Background:Primary breast lymphoma (PBL) is a rare extranodal lymphoma of which diagnosis is challenging due to overlapping clinical and imaging features with breast carcinoma. While the existence of PBL is known, the diagnostic significance of specific sonographic patterns like the "grid-like echo" and the critical imperative for exhaustive systemic staging to differentiate primary from systemic lymphoma warrant emphasis. This case is unique as it demonstrates a diagnostic journey from a bilateral "grid-like echo" on ultrasound to a revised diagnosis of a systemic, high-grade lymphoma, highlighting key pitfalls and the necessity of comprehensive workup. Case Description:A 38-year-old female presented with systemic symptoms. Bilateral breast ultrasound revealed Breast Imaging-Reporting and Data System (BI-RADS) 4 lesions with a distinctive "grid-like echo" pattern, well-defined hypoechoic masses, and rich vascularity. Core needle biopsy confirmed a high-grade B-cell lymphoma. However, comprehensive staging-including bone marrow biopsy, cytogenetics, and positron emission tomography-computed tomography (PET-CT)-revealed widespread disease, a t(8;14) translocation, MYC rearrangement, and multifocal extranodal involvement. The final diagnosis was revised to systemic Burkitt-like lymphoma with 11q aberration, Ann Arbor Stage IV B. The patient received systemic chemotherapy, resulting in symptomatic improvement and resolution of breast lesions on follow-up. Conclusions:While ultrasonography holds significant value in detecting and suggesting PBL, definitive diagnosis depends entirely on pathological evidence acquired through surgical biopsy. The cornerstone of treatment is systemic chemotherapy, and radical surgical resection does not improve patient survival. Therefore, the indispensable role of surgery lies in its diagnostic, not therapeutic, capacity. Enhancing awareness of PBL and establishing a multidisciplinary diagnostic model that integrates surgery, ultrasonography, pathology, and clinical practice is essential to avoid misdiagnosis and develop individualized treatment strategies.

End-stage renal disease (ESRD) is a severe kidney disorder; kidney ultrasound, as a non invasive diagnostic tool, is widely used in its clinical diagnosis. However, due to the morphological changes caused by ESRD, such as kidney shrinkage, cortical thinning, and increased echogenicity, traditional ultrasound image segmentation and diagnosis still face significant challenges. To improve segmentation accuracy and diagnostic performance, this paper proposes a multi-task learning-based approach for ultrasound kidney segmentation and auxiliary diagnosis. The method combines the classical UNet architecture with the advanced RKAN-ResNet34 encoder and incorporates an improved Convolutional Block Attention Module (CBAM), which integrates edge attention and deformable convolutions, to address the issues of blurred boundaries and morphological changes in kidney images. By jointly optimizing segmentation and classification tasks, the model simultaneously enhances both kidney segmentation accuracy and auxiliary diagnostic performance. Experimental results show that the proposed method achieves a Dice coefficient of 0.9233 and an IoU of 0.8592 for segmentation, along with an accuracy of 98.64% and an F1 score of 0.9882 for auxiliary diagnosis, outperforming existing methods. This study provides an effective solution for the automation of the ultrasound kidney image segmentation and diagnosis, contributing to the auxiliary diagnosis of end-stage renal disease.

The purpose of this study was to investigate the effects of tissue fibrosis and microvessel density on shear wave–based ultrasound elastography (SWUE) of chronic kidney disease (CKD). In addition, we were looking to see whether SWUE could predict stage of CKD, correlating with the histology on kidney biopsy. Renal tissue sections from 54 patients diagnosed with suspected CKD were subjected to immunohistochemistry (CD31 and CD34), and the degree of tissue fibrosis was assessed using Masson staining. Before renal puncture, both kidneys were examined using SWUE. Comparative analysis was used to assess the correlation between SWUE and microvessel density, and between SWUE and the degree of fibrosis. Fibrosis area according to Masson staining (p < 0.05) and integrated optical density (IOD) (p < 0.05) were positively correlated with CKD stage. The percentage of positive area (PPA) and IOD for CD31 and CD34 were not correlated with CKD stage (p > 0.05). When stage 1 CKD was removed, PPA and IOD for CD34 were negatively correlated with CKD stage (p < 0.05). Masson staining fibrosis area and IOD were not correlated with SWUE (p > 0.05), PPA and IOD for CD31 and CD34 were not correlated with SWUE (p > 0.05) and, finally, no correlation between SWUE and CKD stage was found (p > 0.05). The diagnostic value of SWUE for CKD staging was very low. The utility of SWUE in CKD was affected by many factors and its diagnostic value was limited. • There was no correlation between SWUE and the degree of fibrosis, or between SWUE and microvessel density among patients with CKD. • There was no correlation between SWUE and CKD stage and the diagnostic value of SWUE for CKD staging was very low. • The utility of SWUE in CKD is affected by many factors and its value was limited.

