Ng Wei Lin, Rahmat Kartini, Fadzli Farhana, Rozalli Faizatul Izza, Mohd-Shah Mohammad Nazri, Chandran Patricia Ann, Westerhout Caroline Judy, Vijayananthan Anushya, Abdul Aziz Yang Faridah
From the Department of Biomedical Imaging (WLN, KR, FF, FIR, MNM-S, CJW, AV, YFA), and Department of Pathology (PAC), Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
Medicine (Baltimore). 2016 Mar;95(12):e3146. doi: 10.1097/MD.0000000000003146.
The purpose of this study was to investigate the diagnostic efficacy of shearwave elastography (SWE) in differentiating between benign and malignant breast lesions.One hundred and fifty-nine lesions were assessed using B-mode ultrasound (US) and SWE parameters were recorded (Emax, Emean, Emin, Eratio, SD). SWE measurements were then correlated with histopathological diagnosis.The final sample contained 85 benign and 74 malignant lesions. The maximum stiffness (Emax) with a cutoff point of ≥ 56.0 kPa (based on ROC curves) provided sensitivity of 100.0%, specificity of 97.6%, positive predictive value (PPV) of 97.4%, and negative predictive value (NPV) of 100% in detecting malignant lesions. A cutoff of ≥80 kPa managed to downgrade 95.5% of the Breast Imaging-Reporting and Data System (BI-RADS) 4a lesions to BI-RADS 3, negating the need for biopsy. Using a combination of BI-RADS and SWE, the authors managed to improve the PPV from 2.3% to 50% in BI-RADS 4a lesions.SWE of the breast provides highly specific and sensitive quantitative values that are beneficial in the characterization of breast lesions. Our results showed that Emax is the most accurate value for differentiating benign from malignant lesions.
本研究的目的是探讨剪切波弹性成像(SWE)在鉴别乳腺良恶性病变中的诊断效能。使用B型超声(US)对159个病变进行评估,并记录SWE参数(Emax、Emean、Emin、Eratio、SD)。然后将SWE测量结果与组织病理学诊断结果进行关联。最终样本包含85个良性病变和74个恶性病变。基于ROC曲线,最大硬度(Emax)截断点≥56.0 kPa时,检测恶性病变的灵敏度为100.0%,特异度为97.6%,阳性预测值(PPV)为97.4%,阴性预测值(NPV)为100%。≥80 kPa的截断值可将95.5%的乳腺影像报告和数据系统(BI-RADS)4a类病变降级为BI-RADS 3类,无需进行活检。通过结合BI-RADS和SWE,作者将BI-RADS 4a类病变的PPV从2.3%提高到了50%。乳腺SWE提供了高度特异和敏感的定量值,有助于乳腺病变的特征性诊断。我们的结果表明,Emax是鉴别乳腺良恶性病变最准确的值。