Predicting Ki-67 expression in hepatocellular carcinoma: nomogram based on clinical factors and contrast-enhanced ultrasound radiomics signatures.

PURPOSE: To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC). METHODS: A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated. RESULTS: Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram. CONCLUSION: The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment.

Evaluation of standard breast ultrasonography by adding two-dimensional and three-dimensional shear wave elastography: a prospective, multicenter trial.

OBJECTIVE: To reduce the number of biopsies performed on benign breast lesions categorized as BI-RADS 4-5, we investigated the diagnostic performance of combined two-dimensional and three-dimensional shear wave elastography (2D + 3D SWE) with standard breast ultrasonography (US) for the BI-RADS assessment of breast lesions. METHODS: A total of 897 breast lesions, categorized as BI-RADS 3-5, were subjected to standard breast US and supplemented by 2D SWE only and 2D + 3D SWE analysis. Based on the malignancy rate of less than 2% for BI-RADS 3, lesions assessed by standard breast US were reclassified with SWE assessment. RESULTS: After standard breast US evaluation, 268 (46.1%) participants underwent benign biopsies in BI-RADS 4-5 lesions. By using separated cutoffs for upstaging BI-RADS 3 at 120 kPa and downstaging BI-RADS 4a at 90 kPa in 2D + 3D SWE reclassification, 123 (21.2%) participants underwent benign biopsy, resulting in a 54.1% reduction (123 versus 268). CONCLUSION: Combining 2D + 3D SWE with standard breast US for reclassification of BI-RADS lesions may achieve a reduction in benign biopsies in BI-RADS 4-5 lesions without sacrificing sensitivity unacceptably. CLINICAL RELEVANCE STATEMENT: Combining 2D + 3D SWE with US effectively reduces benign biopsies in breast lesions with categories 4-5, potentially improving diagnostic accuracy of BI-RADS assessment for patients with breast lesions. TRIAL REGISTRATION: ChiCTR1900026556 KEY POINTS: • Reduce benign biopsy is necessary in breast lesions with BI-RADS 4-5 category. • A reduction of 54.1% on benign biopsies in BI-RADS 4-5 lesions was achieved using 2D + 3D SWE reclassification. • Adding 2D + 3D SWE to standard breast US improved the diagnostic performance of BI-RADS assessment on breast lesions: specificity increased from 54 to 79%, and PPV increased from 54 to 71%, with slight loss in sensitivity (97.2% versus 98.7%) and NPV (98.1% versus 98.7%).

Risk factor analysis and prediction model for papillary thyroid carcinoma with lymph node metastasis.

Objective: We aimed to identify the clinical factors associated with lymph node metastasis (LNM) based on ultrasound characteristics and clinical data, and develop a nomogram for personalized clinical decision-making. Methods: A retrospective analysis was performed on 252 patients with papillary thyroid carcinoma (PTC). The patient's information was subjected to univariate and multivariate logistic regression analyses to identify risk factors. A nomogram to predict LNM was established combining the risk factors. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curve, calibration curve, cross-validation, decision curve analysis (DCA), and clinical impact curve. Results: There are significant differences between LNM and non-LNM groups in terms of age, sex, tumor size, hypoechoic halo around the nodule, thyroid capsule invasion, lymph node microcalcification, lymph node hyperechoic area, peak intensity of contrast (PI), and area under the curve (AUC) of the time intensity curve of contrast (P<0.05). Age, sex, thyroid capsule invasion, lymph node microcalcification were independent predictors of LNM and were used to establish the predictive nomogram. The ROC was 0.800, with excellent discrimination and calibration. The predictive accuracy of 0.757 and the Kappa value was 0.508. The calibration curve, DCA and calibration curve demonstrated that the prediction model had excellent net benefits and clinical practicability. Conclusion: Age, sex, thyroid capsule invasion, and lymph node microcalcification were identified as significant risk factors for predicting LNM in patients with PTC. The visualized nomogram model may assist clinicians in predicting the likelihood of LNM in patients with PTC prior to surgery.

Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System in Hepatocellular Carcinoma ≤5 cm: Biological Characteristics and Patient Outcomes.