Background: Shear wave elastography ultrasound (SWE) is an emerging non-invasive candidate for assessing kidney stiffness. However, its prognostic value regarding kidney injury is unclear. Methods: A prospective cohort was created from kidney biopsy patients in our hospital from May 2019 to June 2020. The primary outcome was the initiation of renal replacement therapy or death, while the secondary outcome was eGFR < 60 mL/min/1.73 m2. Ultrasound, biochemical, and biopsy examinations were performed on the same day. Radiomics signatures were extracted from the SWE images. Results: In total, 187 patients were included and followed up for 24.57 ± 5.52 months. The median SWE value of the left kidney cortex (L_C_median) is an independent risk factor for kidney prognosis for stage 3 or over (HR 0.890 (0.796–0.994), p < 0.05). The inclusion of 9 out of 2511 extracted radiomics signatures improved the prognostic performance of the Cox regression models containing the SWE and the traditional index (chi-square test, p < 0.001). The traditional Cox regression model had a c-index of 0.9051 (0.8460–0.9196), which was no worse than the machine learning models, Support Vector Machine (SVM), SurvivalTree, Random survival forest (RSF), Coxboost, and Deepsurv. Conclusions: SWE can predict kidney injury progression with an improved performance by radiomics and Cox regression modeling.

Objective:To evaluate the diagnostic value of the convolution neural network model DenseNet121 based on deep learning in the diagnosis of end-stage renal disease (ESRD).Methods:In this retrospective study, 489 kidney ultrasound images of patients diagnosed with end-stage renal disease from January 1, 2019 to September 30, 2019 and 450 kidney ultrasound images of healthy controls were selected at China-Japan Friendship Hospital. The deep learning-based supervised convolutional neural network model DenseNet121 was used for network training and verification. According to whether it was end-stage renal disease or not, the prediction results of the deep learning-based model were compared with the prediction results of professional imaging physicians. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the deep learning-based model, the accuracy, specificity, sensitivity, and area under the curve (AUC) were used as metrics to compare the performance of the deep learning-based model and professional imaging physicians, and Delong was used to compare the difference of AUC.Results:The prediction accuracy of professional imaging physicians for end-stage renal disease was 89.36%, the sensitivity was 81.63%, the specificity was 97.77%, and the AUC was 0.897. The prediction accuracy of the deep learning-based convolution neural network model DenseNet121 for end-stage renal disease was 93.51%, the sensitivity was 96.12%, the specificity was 90.66%, and the AUC was 0.934. Compared with professional physicians, the DenseNet121 model had higher diagnostic ability (Z=3.034, P=0.002).Conclusion:The ultrasonic diagnosis method based on deep learning shows high diagnostic performance, and it has the potential to assist professional imaging physicians in the diagnosis of end-stage renal disease.

BACKGROUND:The incidence rate of renal disease is high, which can cause end-stage renal disease. Ultrasound is a commonly used imaging method, including conventional ultrasound, color ultrasound, elastography, etc. Machine learning is a potential method which has been widely used in clinical practices.OBJECTIVE:To compare the diagnostic performance of different ultrasonic image measurement parameters for kidney diseases, and to compare different machine learning methods with the human- reading method.METHODS:Ninety-four patients with pathologically diagnosed renal diseases and 109 normal controls were included in this study. The patients were examined by conventional ultrasound, color ultrasound and shear wave elasticity, respectively. Ultrasonic data were analyzed by Support vector machine (SVM), random forest (RF), K-nearest neighbor (KNN) and artificial neural network (ANN), respectively, and compared with the human-reading method.RESULTS:Only ultrasound elastography data have a diagnostic value for renal diseases. The accuracy of SVM, RF, KNN and ANN methods is 80.98%, 80.32%, 78.03% and 79.67%, respectively, while the accuracy of human-reading is 78.33%. In the data of machine learning ultrasound elastography, the elastic hardness parameters of the renal cortex are most important.CONCLUSION:Ultrasound elastography is of the highest diagnostic value in machine learning for nephropathy, the diagnostic efficiency of the machine learning method is slightly higher than that of the human-reading method, and the diagnostic ability of the SVM method is higher than other methods.

