Ultrasonic features of automated breast volume scanner (ABVS) and handheld ultrasound (HHUS) combined with molecular biomarkers in predicting axillary lymph node metastasis of clinical T1-T2 breast cancer.

Background: In the post-American College of Surgeons Oncology Group Z0011 trial era, clinicians are attempting to preoperatively evaluate axillary lymph node (ALN) status using ultrasound. However, the value of preoperative ultrasound examination remains uncertain. The study aimed to investigate the ultrasonic features of automated breast volume scanner (ABVS) and handheld ultrasound (HHUS), in combination with molecular biomarkers, to predict the risk of ALN metastasis (ALNM) in clinical T1-T2 breast cancer. Methods: A retrospective case-control analysis was conducted on 168 patients with clinical T1-T2 breast cancer at Peking University First Hospital between January 2013 and August 2021. Preoperative ABVS and HHUS examinations were performed. According to the pathology results of the ALN, patients were divided into metastatic and nonmetastatic groups. Logistic regression analyses were used to analyze the ultrasonic characteristics of ABVS and HHUS on clinical T1-T2 breast cancer, and molecular biomarkers were incorporated to predict the risk of ALNM. Results: Of the 168 patients, 88 (52.4%) had ipsilateral ALNM while 80 (47.6%) had no ipsilateral ALNM. The univariate analysis showed that shorter tumor-skin distance (P=0.011), the Adler blood flow grade of II-III (P=0.014), and larger tumor size on ABVS (P<0.001) were associated with ALNM. The multivariate logistic analysis showed that these three risk factors, including the tumor-skin distance [odds ratio (OR) =0.279; P=0.024], the Adler blood flow grade (OR =2.164; P=0.046), and the tumor size on ABVS (OR =1.033; P=0.002), were independent predictive parameters. Conclusions: The tumor-skin distance, tumor size on ABVS, and Adler blood flow grade have diagnostic value for ALNM in clinical T1-T2 breast cancer.

Contrast-enhanced ultrasound evaluation of renal perfusion before angioplasty and its predictive value for hypertension.

BACKGROUND: Atherosclerotic renal artery stenosis (ARAS) is a common disease in the elderly population. OBJECTIVE: The aim was to develop a contrast-enhanced ultrasound (CEUS)-based model for predicting post-angioplasty improvement in hypertension in patients with severe ARAS. METHODS: Thirty-five patients with severe ARAS (⩾ 70%) were included in this study, and 42 renal arteries received percutaneous transluminal renal arterial stenting. An optimal integral formula was developed from pre-interventional color-coded duplex sonography (CCDS) and CEUS parameters using least absolute shrinkage and selection operator (LASSO) regression and receiver operating characteristic (ROC) curve analysis. A model for predicting short-term hypertension improvement was established using the integral formula and clinical risk factors. Bootstrapping was used for internal validation. RESULTS: Two integral formulas, LASSO.CCDS and LASSO.CEUS, were established. ROC curves of the two integral formulas showed that LASSO.CEUS was the better formula for predicting hypertension improvement (AUC 0.816, specificity 78.6%). Univariate and multivariate regression analyses showed that duration of hypertension (OR 0.841, P= 0.027), diabetes (OR = 0.019, P= 0.010), and LASSO.CEUS (OR 7.641, P= 0.052) were predictors of short-term hypertension improvement after interventional therapy. Using LASSO.CEUS combined with clinical risk factors, the following prediction model was established: logit (short-term improvement in hypertension) = 1.879-0.173 × hypertension duration - 3.961 × diabetes + 2.034 × LASSO.CEUS (AUC 0.939). CONCLUSIONS: The model established using CEUS parameters and clinical risk factors could predict hypertension improvement after interventional therapy, but further research and verification are needed.

Comparison of the diagnostic performance and clinical role of different ultrasound-based thyroid malignancy risk stratification systems for medullary thyroid carcinoma.