Introduction: The present study aimed to evaluate the influence of biological characteristics of hepatocellular carcinoma (HCC) on the Liver Imaging Reporting and Data System (LI-RADS) v2017 category of contrast-enhanced ultrasound (CEUS) in patients with high risk and compare the outcomes among different categories after radical resection. Methods: Between June 2017 and December 2020, standardized CEUS data of liver nodules were prospectively collected from multiple centers across China. We conducted a retrospective analysis of the prospectively collected data on HCCs measuring no more than 5 cm, as diagnosed by pathology. LI-RADS categories were assigned after thorough evaluation of CEUS features. Then, CEUS LI-RADS categories and major features were compared in different differentiation, Ki-67, and microvascular invasion (MVI) statuses. Differences in recurrence-free survival (RFS) among different LI-RADS categories were further analyzed. Results: A total of 293 HCC nodules in 293 patients were included. This study revealed significant differences in the CEUS LI-RADS category of HCCs among differentiation (p < 0.001) and levels of Ki-67 (p = 0.01) and that poor differentiation (32.7% in LR-M, 12% in LR-5, and 6.2% in LR-4) (p < 0.001) and high level of Ki-67 (median value 30%) were more frequently classified into the LR-M category, whereas well differentiation (37.5% in LR-4, 15.1% in LR-5, and 11.5% in LR-M) and low levels of Ki-67 (median value 11%) were more frequently classified into the LR-4 category. No significant differences were found between MVI and CEUS LI-RADS categories (p > 0.05). With a median follow-up of 23 months, HCCs assigned to different CEUS LI-RADS classes showed no significant differences in RFS after resection. Conclusions: Biological characteristics of HCC, including differentiation and level of Ki-67 expression, could influence major features of CEUS and impact the CEUS LI-RADS category. HCCs in different CEUS LI-RADS categories showed no significant differences in RFS after resection.

On-Site Diagnostic Ability of CEUS/CT/MRI for Hepatocellular Carcinoma (2019-2022): A Multicenter Study.

OBJECTIVES: To compare the on-site diagnostic performance of contrast-enhanced ultrasound (CEUS), computed tomography (CECT), and magnetic resonance imaging (CEMRI) for hepatocellular carcinoma (HCC) across diverse practice settings. METHODS: Between May 2019 and April 2022, a total of 2085 patients with 2320 pathologically confirmed focal liver lesions (FLLs) were enrolled. Imaging reports were compared with results from pathology analysis. Diagnostic performance was analyzed in defined size, high-risk factors for HCC, and hospital volume categories. RESULTS: Three images achieved similar diagnostic performance in classifying HCC from 16 types of FLLs, including HCC ≤2.0 cm. For HCC diagnosis at low-volume hospitals and HCC with high-risk factors, the accuracy and specificity of CEUS were comparable to CECT and CEMRI, while the sensitivity of CEUS (77.4 and 89.5%, respectively) was inferior to CEMRI (87.0 and 92.8%, respectively). The diagnostic accuracy of CEUS + CEMRI and CEUS + CECT increased by 7.8 and 6.2% for HCC ≤2.0 cm, 8.0 and 5.0% for HCC with high-risk factors, and 7.4 and 5.5% for HCC at low-volume hospitals, respectively, compared with CEMRI/CECT alone. CONCLUSIONS: Compared with CECT and CEMRI, CEUS provides adequate diagnostic performance in clinical first-line applications at high-volume hospitals. Moreover, a higher diagnostic performance for HCC is achieved by combining CEUS with CECT/CEMRI compared with any single imaging technique.

DGANet: A Dual Global Attention Neural Network for Breast Lesion Detection in Ultrasound Images.