目的 基于剪切波弹性成像(SWE)量化参数和卷积神经网络建立深度学习(DL)模型预测肾脏病变.方法 采集94例肾脏病变患者(病例组)和109名健康人(对照组)的肾脏超声SWE量化参数.利用卷积神经网络建立DL模型,比较DL模型和支持向量机、随机森林模型预测肾脏病变的敏感度、特异度、准确率和曲线下面积(AUC).结果 DL模型对预测肾脏病变的敏感度为90.48％,特异度为100％,准确率为95.12％,AUC为0.93;支持向量机模型的敏感度、特异度、准确率和AUC分别为80.74％、80.71％、80.98％、0.90,随机森林模型分别为82.22％、77.87％、80.33％和0.88.DL模型预测敏感度、特异度、准确率和AUC均高于支持向量机和随机森林模型,与支持向量机模型和随机森林模型预测肾脏病变差异均有统计学意义(P均＜0.05).结论 基于SWE量化参数和卷积神经网络的DL模型预测肾脏疾病性能良好,具有一定临床价值.

BACKGROUND:Noninvasively predicting kidney tubulointerstitial fibrosis is important because it's closely correlated with the development and prognosis of chronic kidney disease (CKD). Most studies of shear wave elastography (SWE) in CKD were limited to non-linear statistical dependencies and didn't fully consider variables' interactions. Therefore, support vector machine (SVM) of machine learning was used to assess the prediction value of SWE and traditional ultrasound techniques in kidney fibrosis. METHODS:We consecutively recruited 117 CKD patients with kidney biopsy. SWE, B-mode, color Doppler flow imaging ultrasound and hematological exams were performed on the day of kidney biopsy. Kidney tubulointerstitial fibrosis was graded by semi-quantification of Masson staining. The diagnostic performances were accessed by ROC analysis. RESULTS:Tubulointerstitial fibrosis area was significantly correlated with eGFR among CKD patients (R = 0.450, P < 0.001). AUC of SWE, combined with B-mode and blood flow ultrasound by SVM, was 0.8303 (sensitivity, 77.19%; specificity, 71.67%) for diagnosing tubulointerstitial fibrosis (>10%), higher than either traditional ultrasound, or SWE (AUC, 0.6735 [sensitivity, 67.74%; specificity, 65.45%]; 0.5391 [sensitivity, 55.56%; specificity, 53.33%] respectively. Delong test, p < 0.05); For diagnosing different grades of tubulointerstitial fibrosis, SWE combined with traditional ultrasound by SVM, had AUCs of 0.6429 for mild tubulointerstitial fibrosis (11%-25%), and 0.9431 for moderate to severe tubulointerstitial fibrosis (>50%), higher than other methods (Delong test, p < 0.05). CONCLUSION:SWE with SVM modeling could improve the diagnostic performance of traditional kidney ultrasound in predicting different kidney tubulointerstitial fibrosis grades among CKD patients.

Objective To explore the value of elastography strain ratio(SR)combined with breast ultrasound imaging reporting and data system(BI-RADS-US)in the differential diagnosis of breast nodules.Methods A total of 471 breast nodules(from 471 patients)were reclassified by SR combined with BI-RADS-US.With the pathology results as gold standard,the area under the receiver operating characteristic(ROC)curve(AUC)was employed to evaluate the diagnostic performance,and the sensitivity,specificity,and accuracy were compared between the combined method and BI-RADS-US.Results Among the 471 breast nodules,180 nodules were benign and 291 were malignant.The AUC of the combined method was statistically significantly higher than that of BI-RADS-US(0.798 vs. 0.730;Z= 2.583, P= 0.010).SR,BI-RADS-US,and the combined method for diagnosing breast nodules had the sensitivity of 86.6%,99.0%,and 96.6%,the specificity of 67.2%,47.2%,and 63.3%,and the accuracy of 79.2%,79.2%,and 83.9%,respectively.The combined method increased the specificity from 47.2%(BI-RADS-US)to 63.3%(χ 2=14.25,P < 0.001),and downgraded 57.5%(42/73)benign nodules of BI-RADS category 4A to category 3.Conclusions SR combined with BI-RADS-US can improve the diagnostic performance for breast nodules.Especially,it can improve the specificity,avoiding unnecessary biopsy of breast nodules.

