNOWLEDGE: Pre-operative USE indices may have a limited value for predicting the aggressive features of PTC.

UTMD inhibits pancreatic cancer growth and metastasis by inducing macrophage polarization and vessel normalization.

Pancreatic cancer (PaCa) is a hypovascular type of tumor and is not very responsive to conventional chemotherapy due to the problem of low drug accumulation. Recent advancements in ultrasound targeted microbubble destruction (UTMD) have improved drug delivery into target tissues. UTMD operates via microbubble interaction with vascular endothelial cells; however, the molecular mechanism and interrelationship in the PaCa microenvironment remain enigmatic. Tumor-associated macrophages (TAMs) have different phenotypes and regulate tumorigenesis. Using a PaCa orthotopic model, we established that UTMD improved chemotherapy by redirecting TAM polarization from M2 macrophages to tumor-inhibiting M1 macrophages, remodeling vessel normalization, and inducing anti-tumor immune responses. Tumor vascular maturity and function were also improved, and an insignificant change in vascular density resulting in enhanced blood perfusion and inhibited tumor growth and metastasis were observed. Therefore, this research unveils the crucial role of TAM polarization on UTMD-induced tumor vessel normalization and inhibition of tumor progression. These findings offer a novel insight into UTMD-mediated drug delivery for anti-tumor and anti-angiogenic treatment.

Nomogram incorporating preoperative clinical and ultrasound indicators to predict aggressiveness of solitary papillary thyroid carcinoma.

Objective: To construct a nomogram based on preoperative clinical and ultrasound indicators to predict aggressiveness of solitary papillary thyroid carcinoma (PTC). Methods: Preoperative clinical and ultrasound data from 709 patients diagnosed with solitary PTC between January 2017 and December 2020 were analyzed retrospectively. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with PTC aggressiveness, and these factors were used to construct a predictive nomogram. The nomogram's performance was evaluated in the primary and validation cohorts. Results: The 709 patients were separated into a primary cohort (n = 424) and a validation cohort (n = 285). Univariate analysis in the primary cohort showed 13 variables to be associated with aggressive PTC. In multivariate logistic regression analysis, the independent predictors of aggressive behavior were age (OR, 2.08; 95% CI, 1.30-3.35), tumor size (OR, 4.0; 95% CI, 2.17-7.37), capsule abutment (OR, 2.53; 95% CI, 1.50-4.26), and suspected cervical lymph nodes metastasis (OR, 2.50; 95% CI, 1.20-5.21). The nomogram incorporating these four predictors showed good discrimination and calibration in both the primary cohort (area under the curve, 0.77; 95% CI, 0.72-0.81; Hosmer-Lemeshow test, P = 0.967 and the validation cohort (area under the curve, 0.72; 95% CI, 0.66-0.78; Hosmer-Lemeshow test, P = 0.251). Conclusion: The proposed nomogram shows good ability to predict PTC aggressiveness and could be useful during treatment decision making. Advances in knowledge: Our nomogram-based on four indicators-provides comprehensive assessment of aggressive behavior of PTC and could be a useful tool in the clinic.