乳腺良恶性病灶超声造影预测模型在乳腺影像报告与数据系统4类乳腺病灶恶性风险评估中的应用价值

目的构建乳腺良恶性病灶超声造影预测模型，评价其在乳腺影像报告与数据系统（BI-RADS）4类乳腺病灶恶性风险评估中的应用价值。 方法2013年1月至2014年7月在四川省人民医院接受乳腺超声造影检查的230例患者，共235个乳腺实性结节。所有患者经最终穿刺活检或者手术病理结果确诊。通过对既往文献关于乳腺良恶性病灶超声造影模式的分析及本课题组的前期研究和临床经验总结，构建乳腺良恶性病灶超声造影预测模型。以穿刺活检或手术病理结果作为金标准，计算预测乳腺良恶性病灶的超声造影模型鉴别诊断乳腺良恶性病灶的敏感度、特异度、准确性。 结果本组235个乳腺结节，其中乳腺良性结节139个（59.2%），乳腺恶性结节96个（40.8%）。乳腺良恶性病灶超声造影预测模型鉴别诊断乳腺良恶性病灶的敏感度、特异度及准确性分别为87.01%、86.92%和86.99%。 结论乳腺良恶性病灶超声造影模式存在差异。乳腺良恶性病灶超声造影预测模型可以更好地评估乳腺病灶恶性风险，尤其对BI-RADS 4类乳腺病灶评估更准确。

Application value of predictive models of contrast-enhanced ultrasound in the evaluation of breast imaging reporting and data system 4 breast lesions

ObjectiveTo build breast contrast-enhanced ultrasound (CEUS) predictive models of benign and malignant lesions, and evaluate its value in malignant risk assessment. MethodsBreast CEUS predictive models of benign and malignant lesions was build depending on the analysis of published papers, conclusion of the previous study results and the clinical experience. With final pathology results as the gold standard, the predictive value was evaluated in totally 235 nodules which were classified as breast imaging reporting and data system (BI-RADS) 4. ResultsThere were 139 benign nodules (59.2%) and 96 malignant nodules (40.8%) in this study. Diagnostic sensitivity, specificity and accuracy of three malignant CEUS models and three benign CEUS models were 87.01%, 86.92% and 86.99%, respectively. ConclusionsThe contrast-enhanced patterns of benign and malignant breast tumors are different. The breast CEUS models can predict malignant risk of breast lesions more accurately, may lead to the decrease of false-positive biopsy and better BI-RADS used nowadays.