Deep learning-based breast lesion detection in ultrasound images has demonstrated great potential to provide objective suggestions for radiologists and improve their accuracy in diagnosing breast diseases. However, the lack of an effective feature enhancement approach limits the performance of deep learning models. Therefore, in this study, we propose a novel dual global attention neural network (DGANet) to improve the accuracy of breast lesion detection in ultrasound images. Specifically, we designed a bilateral spatial attention module and a global channel attention module to enhance features in spatial and channel dimensions, respectively. The bilateral spatial attention module enhances features by capturing supporting information in regions neighboring breast lesions and reducing integration of noise signal. The global channel attention module enhances features of important channels by weighted calculation, where the weights are decided by the learned interdependencies among all channels. To verify the performance of the DGANet, we conduct breast lesion detection experiments on our collected data set of 7040 ultrasound images and a public data set of breast ultrasound images. YOLOv3, RetinaNet, Faster R-CNN, YOLOv5, and YOLOX are used as comparison models. The results indicate that DGANet outperforms the comparison methods by 0.2%-5.9% in total mean average precision.

Safety findings after intravenous administration of sulfur hexafluoride microbubbles to 463,434 examinations at 24 centers.

OBJECTIVES: We aimed to evaluate the safety of the ultrasound contrast agent sulfur hexafluoride microbubbles in a large group of patients referred for routine contrast-enhanced ultrasound (CEUS). METHODS: A retrospective assessment was made of all patients that received sulfur hexafluoride microbubbles intravenously for CEUS at 24 centers between January 2006 and April 2019. Patient demographic details, examination type, and the dose of sulfur hexafluoride microbubbles administered were recorded with specific adverse events (AEs) documentation tools at each center. All AEs were recorded as serious or non-serious. Non-serious AEs were classified by intensity as mild, moderate, or severe according to ACR criteria. The frequencies of AEs across patient subgroups were compared using the chi-square test. RESULTS: A total of 463,434 examinations were evaluated. Overall, 157 AEs (153 [0.033%] non-serious; 4 [0.001%] serious) were reported after sulfur hexafluoride microbubbles administration, giving an AE frequency of 0.034% (157/463,434). Among the non-serious AEs, 66 (0.014%) were mild, 70 (0.015%) moderate, and 17 (0.004%) severe in intensity. The liver was the most common examination site, presenting an AE frequency of 0.026%. The highest AE frequency (0.092%) was for patients undergoing CEUS for vascular disease. There were no significant gender differences in either the total number or the severity of non-serious AEs (chi-square = 2.497, p = 0.287). The onset of AEs occurred within 30 min of sulfur hexafluoride microbubbles administration in 91% of cases. CONCLUSION: The frequency of AEs to sulfur hexafluoride microbubbles is very low and severe reactions are rare, confirming that sulfur hexafluoride microbubbles are appropriate for routine CEUS applications. KEY POINT: • The frequency of AEs to sulfur hexafluoride microbubbles is very low and severe reactions are rare.

Distinguishing Hepatocellular Carcinoma From Hepatic Inflammatory Pseudotumor Using a Nomogram Based on Contrast-Enhanced Ultrasound.

BACKGROUND: Hepatocellular carcinoma (HCC) and hepatic iflammatory pseudotumor (IPT) share similar symptoms and imaging features, which makes it challenging to distinguish from each other in clinical practice. This study aims to develop a predictive model based on contrast-enhanced ultrasound (CEUS) and clinical features to discriminate HCC from IPT. METHODS: Sixty-two IPT and 146 HCC patients were enrolled in this study, where pathological diagnosis served as the reference standard for diagnosis. Clinical and ultrasound imaging data including CEUS features: enhancement degree during arterial phase, portal phase and delayed phase, enhancement pattern, early washout within 60 s, feeding artery, peritumoral vessels, peritumoral enhancement, and margin of nonenhanced area were retrospectively collected. Imaging data were reviewed by two experienced ultrasound doctors. Patients were randomly assigned to training and validation sets. Chi-squared test followed by LASSO regression was performed on ultrasonographic features in the training set to identify the most valuable features that distinguish HCC from IPT, based on which the sonographic score formula was generated. With the significant clinical and ultrasonographic indicators, a nomogram was developed. The performance of the nomogram was verified by ROC curve and decision curve analysis (DCA) with the comparison with sonographic score and the ultrasound doctor's diagnosis. RESULTS: The most valuable ultrasonographic features that distinguish between HCC and IPT were enhancement degree during arterial phase, early washout, peritumoral vessels, peritumoral enhancement, and liver background. The sonographic score based on these features was verified to be an independent factor that predicts the diagnosis (p = 0.003). Among the clinical indicators, AFP (p = 0.009) and viral hepatitis infection (p = 0.004) were significant. Sonographic score, AFP, and viral hepatitis were used to construct a predictive nomogram. The AUC of the nomogram was 0.989 and 0.984 in training and validation sets, respectively, which were higher than those of sonographic score alone (0.938 and 0.958) or the ultrasound doctor's diagnosis (0.794 and 0.832). DCA showed the nomogram provided the greatest clinical usefulness. CONCLUSION: A predictive nomogram based on a sonographic signature improved the diagnostic performance in distinguishing HCC and IPT, which may help with individualized diagnosis and treatment in clinical practice.