目的 探讨声脉冲辐射力(acoustic radiation force impulse,ARFI)弹性成像联合常规超声鉴别乳腺良恶性肿物的价值.方法 选取2014年1月至2020年6月就诊于中日友好医院并经病理证实的乳腺肿物患者360例,共360个肿物,术前行常规超声及ARFI成像,获得剪切波速度(shear wave velocity,SWV)值.所有肿物行乳腺影像报告与数据系统(breast imaging reporting and data system,BI-RADS)分类,并绘制 SWV值的 ROC 曲线.VTQ界值取约登指数最大时ROC曲线的值4.05 m/s,BI-RADS及联合法界值均为3～4A类,计算3种方法的AUC、敏感性、特异性、准确性、阳性预测值及阴性预测值,比较三者对乳腺肿物的诊断效能.结果 乳腺恶性肿物227个,良性133个,恶性肿物SWV值高于良性,差异有统计学意义[(6.08±2.95)m/s 比(3.16±2.14)m/s,P=0.000].常规超声、ARFI及联合法 AUC 分别为0.742、0.748、0.833,敏感性为98.7％、66.1％、90.7％,特异性为49.6％、83.5％、75.9％,准确性为80.6％、72.5％、85.3％,阳性预测值为77.0％、87.2％、86.6％,阴性预测值为95.7％、59.0％及82.8％.联合法将86.3％的病理良性4A类肿物降为3类.结论 ARFI辅助常规超声能够提高乳腺肿物诊断效能,诊断特异性提高26.3％,能够避免86.3％的病理良性4A类肿物穿刺活检.

目的 比较基于支持向量机(SVM)和传统Logistic回归法基于常规超声、彩色多普勒超声和弹性成像参数构建的多模态超声模型诊断肾脏疾病的效能.方法 收集94例肾脏疾病患者(肾病组)及无肾脏疾病的对照组患者109名,分别进行常规超声、彩色超声和剪切波弹性检查.采用Logistic回归法和SVM构建模型.利用随机数字法将全部201例患者按照3∶1分为2组,以其中153例为训练样本,进行单因素变量判断和建立SVM模型;以50例为验证样本,评价SVM模型的预测效果.结果 Logistic回归方程纳入左肾皮质弹性硬度和右肾宽度.Logistic回归模型预测肾脏疾病的准确率为83.74％,SVM模型为85.10％(x2=0.21,P=0.65).结论 多模态超声对于肾脏疾病具有较高诊断效能;SVM和Logistic模型的诊断效能相似.

Objective: The identification of neovascularization in carotid plaque in carotid artery stenosis by contrast-enhanced ultrasound (CEUS) provides other risk markers for stroke besides carotid artery stenosis -intraplaque neovascularization. Methods: From January 2017 to September 2017, 40 patients with carotid atherosclerosis plaque were examined by contrast-enhanced ultrasound in China-Japanese Friendship Hospital. The enhancement intensity (EI) measured by contrast-enhanced ultrasound was compared with the micro-vessel density (MVD) measured by histopathology after carotid endarterectomy (CEA). Contrast-enhanced ultrasound was used to observe whether there was enhancement in the plaque and the enhancement was divided into 0-2 grades. The EI in plaque, the ratio of EI in plaque to EI in carotid artery lumen were calculated by time intensity curve quantitative analysis software. Pathological sections of carotid plaques after CEA were stained with CD34 and neovascularization density was measured. Results: There were significant differences in age, EI1, EI1/EI2 and CD34 among patients with different grades of plaque enhancement (P<0.05), but no significant differences in gender and EI2 (P>0.05). The density of neovascularization obtained by CD34 staining was highly positively correlated with EI1 (r=0.836, P<0.001), EI1/EI2 (r=0.955, P<0.001), but not with age (r=0.066, P=0.684), EI2 (r=0.159, P=0.328). Conclusions: Contrast-enhanced ultrasound can observe the neovascularization in carotid plaque, which is a simple and non-invasive method to evaluate the stability of carotid plaque. CEUS may also help to extract features of vulnerable plaques, such as acute intraplaque hemorrhage.

