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    吴佳辉, 鹿皎, 卓晓英, 王荣, 王影, 王兴田. 声触诊弹性成像技术联合超声造影优化乳腺BI-RADS 4类病灶诊断的价值研究[J]. 徐州医科大学学报, 2023, 43(3): 196-200. DOI: 10.3969/j.issn.2096-3882.2023.03.008
    引用本文: 吴佳辉, 鹿皎, 卓晓英, 王荣, 王影, 王兴田. 声触诊弹性成像技术联合超声造影优化乳腺BI-RADS 4类病灶诊断的价值研究[J]. 徐州医科大学学报, 2023, 43(3): 196-200. DOI: 10.3969/j.issn.2096-3882.2023.03.008
    shu
    WU Jiahui, LU Jiao, ZHUO Xiaoying, WANG Rong, WANG Ying, WANG Xingtian. Application of sound touch elastography combined with contrast-enhanced ultrasound in optimizing the diagnosis of BI-RADS 4 breast lesions[J]. Journal of Xuzhou Medical University, 2023, 43(3): 196-200. DOI: 10.3969/j.issn.2096-3882.2023.03.008
    Citation: WU Jiahui, LU Jiao, ZHUO Xiaoying, WANG Rong, WANG Ying, WANG Xingtian. Application of sound touch elastography combined with contrast-enhanced ultrasound in optimizing the diagnosis of BI-RADS 4 breast lesions[J]. Journal of Xuzhou Medical University, 2023, 43(3): 196-200. DOI: 10.3969/j.issn.2096-3882.2023.03.008
    shu

    声触诊弹性成像技术联合超声造影优化乳腺BI-RADS 4类病灶诊断的价值研究

    Application of sound touch elastography combined with contrast-enhanced ultrasound in optimizing the diagnosis of BI-RADS 4 breast lesions

      摘要
    • 摘要: 目的 探讨声触诊弹性成像(STE)技术联合超声造影(CEUS)优化乳腺影像报告和数据系统(BI-RADS)4类病灶诊断的价值。方法 回顾性分析2020年12月—2022年6月徐州医科大学附属医院收治的91例患者共93个乳腺BI-RADS 4类病灶,术前均行常规超声、STE及CEUS检查,测量病灶(A)及其周围区域(shell 2.0 mm, S)的弹性模量值(Amean、Amax、Smean、Smax)。依据STE、CEUS预测模型优化BI-RADS分类。以病理结果为金标准绘制ROC曲线,比较STE、CEUS及两者联合优化BI-RADS分类的诊断效能。结果 93个病灶中良性病灶64个,恶性病灶29个。恶性病灶的Amean、Amax、Smean、Smax高于良性病灶,差异均有统计学意义(P均<0.05),ROC曲线显示Smax的诊断效能最高,Smax诊断截断值为106.51 kPa, Smax优化BI-RADS分类诊断的敏感度、特异度、准确度及AUC分别为75.86%、87.50%、83.87%、0.807。运用CEUS预测模型优化BI-RADS分类诊断的敏感度、特异度、准确度及AUC分别为82.76%、84.38%、83.87%、0.836。STE联合CEUS优化BI-RADS分类诊断的敏感度、特异度、准确度及AUC分别为89.66%、93.75%、92.47%、0.917,高于单独优化分类(P<0.05)。结论 STE联合CEUS优化BI-RADS分类能显著提高超声鉴别乳腺病灶良恶性的诊断效能,减少不必要的穿刺活检。

       

      Abstract: Objective To evaluate the application of sound touch elastography(STE) combined with contrast-enhanced ultrasound(CEUS) in optimizing the diagnosis of BI-RADS 4 breast lesions.Methods A total of 91 patients with 93 breast lesions in four BI-RADS types, who were admitted to the Affiliated Hospital of Xuzhou Medical University from December 2020 to June 2022 were enrolled and their clinical data were retrospectively analyzed.The patients underwent conventional ultrasound, STE and CEUS examinations.The elastic modulus of the lesion(A) and its surrounding area(shell 2.0 mm, S)were measured(Amean, Amax,Smean,and Smax).According to STE and the prediction CEUS models, the classification of BI-RADS was optimized.Then, ROC curves were plotted, using pathological results as the gold standard. The diagnostic efficiencies of STE, CEUS and both in optimizing BI-RADS classification were compared.Results Among the 93 lesions, 64 were benign and 29 were malignant. The values of Amean,Amax,Smean and Smaxin malignant lesions were higher than those in benign breast lesions, with statistical differences(all P<0.05). ROC curves showed that Smax had the highest diagnostic efficiency, at the cut-off value of 106.51 kPa. The sensitivity, specificity, accuracy and AUC of Smax in optimizing BI-RADS classification was75.86%, 87.50%, 83.87% and 0.807, respectively. The sensitivity, specificity, accuracy and AUC of CEUS in optimizing BI-RADS classification was 82.76%,84.38%,83.87% and 0.836, respectively. The sensitivity, specificity, accuracy and AUC of both STE and CEUS in optimizing BI-RADS classification was 89.66%,93.75%,92.47% and 0.917, respectively, which were higher than those of single optimized classification(P<0.05).Conclusions The optimization of BI-RADS classification by STE and CEUS can significantly improve the diagnostic efficiency of ultrasound in distinguishing benign and malignant breast lesions and avoid unnecessary puncture biopsies.

       

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