Preoperative Prediction of Microvascular Invasion in Patients With Hepatocellular Carcinoma Based on Radiomics Nomogram Using Contrast-Enhanced Ultrasound.

PURPOSE: This study aimed to develop a radiomics nomogram based on contrast-enhanced ultrasound (CEUS) for preoperatively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. METHODS: A retrospective dataset of 313 HCC patients who underwent CEUS between September 20, 2016 and March 20, 2020 was enrolled in our study. The study population was randomly grouped as a primary dataset of 192 patients and a validation dataset of 121 patients. Radiomics features were extracted from the B-mode (BM), artery phase (AP), portal venous phase (PVP), and delay phase (DP) images of preoperatively acquired CEUS of each patient. After feature selection, the BM, AP, PVP, and DP radiomics scores (Rad-score) were constructed from the primary dataset. The four radiomics scores and clinical factors were used for multivariate logistic regression analysis, and a radiomics nomogram was then developed. We also built a preoperative clinical prediction model for comparison. The performance of the radiomics nomogram was evaluated via calibration, discrimination, and clinical usefulness. RESULTS: Multivariate analysis indicated that the PVP and DP Rad-score, tumor size, and AFP (alpha-fetoprotein) level were independent risk predictors associated with MVI. The radiomics nomogram incorporating these four predictors revealed a superior discrimination to the clinical model (based on tumor size and AFP level) in the primary dataset (AUC: 0.849 vs. 0.690; p < 0.001) and validation dataset (AUC: 0.788 vs. 0.661; p = 0.008), with a good calibration. Decision curve analysis also confirmed that the radiomics nomogram was clinically useful. Furthermore, the significant improvement of net reclassification index (NRI) and integrated discriminatory improvement (IDI) implied that the PVP and DP radiomics signatures may be very useful biomarkers for MVI prediction in HCC. CONCLUSION: The CEUS-based radiomics nomogram showed a favorable predictive value for the preoperative identification of MVI in HCC patients and could guide a more appropriate surgical planning.

Management of breast lesions seen on US images: dual-model radiomics including shear-wave elastography may match performance of expert radiologists.

PURPOSE: To develop a nomogram incorporating B-mode ultrasound (BMUS) and shear-wave elastography (SWE) radiomics to predict malignant status of breast lesions seen on US non-invasively. METHODS: Data on 278 consecutive patients from Hospital #1 (training cohort) and 123 cases from Hospital #2 (external validation cohort) referred for breast US with subsequent histopathologic analysis between May 2017 and October 2019 were retrospectively collected. Using their BMUS and SWE images, we built a radiomics nomogram to improve radiology workflow for management of breast lesions. The performance of the algorithm was compared with a consensus of three ACR BI-RADS committee experts and four individual radiologists, all of whom interpreted breast US images in clinical practice. RESULTS: Twelve features from BMUS and three from SWE were selected finally to construct the respective radiomic signature. The nomogram based on the dual-modal US radiomics achieved good diagnostic performance in the training (AUC 0.96; 95% confidence intervals [CI], 0.94-0.98) and the validation set (AUC 0.92; 95% CI, 0.87-0.97). For the 123 test lesions, the algorithm achieved 105 of 123 (85%) accuracy, comparable to the expert consensus (104 of 123 [85%], P =  0.86) and four individual radiologists (93, 99, 95 and 97 of 123, with P value of 0.05, 0.31, 0.10 and 0.18 respectively). Furthermore, the model also performed well in the BI-RADS 4 and 5 categories. CONCLUSIONS: Performance of a dual-model US radiomics nomogram based on SWE for breast lesion classification may comparable to that of expert radiologists who used ACR BI-RADS guideline.