Objective To investigate the role of 17-MHz high-frequency linear array probe in detecting the microcalcification of papillary thyroid carcinoma (PTC) and its pathological basis. Methods The clinical data of 75 patients with PTC diagnosed by ultrasonography and pathology in China-Japan Friendship Hospital from January 2016 to January 2017 were analyzed. The detection rate of microcalcification was compared between 17-MHz high-frequency ultrasound and conventional ultrasound,and the imaging findings and pathological Results were analyzed. Results Among 93 thyroid nodules,the detection rate of PTC microcalcification by 17-MHz ultrasound was 74.2% (69/93),which was significantly higher than that of conventional ultrasound (59.1%,55/93) (χ2=4.742,P=0.029). The diagnostic sensitivity,specificity,accuracy,positive predictive value,and negative predictive value of the conventional ultrasound and the 17-MHz ultrasound were 73.6% and 98.1%,60.0% and 57.5%,67.7% and 80.6%,70.9% and 75.4%,and 63.1% and 95.8%,respectively. Pathology confirmed the presence of microcalcification at 53 nodules,among which psammoma bodies were found in 10 nodules;in addition,all the psammoma bodies were located in the cell mass,whereas irregular calcium deposits were mainly in proliferated fibrous tissues. Conclusion sThe 17-MHz high-frequency ultrasound can increase the detection rate of microcalcification in thyroid nodules. The ultrasonic manifestations of microcalcification do not completely correspond to the psammoma bodies found in pathology;rather,they may represent the irregular calcium deposits on fibrous tissues.

目的 观察动脉粥样硬化兔模型内皮细胞标志物的变化及调脂通脉中药的干预作用.方法 采用高脂饲料饮食和球囊损伤颈动脉的方法复制动脉粥样硬化兔模型,随机分为正常组、模型组、假手术组、西药组(阿托伐他汀,1.1 mg/kg)和中药组(调脂通脉中药,7.3 g/kg)组,共5组,选择治疗后第6周、12周为观察点.在两个时间点,检测血脂水平;HE染色检测颈总动脉、肝脏形态学变化;ELISA检测内皮细胞标志物内皮素(ET-1)、一氧化氮合酶(eNOS)、前列环素2(PGI2)、血栓素A2(TXA2)的变化.结果 两个时间点,模型组ET-1、TXA2表达增加(P＜0.05)、eNOS、PGI2表达下降(P＜0.05).调脂通脉中药能够降低ET-1、TXA2水平(P＜0.01),且升高eNOS、PGI2表达(P＜0.05).结论 调脂通脉中药能够改善血管内皮细胞损伤,减轻动脉粥样硬化.

