246例乳腺影像报告和数据系统3级评分乳腺病变ER、PR和C-erbB-2表达的临床分析

目的通过对246例乳腺影像报告和数据系统(Breast Imaging Reporting and Data System,BIRADS)3级乳腺肿块的病理、雌激素受体(ER)、孕激素受体(PR)、乳腺癌原癌基因(C-erb B-2)的表达水平进行研究统计,为BI-RADS 3级乳腺肿块是否需要手术活检或治疗提供依据。方法特选取行乳腺B超或高频X线检查BI-RADS 3级有可触及乳腺肿块或局限性增厚腺体,同时进行空芯针穿刺活检的女性患者246例(共246个肿块),对所有标本进行组织病理学检查及ER、PR、Cerb B-2检查。分析患者的影像学结果及其与病理免疫组织化学部分重要指标的关系。结果由病理结果可知,246例乳腺肿块中纤维腺瘤125例,囊肿30例,乳腺癌17例,乳管内乳头状瘤23例,腺病31例,导管扩张症20例。恶性率为6.91%。影像学表现肿块最大径≤20 mm者,其免疫组织化学指标PR阳性率高,统计学上有意义(P<0.05)。影像表现中肿块内有点状钙化,其免疫组织化学指标C-erb B-2、ER阳性率高,统计学上有意义(P<0.05)。结论本研究发现BI-RADS 3级乳腺病变存在恶性率为6.91%,所以影像表现肿块内点状钙化者或肿块最大径≥20 mm的肿块,需积极手术活检或治疗。     

2013版BI-RADS分类标准结合声触诊组织量化技术鉴别诊断乳腺良恶性病灶的价值

目的 探讨2013版超声乳腺影像报告和数据系统(BI-RADS)分类诊断标准结合声触诊组织量化技术(VTQ)鉴别乳腺良恶性病灶的价值。方法 对251位患者共334个乳腺病灶行常规超声检查,并用BI-RADS分类诊断标准判断其良恶性;然后应用VTQ技术测量病灶的剪切波速度(SWV);以病理结果作为金标准,构建受试者的工作特征曲线,比较两种方法的诊断价值。结果 BI-RADS分类诊断标准及VTQ技术鉴别乳腺良恶性病灶的ROC曲线下面积分别为0.899、0.855,两者差异无统计学意义(z=1.367,P=0.172)。结论 BI-RADS分类诊断标准与VTQ技术结合可以提高乳腺病灶的诊断准确性。对于BI-RADS 4类的病灶,联合VTQ技术可减少不必要的穿刺活检或手术。     

乳腺结节超声BI-RADS分类3~5类的量化评分研究

目的探讨基于超声BI-RADS分类的量化评分方法在乳腺结节良恶性风险评估中的应用价值。方法回顾性分析486个最大直径>1 cm的乳腺结节,将其超声征象与患者年龄作为评分指标并进行赋值,计算每个结节的总分并根据设定的BI-RADS 3~5类的分值界限进行BI-RADS分类。绘制ROC曲线,寻找最佳诊断分值界限。结果 486个乳腺结节中良性结节368个,恶性结节118个。ROC曲线下面积为0.952,以总分9分作为诊断界值,其灵敏度、特异度、准确度分别为91.52%、83.69%、85.60%。BI-RADS 3、4a、4b、4c、5类的恶性构成比分别为0%、8.06%、29.09%、65.22%、92.54%。结论基于乳腺结节超声BI-RADS分类的量化评分方法可行性大,对常规超声下乳腺结节的良恶性风险评估有较高的准确度,有助于BI-RADS分类的推广应用。     