Multimodal and multifunctional nanoparticles with platelet targeting ability and phase transition efficiency for the molecular imaging and thrombolysis of coronary microthrombi.

Recently, coronary microthrombosis has received attention owing to its involvement in the pathophysiological process of no-reflow after acute myocardial ischemia/reperfusion. Due to the small size of coronary microthrombi, there are no precise detection and treatment methods available in the clinic so far. In experimental study, bimodal molecular probes for both detecting and dissolving coronary microthrombi have not yet been reported. In this study, multimodal and multifunctional PLGA-cRGD-PFH-ICG NPs (PLGA: poly(lactic-co-glycolic) acid, cRGD: cyclic arginine-glycine-aspartic acid, PFH: perfluorohexane, ICG: indocyanine green, NPs: nanoparticles) were constructed through a three-step emulsification process, and the corresponding physical and chemical characteristics of the NPs were also tested. The in vitro and in vivo experiments showed that PLGA-cRGD-PFH-ICG NPs could bind to the activated platelets of coronary microthrombi through cRGD and could achieve bimodal molecular imaging (photoacoustic and near-infrared fluorescence) through ICG. Moreover, the PLGA-cRGD-PFH-ICG NPs could permeate more deeply into the thrombus than other common NPs before being triggered by low-intensity focused ultrasound (LIFU), and thrombolysis was carried out through the cavitation effect of PFH after triggering by LIFU. In summary, PLGA-cRGD-PFH-ICG NPs, constructed with safe and approved materials, serve as an excellent theranostic contrast agent that paves the way for the clinical diagnosis and treatment of coronary microthrombosis.

Improving B-mode ultrasound diagnostic performance for focal liver lesions using deep learning: A multicentre study.

BACKGROUND: The diagnosis performance of B-mode ultrasound (US) for focal liver lesions (FLLs) is relatively limited. We aimed to develop a deep convolutional neural network of US (DCNN-US) for aiding radiologists in classification of malignant from benign FLLs. MATERIALS AND METHODS: This study was conducted in 13 hospitals and finally 2143 patients with 24,343 US images were enrolled. Patients who had non-cystic FLLs with pathological results were enrolled. The FLLs from 11 hospitals were randomly divided into training and internal validations (IV) cohorts with a 4:1 ratio for developing and evaluating DCNN-US. Diagnostic performance of the model was verified using external validation (EV) cohort from another two hospitals. The diagnosis value of DCNN-US was compared with that of contrast enhanced computed tomography (CT)/magnetic resonance image (MRI) and 236 radiologists, respectively. FINDINGS: The AUC of ModelLBC for FLLs was 0.924 (95% CI: 0.889-0.959) in the EV cohort. The diagnostic sensitivity and specificity of ModelLBC were superior to 15-year skilled radiologists (86.5% vs 76.1%, p = 0.0084 and 85.5% vs 76.9%, p = 0.0051, respectively). Accuracy of ModelLBC was comparable to that of contrast enhanced CT (both 84.7%) but inferior to contrast enhanced MRI (87.9%) for lesions detected by US. INTERPRETATION: DCNN-US with high sensitivity and specificity in diagnosing FLLs shows its potential to assist less-experienced radiologists in improving their performance and lowering their dependence on sectional imaging in liver cancer diagnosis.

Incremental diagnostic value of shear wave elastography combined with contrast-enhanced ultrasound in TI-RADS category 4a and 4b nodules.