Objectives To investigate the efficacy of the shear wave velocity (SWV) based on acoustic radiation force impulse (ARFI) elastography in the differentiation of normal population with chronic kidney disease (CKD) and acute kidney injury (AKI) in middle aged and elderly patients.Methods Sixty-four middle aged and elderly patients referred to China-Japan Friendship Hospital and Zhejiang Provincial People's Hospital with AKI or CKD were enrolled in this study from February 2015 to December 2016 (kidney disease group).Among them,43 patients were CKD (CKD group),and 21 patients were AKI (AKI group,15 patients combined with prior CKD,6 patients without prior CKD).Twenty-nine middle aged and elderly healthy volunteers from China-Japan Friendship Hospital were enrolled at the same time (healthy control group).The SWV values of the renal middle pole cortex were acquired using the ARFI elastography.The differences of the kidney length,cortical thickness and SWV values among healthy control group,AKI and CKD group were compared by variance analysis.The LSD-t analysis was used for the advanced comparison between any two groups.The differences of cortical SWV values among healthy control group,AKI combined with prior CKD group,AKI without prior CKD group and CKD group were compared by variance analysis.The LSD-t analysis was used for the advanced comparison between any two groups.The receiver operating characteristic (ROC) curves of the cortical SWV values for diagnosing kidney disease was drawn.Results The mean cortical SWV values of healthy control group,AKI and CKD groups were (2.88±0.63),(2.42±0.83) and (2.06±0.72) m/s,respectively.The SWV values of AKI and CKD groups were significantly lower than that of healthy control group (t=2.158,P=0.033;t=5.234,P ＜ 0.001).The SWV values of CKD group were lower than that of AKI group,but there were no significant differences.The SWV values of AKI without previous CKD group and AKI combined with prior CKD group were (2.60±0.84) and (1.80±0.45) m/s,respectively.The SWV values of AKI combined with prior CKD group and CKD group were significant lower than that of healthy control group and AKI without prior CKD group (compared with healthy control group:t=2.916,P=0.004 and t=5.318,P ＜ 0.001;compared with AKI without prior CKD group:t=2.054,P=0.043 and t=-2.517,P=0.013).But there were no significant differences between AKI combined with prior CKD group and CKD group,so as to the AKI without prior CKD group and healthy control group.The cutoff value of cortical SWV for diagnosing kidney disease was 2.40 m/s,with an area under ROC curve was 0.767 (95％ CI 0.689-0.898,P=0.000).The sensitive and specificity were 57.1％ and 81.9％,respectively.Conclusions The SWV values of kidneys in middle aged and elderly CKD and AKI patients were significantly lower than those of apparently normal kidneys.The SWV values of AKI patients combined with prior CKD were lower than AKI patients without prior CKD.Determining cut-off SWV values based on ARFI elastography between normal and damaged renal parenchyma can help in the diagnosis of kidney disease in middle aged and elderly patients.

Objective To investigate the regulatory mechanism of Tiaozhi Tongmai formula on vascular remodeling related factors in rabbits with atherosclerosis.Method The rabbit model of atherosclerosis was established by high fat diet and balloon injury.54 rabbits were randomly divided into normal group, model group, sham operation group, atorvastatin group and Chinese medicine group.Except the rabbits in normal group, the remaining four groups to choose the observation point at 45 day and 90 day after treatment.At 45 days, 30 animals were observed.At 90 days, 24 animals were observed.The lumen diameter and the intima-media thickness and the peak systolic velocity was measured by ultrasound.The common carotid arteries were observed by pathology.The levels of matrix metalloproteinases (MMP-1, MMP-2), tissue inhibitor of metalloproteinase-1(TIMP-1), platelet derived endothelial cell growth factor (PD-ECGF) and uric acid was detected by enzyme-linked immunosorbent assay(ELISA).Result There are two time points, the expression levels of MMP-1, MMP-2, PD-ECGF and UA in the model group were significantly higher than those in the sham operation group (P<0.01), TIMP-1 was lower than that in sham operation group(P<0.01).The serum levels of MMP-1, MMP-2, PD-ECGF and UA in the Tiaozhi Tongma formula group was significantly lower than those in the model group(P<0.01), the level of TIMP-1 was significantly increased(P<0.01), there was no significant difference from atorvastatin group.Conclusions Tiaozhi Tongmai formula can reduced the level of MMP-1, MMP-2,PD-ECGF, UA, and increase the level of TIMP-1, therefore influence the vascular remodeling to improve atherosclerosis, this may be the mechanism of its.

目的 探讨超声对颈动脉粥样硬化(CAS)斑块性质判定的准确性及临床应用价值.方法 61例CAS斑块患者均行颈动脉超声检查及颈动脉内膜剥脱术(CEA),标本送病理分析.超声评估血管管腔直径狭窄率,斑块性质(低回声斑块、混合回声斑块、强回声斑块),并与相应的颈动脉内膜病理改变进行对照分析.结果 61例患者中,混合回声斑块34例,低回声斑块25例,强回声斑块2例.93.4％ (57/61)的斑块病理改变为脂质坏死池形成.混合回声斑块和低回声斑块的病理改变中的慢性炎细胞浸润的比例分别为42.6％(26/61)、37.7％(23/61),混合回声斑块的慢性炎细胞浸润较低回声斑块比例高.不连续性纤维帽的斑块比例(52.5％,32/61)较连续性纤维帽的斑块比例高(37.7％,23/61).钙化是强回声斑块的主要病理改变.结论 超声可直观评价CAS斑块性质.超声评价CAS斑块性质为临床诊断提供了客观依据,具有重要的应用价值.