Background: This study sought to investigate the applicability of different ultrasound (US) thyroid risk stratification systems in diagnosing medullary thyroid carcinoma (MTC) and determining the need for biopsy. Methods: In total, 34 MTC nodules, 54 papillary thyroid carcinoma (PTC) nodules, and 62 benign thyroid nodules were examined in this study. All the diagnoses were histopathologically confirmed postoperatively. All the thyroid nodule sonographic features were recorded and categorized by 2 independent reviewers according to the Thyroid Imaging Reporting and Data System (TIRADS) of the American College of Radiology (ACR), the American Thyroid Association (ATA) guidelines, the European Thyroid Association (EU) TIRADS, the Kwak-TIRADS, and the Chinese TIRADS (C-TIRADS). The sonographic differences and risk stratifications of the MTCs, PTCs, and benign thyroid nodules were analyzed. The diagnostic performance and recommended biopsy rates for each classification system were evaluated. Results: The risk stratifications of MTCs were all higher than the benign thyroid nodules (P<0.01) and lower than PTCs (P<0.01) with each classification system. Hypoechogenicity and malignant marginal features were independent risk factors for identifying malignant thyroid nodules, and the area under the receiver operating characteristic curve (AUC) for identifying MTCs was lower than that for identifying PTCs (0.873 vs. 0.954, respectively). The AUCs, sensitivity, specificity, positive predictive values, negative predictive values, and accuracy values of the 5 systems for MTC were all lower than those for PTC. The best cut-off values for diagnosing MTC were TIRADS (TR) 4 in the ACR-TIRADS, intermediate suspicion in the ATA guidelines, TR 4 in EU-TIRADS, and TR 4b in both the Kwak-TIRADS and the C-TIRADS. The Kwak-TIRADS had the highest recommended biopsy rate for MTCs (97.1%), followed by the ATA guidelines, the EU-TIRADS (88.2%), the C-TIRADS (85.3%), and the ACR-TIRADS (79.4%). Conclusions: The US-based thyroid malignancy risk stratification systems analyzed in this study were able to satisfactorily identify MTC and recommend biopsy, but the diagnostic performance of these systems for MTC was not as good as that for PTC.

Real-time ultrasound elastography evaluation of achilles tendon properties in patients with mild hemiplegic stroke after rehabilitation training.

OBJECTIVE: This study aims to evaluate the Achilles tendon's properties after rehabilitation training in patients with stroke using real-time ultrasound elastography. METHODS: A total of 24 patients with mild hemiplegic stroke in the past 6 to 12 months and unilateral lower limb movement disorder were prospectively enrolled. All patients accepted 9-week rehabilitation training with the same schema. The 2-dimensional elastography and real-time elastography findings in the impaired and contralateral normal Achilles tendon were measured at pretraining and at 3, 6, and 9 weeks after training, which included tendon length, thickness, elasticity score (grade 1-3), and strain ratio of fat to tendon. The functional properties, which include the 10-meter walk test and timed up-and-go scores, were evaluated before and after the 9-week training. RESULTS: The impaired Achilles tendon had a longer length (P = .002), lower frequency of grade 1 (P = .012), and lower strain ratio (P = .009) than the contralateral tendon before training. The impaired tendons at the third, sixth, and ninth weeks after training were compared to ones before training, respectively, which revealed shorter length, increased frequency of grade 1, and increased strain ratio. The first statistically significant changes in the length were observed at the sixth week, while such changes in elasticity score and strain ratio were observed at the ninth week. CONCLUSIONS: Two-dimensional elastography and real-time elastography can provide valuable imaging markers for quantitatively evaluating the Achilles tendon's properties after rehabilitation training in patients with stroke.

[Logistic regression analysis of clinical and ultrasonic features of breast nodules].

OBJECTIVE: To create a breast nodule estimation model based on grayscale and color Doppler ultrasonography using Logistic regression that can screen out the specific features for distinguishing breast malignancy from benignancy. METHODS: From July, 2009 to May, 2010, 217 patients were enrolled in the study in peking university first hospital. Clinical data and ultrasonic features were evaluated in 219 breast nodules of 217 patients confirmed by surgical pathology. Logistic regression model was established to screen out significant ultrasonic indexes for differentiating breast malignancy from benignancy. A receiver operating characteristics curve was made to assess diagnostic value of the Logistic regression model. Correlation was analyzed between the Logistic regression model and surgical pathology. RESULTS: Logistic regression model: Logit(p) = -16.884 + 0.037 × age + 3.228 × longitudinal-transverse axis ratio + 1.412 × border + 2.663 × halo + 1.813 × microcalcium + 1.157 × resistance index + 2.204 × enlarged axillary lymph node (χ(2) = 167.107, P = 000). The areas of ROC curve for probability and identification of breast malignant and benign nodule were 0.948 and 0.882 respectively. Diagnostic sensitivity, specificity and accuracy were 91.6%, 84.9% and 88.9%. Logistic regression model positively correlated with surgical pathology (r = 0.768, P = 0.000). CONCLUSION: Our Logistic regression model can effectively differentiate malignant breast nodules from benign and can identify the ultrasonic features associated with breast cancer.