PURPOSE: To evaluate the diagnostic value of shear wave elastography (SWE) combined with contrast-enhanced ultrasonography (CEUS) in diagnosing thyroid imaging reporting and data system (TI-RADS) category 4a and 4b nodules. METHODS: TI-RADS, SWE, and CEUS features of 71 thyroid nodules (23 benign, 48 malignant) confirmed by postoperative pathological results were retrospectively analyzed. The diagnostic efficiency of each single method and that of a combination of three methods were compared. RESULTS: The sensitivity and specificity in diagnosing thyroid nodules were 70.83% and 65.22% for TI-RADS, 68.75% and 91.30% for SWE, 77.08% and 78.26% for CEUS, and 91.67% and 95.65% for TI-RADS + SWE + CEUS, respectively. The area under the curve for TI-RADS, SWE, CEUS, and TI-RADS + SWE + CEUS in diagnosing thyroid nodules were 0.680, 0.839, 0.799, and 0.937, respectively. A significant difference was observed between a combination of the three methods and any of them alone (p < 0.05). CONCLUSION: Combining SWE and CEUS improves the differential diagnosis of TI-RADS category 4a and 4b nodules.

[Anti-cicatricial and anti-restenosis effect of verapamil on anterior urethral stricture: A randomized controlled clinical trial].

OBJECTIVE: To evaluate the anti-cicatricial and anti-restenosis effect of verapamil on anterior urethral stricture.
 Methods: A total of 32 patients received anterior urethral stricture were enrolled in this study. They were divided into 4 blocks according to the duration of previous urethral operations and dilations. Every block was further randomly divided into an experimental group and a control group. Experimental groups received 2 mL injection of verapamil around the anastomosis site of urethra before and after the surgery (2, 4, 6, 8, and 10 weeks after the surgery), while the control groups only received the anastomosis surgery. After surgery, maximal urinary flow rate (Qmax) was examined for all patients once the catheter was removed. In addition, they were also conducted palpation of urethral scar range. The sum of long transverse diameters of urethral scar was measured, and the narrowest urethral inner diameter was examined. The Qmax was rechecked and the urethral scar range was assessed by penis color Doppler elastography after 12 weeks of surgery. The above 4 indexes were used to evaluate the inhibitory effect of verapamil on urethral scar.
 Results: The length of palpated urethral scar in the Block 1 to 4 of the experimental groups was (22.75±1.03), (21.25±0.25), (20.75±1.03), and (20.0±0.58) mm, respectively; and those in the control groups (26.00±0.82), (24.5±1.04), (25.75±1.65), and (28.25±1.75) mm, respectively. The Qmax rates in the Block 1 to 4 of the experimental groups were (11.85±0.77), (11.33±0.81), (10.23±0.26), and (10.35±0.17) mL/s, respectively; and those in the control groups were (10.85±0.39), (10.50±0.76), (10.53±1.00), (12.60±0.39) mL/s, respectively. The Qmax rates in the Block 1 to 4 of the experimental groups were (11.73±0.87), (10.65±0.25), (10.23±0.19), and (10.35±0.29) mL/s, respectively; and those in the control groups were (8.05±0.28), (7.73±0.68), (7.53±0.92), and (9.60±0.32) mL/s, respectively. The narrowest diameters of urethral in the Block 1 to 4 of the experimental groups were (9.00±0.58), (7.50±2.89), (7.00±0.10), and (7.00±0.41) mm, respectively; and those in the control groups were (5.50±0.29), (5.00±0.41), (4.75±0.48), and (6.75±0.48) mm, respectively. The ultrasound strain ratio in the Block 1 to 4 of the experimental groups were 6.10±0.22, 6.10±0.17, 5.10±0.16, and 6.90±0.19, respectively; and those in the control groups were 8.00±0.25, 10.60±0.29, 11.30±0.16, and 8.90±0.33, respectively. Compared with the control groups, the experimental groups displayed smaller urethral scar range, less severe scarring, improved Qmax rates and wider inner diameters (all P<0.05).
 Conclusion: Urethral regional injection of verapamil intraoperatively or postoperatively can prevent overgrowth of urethral scar tissues after the transperineal anastomosis surgery, and reduce the tendency of postoperative restenosis of anterior urethral stricture.

Predictive Value of Conventional Ultrasound and Contrast-Enhanced Ultrasound in Early Recurrence of Hepatocellular Carcinoma after Surgical Resection.