目的:探讨不同大小嗜铬细胞瘤的超声表现,通过与病理对照分析提高对本病的超声诊断水平.方法:分析手术后经病理证实的24例患者嗜铬细胞瘤的超声诊断资料.按嗜铬细胞瘤的最大直径分为3组,即直径＜4.0cm组,4.0～6.0cm组及＞6.0cm组,分析病灶内部回声、周边及内部血流和边界的情况.结果:24例患者中3例为双侧发病,嗜铬细胞瘤病灶共27个:其中5个病灶为异位嗜铬细胞瘤(3个位于肾门部,2个位于腹主动脉或下腔静脉前方),10病灶个位于右侧肾上腺,12个病灶位于左侧肾上腺.27个病灶中有2个为恶性.不同大小病灶组之间内部回声及病灶血流情况,均具有显著性差异(P＜0.05,P＜0.01).但病灶边界情况与病灶大小无关,3组之间无显著性差异(P＞0.05).术后病理大体标本多数肿瘤界限清楚有完整包膜,切面灰褐色或棕黄色,常有出血、坏死和囊性变.镜下肿瘤细胞排列呈巢状,有富含血管的纤维组织或薄壁血窦分隔,瘤细胞多数为多角形,胞浆丰富、嗜碱性.免疫组化瘤细胞CgA(+)、肿瘤巢周支持细胞均为S-100(+).结论:随嗜铬细胞瘤肿物大小不同超声图像有所不同,嗜铬细胞瘤病理结构决定超声图像有一定的特点.

目的:探讨超声评估早期颈动脉粥样硬化危险程度的方法.方法:将49只雄性新西兰兔随机分为7组:正常组、模型组1和2、中药组1和2、西药组1和2.正常组:喂以正常饮食;模型组1和2:分别接受球囊损伤术加高脂饮食喂养6周和12周;中药组1和2:分别接受球囊损伤术、高脂饮食喂养加调脂通脉颗粒治疗6周和12周;西药组1和2:分别接受球囊损伤术、高脂饮食喂养加阿托伐他汀治疗6周和12周.超声测量各实验组兔左颈总动脉的管腔内径、内中膜厚度和收缩期峰值流速,Image-Pro-Plus 6.0计算H&E染色切片血管的内弹力膜围绕半径和最大内膜厚度百分比,评价超声测量指标与病理的对应程度,寻找一致性高且灵敏的预测疾病危险度的指标.结果:超声测量管腔内径、内中膜厚度,均未能显示出其与病理内弹力膜围绕半径和最大内膜厚度百分比相一致的变化特点;而测量收缩期峰值流速,则能够较灵敏地反映出病理内弹力膜围绕半径的变化规律.结论:超声测量收缩期峰值流速可用以评估颈动脉正性重塑的程度,从而在早期预测动脉粥样硬化的进展及危险程度.

Introduction: To determine an effective and non-invasive medical method for evaluating the severity level of extracranial internal carotid artery (ICA) stenosis by comparing the detection performances of contrast-enhanced ultrasound(CEUS) and digital subtraction angiography(DSA). Materials and methods: Thirty-two consecutive patients (7 women and 25 men; mean age: 65.0 +/- 9.4 years, range: 43-78 years) with internal carotid artery (ICA) stenosis were examined by CEUS and DSA. The studies were performed using a Hitachi Preirus ultrasound machine for CEUS and Allura Xper FD20 system (Philips Medical Systems, Nederland B.V.) for DSA. The contrast-enhancing agent used was 1.2 ml SonoVize (Bracco, Switzerland),In addition, the performances of CEUS and DSA in assessing the patency of ICA and suitability of CEA (carotid endarterectomy) were explored. Results: There was no significant difference between the distributions detected by CEUS and DSA for the four groups. The diameter stenosis percentage measured by CEUS strongly correlated with the DSA image measurements. CEUS reliably identified patients with good sensitivity and specificity at the three cut-off values of 100%, 70%, and 50%. CEUS performed better than DSA in assessing the patency of ICA and suitability of CEA. Conclusion: CEUS is an accurate non-invasive imaging test for carotid artery stenosis that is feasible tolerated in patients with different degrees of carotid stenosis.