乳腺小肿块超声BI-RADS分级的临床应用价值

目的：探讨超声乳腺影像报告和数据系统(BI-RADS)分级在乳腺小肿块临床诊断中的应用价值。方法收集2011年5月至2013年12月间于我院外科行手术治疗的113例乳腺小肿块(长径≤2 cm)高频多普勒彩色超声BI-RADS分级资料,比较BI-RADS 3~5级间的病灶在超声特征上的差异,并分析其与病理诊断间的关系。结果 BI-RADS 3~5级患者共99例。术后病理证实,21例BI-RADS 3级病灶中良性肿瘤20例,恶性肿瘤1例;41例BI-RADS 4级病灶中良性肿瘤10例,恶性肿瘤31例;37例BI-RADS 5级病灶中良性肿瘤3例,恶性肿瘤34例。不同分级病变在病灶边缘、边界、回声、周围组织改变、病灶内血管生成、血流阻力指数间差异均有统计学意义(P<0.05)。超声BI-RADS分级诊断乳腺恶性肿瘤的阳性预测值为83.33%、灵敏度为98.48%、特异度为60.61%、ROC曲线下面积为0.901。结论超声BI-RADS分级诊断乳腺恶性小肿块的准确性较高,在乳腺恶性肿瘤的早期诊断和治疗指导中具有重要的临床应用价值。     

Effect of Training on Qualitative Mammographic Density Assessment

PurposeThe aim of this study was to evaluate the accuracy of visual mammographic breast density assessment and determine if training can improve this assessment, to compare the accuracy of qualitative density assessment before and after training with a quantitative assessment tool, and to evaluate agreement between qualitative and quantitative density assessment methods.MethodsConsecutive screening mammograms performed over a 4-month period were visually assessed by two study breast radiologists (the leads), who selected 200 cases equally distributed among the four BI-RADS density categories. These 200 cases were shown to 20 other breast radiologists (the readers) before and after viewing a training module on visual density assessment. Agreement between reader assessment and lead radiologist assessment was calculated for both reading sessions. Quantitative volumetric density of the 200 mammograms, determined using a commercially available tool, was compared with both sets of reader assessment and with lead radiologist assessment.ResultsCompared with lead radiologist assessment, reader accuracy of breast density assessment increased from 65% before training to 72% after training (odds ratio, 1.41; P < .0001). Training specifically improved assignment to BI-RADS categories 1 (P < .0001) and 4 (P < .10). Compared with quantitative assessment, reader accuracy showed statistically nonsignificant improvement with training (odds ratio, 1.1; P = .26). Substantial agreement between qualitative and quantitative breast density assessment was demonstrated (κ = 0.78).ConclusionsTraining may improve the accuracy of mammographic breast density assessment. Substantial agreement between qualitative and quantitative breast density assessment exists.     

Computer aided classification system for breast ultrasound based on Breast Imaging Reporting and Data System (BI-RADS)

Clinically, the ultrasound findings are evaluated by its sonographic characteristics and then assigned to assessment categories according to the definitions of Breast Imaging Reporting and Data System (BI-RADS) developed by the American College of Radiology. In this study, a computer-aided classification (CAC) system was proposed to classify the masses into assessment categories 3, 4 and 5, which simulated the clinical diagnosis of radiologists. Compared with current computer-aided diagnosis systems, the proposed CAC system classifies the indeterminate cases into BI-RADS category 4 for further diagnosis. Six hundred twenty-six cases were collected from three ultrasound systems and confirmed by pathology and retrospectively classified into categories 3, 4 and 5 by radiologists. The multinomial logistic regression model was trained as the CAC system for predicting the assessment category from the computerized BI-RADS features and from a set of machine-dependent factors. By using the machine-dependent factors to indicate the adopted ultrasound systems, the same regression model could be applied for the cases acquired from different ultrasound systems. A basic CAC system was trained by using the classification result of radiologists. A weighted CAC system, to improve the capacity of the basic CAC system in differentiating benign from malignant lesions, was trained by adding the pathologic result. Between the radiologists and the basic CAC system, a substantial agreement was indicated by Cohen's kappa statistic and the differences in either the performance indices or the A(Z) of receiver operating characteristic (ROC) analysis were not statistically significant. For the weighted CAC system, the performance indices accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 73.00% (457 of 626), 98.17% (215 of 219), 59.46% (242 of 407), 56.58% (215 of 380) and 98.37% (242 of 246), respectively; the A(Z) was 0.94; and the correlation with the radiologists was also substantial agreement. The indices accuracy and specificity of weighted CAC system, compared with those of the radiologists, were improved by 5.91% and 8.85%, respectively and the indices of sensitivity and NPV, compared with those of a conventional CAD system, were improved by 10.5% and 5.21%, respectively; all improvements were statistically significant. To classify the mass into BI-RADS assessment categories by the CAC system is feasible. Moreover, the proposed CAC system is flexible because it can be used to diagnose the cases acquired from different ultrasound systems.     