The goals of the work described here were to study the pre-operative risk factors associated with early recurrence (ER) of hepatocellular carcinoma (HCC) after surgical resection and discuss the value of conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) in predicting ER of HCC, so as to provide more information for optimizing clinical treatment and improving prognosis. A retrospective analysis was conducted on 59 patients who underwent both US and CEUS examinations pre-operatively and surgical resection for HCC between December 2010 and January 2014 in our hospital. The patients' clinical data, laboratory examination data and ultrasonic imaging diagnostic data were collected. Univariate analysis and logistic regression analysis were performed to determine the independent risk factors for ER of HCC after surgical resection. Diagnostic values of independent risk factors in predicting ER were further evaluated. The 59 patients were divided into the ER group (27 cases) and ER-free group (32 cases). There were no significant differences in age and sex between the two groups (p > 0.05). Univariate analysis revealed that differences in pre-operative serum α-fetoprotein level ≥400 ng/mL (p = 0.008), tumor diameter ≥5 cm (p = 0.012), macroscopic vascular invasion (p = 0.040), "fast wash-out" enhancement pattern (p = 0.006) and inhomogeneous distribution of contrast agent (p = 0.031) statistically significantly differed between the two groups. Logistic regression analysis indicated that pre-operative serum AFP level ≥400 ng/mL (p = 0.024), tumor diameter ≥5 cm (p = 0.042) and "fast wash-out" enhancement pattern (p = 0.009) were independent risk factors for ER of HCC; macrovascular invasion (p = 0.095) and inhomogeneous distribution of contrast agent (p = 0.628) did not statistically significantly differ between two groups (p = 0.628). Predictive values of the independent risk factors were further evaluated. The sensitivity of a "fast wash-out" enhancement pattern in predicting ER of HCC post-operatively did not statistically differ from that of tumor diameter ≥5 cm (p > 0.05), whereas it was significantly higher than the sensitivities of the other predictive indexes (p < 0.05). A pre-operative serum α-fetoprotein level ≥400 ng/mL, tumor diameter ≥5 cm and "fast wash-out" enhancement pattern are independent risk factors for ER of HCC after surgical resection. In addition, the "fast wash-out" enhancement pattern could probably be used to screen populations at high risk of recurrence owing to its high sensitivity in predicting ER of HCC post-operatively. All these findings provide beneficial information for management of HCC.

Primary thyroid lymphoma has different sonographic and color Doppler features compared to nodular goiter.

OBJECTIVES: The purpose of this study was to determine the specific sonographic features of primary thyroid lymphoma and its color Doppler pattern compared to nodular goiter. METHODS: The sonographic findings for 13 surgically proven primary thyroid lymphomas were analyzed and compared to those for 27 nodular goiters. RESULTS: In accordance with the suggested pathologic patterns, the sonographic patterns of primary thyroid lymphoma could be classified into diffuse and nodular or segmental types based on the distribution of hypoechoic and echogenic structures within the lesions. Some common sonographic characteristics suggesting thyroid malignancy could not facilitate differentiation of primary thyroid lymphoma from nodular goiter. However, a central blood flow pattern would favor the diagnosis of primary thyroid lymphoma, whereas a peripheral pattern would suggest the diagnosis of nodular goiter. CONCLUSIONS: Primary thyroid lymphoma has characteristic sonographic and Doppler flow features. Along with several other parameters, a central blood flow pattern would highly suggest the diagnosis of primary thyroid lymphoma rather than nodular goiter.

[Color Doppler flow image of Budd-Chiari syndrome].

OBJECTIVE: To evaluate the diagnostic value of color Doppler flow image (CDFI) for the diagnosis of Budd-Chiari syndrome (B-CS). METHODS: CDFI findings of 35 patients with B-CS were retrospectively analyzed and compared with the findings of venography of inferior vena cava (IVC). RESULTS: Thirty-four patients were diagnosed as B-CS by CDFI, while one patient with local tunica stenosis was misdiagnosed. The correct diagnostic rate was 97.1%. In the 34 patients, CDFI displayed stenosis or occlusion in the hepatic vein and IVC in 24 patients, IVC only in 8,and hepatic vein only in 2. CONCLUSION: CDFI may be a principal non-invasive technique to diagnose B-CS.