乳腺疾病超声与钼靶 X线诊断回顾性分析

目的：探讨超声、钼靶X线在乳腺疾病中的诊断价值。方法回顾性分析102例患者超声及钼靶影像资料,并且以临床病理结果作为对照标准。结果乳腺疾病超声诊断符合率87．3％,X线钼靶诊断符合率84．3％,两者联合应用诊断符合率92．2％。结论超声与钼靶对乳腺疾病诊断均有较大价值,乳腺超声可作为乳腺疾病普查首选方法,两者联合应用可提高乳腺疾病诊断符合率。     

Shear wave elastography contribution in ultrasound diagnosis management of breast lesions

PurposeTo determine the diagnosis performance of shear wave elastography in the differentiation of benign and malignant breast lesions and the factors influencing the elasticity values. To suggest an appropriate management of breast lesions using the ultrasound-elastography combination.Patients and methodsMonocentric retrospective study of 167 breast lesions classified by conventional ultrasound as BI-RADS category 3 or higher that underwent an elastography study and histological analysis.ResultsThe analysis of qualitative parameters, according to the classification established in this study, allows us to obtain a sensitivity of 91.1% and a specificity of 92.3%. These values are very close to or better than the quantitative parameters Emax and Emean. Different Emax thresholds values were established based on the long axis of the lesion and its palpable character, which appeared to be significant factors influencing elasticity. The management of breast lesions by combining ultrasound and elastography, as proposed here, allows us to keep the sensitivity of an ultrasound (96%), while doubling its specificity (86.2% versus 43.1%).ConclusionWith the complementary nature of their performance, the combination of conventional ultrasound and shear wave elastography can improve the management of breast lesions. The qualitative classification proposed appears to be relevant assistance in lesion characterization.     

超声引导下麦默通旋切术在BI-RADS3级临床触诊阴性乳腺病灶中的临床应用价值

目的探讨B超引导下麦默通旋切术在BI-RADS 3级临床触诊阴性乳腺病灶中的临床应用价值。方法175例临床触诊阴性的乳腺肿瘤患者,BI-RADS分级为3级的肿块共425个,分析其手术时间、术后并发症、术后复发、≥35岁及<35岁不同年龄段的病理结果、恶性率等。结果425个临床触诊阴性病灶均被完全切除,平均手术时间小于15 min。术后病理结果显示,良性病灶共405个(95.29%),恶性病灶共6个(1.41%),癌前病变共14个(3.29%);术后出现瘀斑4例(2.29%),局部血肿2例(1.14%);术后随访1年,其中3人局部复发(1.71%)。≥35岁患者103例,其中乳腺癌有5例(4.84%),不典型增生有4例(3.88%),良性乳腺疾病患者有94例(91.3%);<35岁患者72例,其中乳腺癌为0(0%),不典型增生有2例(2.78%),良性乳腺疾病患者有70例(97.2%)。结论超声引导下麦默通旋切术可对BI-RADS 3级临床触诊阴性的乳腺病灶进行早期诊治,且美观、微创、安全,值得推广应用;≥35岁患者推荐微创手术活检以早期诊断及降低乳腺癌漏诊率。