摘要
第一部分：ABVS与HHUS鉴别乳腺良恶性病变诊断价值的比较
目的比较自动乳腺全容积成像技术(ABVS)与常规超声对乳腺良恶性病变的诊断价值。
方法前瞻性研究213例患者共239个乳腺病变,并与手术病理对照,分别计算自动乳腺全容积成像技术(ABVS)与常规超声的诊断敏感性、特异性、正确性、阳性预测值及阴性预测值。诊断准确性再按病变大小进一步分类评估。
结果239个乳腺病变中,良性154(64.4%)个,恶性85(35.6%)个。ABVS与常规超声对乳腺病变诊断价值的比较：敏感性(95.3%vs.90.6%),特异性(80.5%vs.82.5%),准确性(85.8%vs.85.3%),阳性预测值(73.0%vs.74.0%),及阴性预测值(93.3%vs.94.1%)。 ROC曲线下面积分别为0.948及0.928。
结论虽然ABVS与HHUS对乳腺病变的诊断准确性无明显差异,但ABVS可提供新的诊断信息。ABVS可帮助区分真正的占位性病变与不均质的片状回声区,发现恶性病变的卫星灶,及更清晰的显示导管病变。ABVS有很好的临床应用前景。
第二部分：乳腺病变ABVS超声图像的观察者间一致性研究
目的回顾性评估超声医生使用三维乳腺超声特有的术语以及超声乳腺影像报告和数据系统(BI-RADS)术语描述和诊断自动乳腺容积技术(ABVS)超声图像的观察者间一致性。
方法患者已提供知情同意书。2010年8月一12月,208位患者在仰卧位接受ABVS检查,数据自动存入ABVS工作站。2位超声医生通过ABVS工作站回顾性独立评估234个乳腺病变(病理已证实为148个良性病变和86个恶性病变)的超声图像。观察者不知道钼靶图像、病史和病理结果。通过Cohen's kappa statistic评估观察者间的差异。
结果观察者间的一致性为病变周边回声(κ=0.42)、纠集征(κ=0.54)的中等,形态(κ=0.79),纵横比(κ=0.74),边缘(κ=0.76),回声(K=0.69),后方回声(κ=0.68),钙化(κ=0.71),最终诊断(κ=0.70)的良好。
结论ABVS获取的乳腺病变超声图像评估重复性好,但病变周边回声以及冠状切面所特有的纠集征一致性中等。
Part I Differentiation of benign and malignant breast lesions:A comparison between automatically generated breast volume scans and handheld ultrasound examinations
Objective:To assess the diagnostic value of automated breast volume scanning (ABVS) or conventional handheld ultrasonography (HHUS) for the differentiation of benign and malignant breast lesions.
Materials and methods:The study prospectively evaluated239lesions in213women who were scheduled for open biopsy. The patients underwent ABVS and conventional HHUS. The sensitivity, specificity, accuracy, false positive rate, false negative rate, and positive and negative predictive values for HHUS and ABVS images were calculated using histopathological examination as the gold standard. Additionally, diagnostic accuracy was further evaluated according to the size of the masses.
Results:Among the239breast lesions studied, pathology revealed85(35.6%) malignant lesions and154(64.4%) benign lesions. ABVS was similar to HHUS in terms of sensitivity (95.3%vs.90.6%), specificity (80.5%vs.82.5%), accuracy (85.8%vs.85.3%), positive predictive value (73.0%vs.74.0%), and negative predictive value (93.3%vs.94.1%). The area under the receiver operating characteristic (ROC) curve, which is used to estimate the accuracy of the methods, demonstrated only minor differences between HHUS and ABVS (0.928and0.948, respectively).
Conclusions:The diagnostic accuracy of HHUS and ABVS in differentiating benign from malignant breast lesions is almost identical. However, ABVS can offer new diagnostic information. ABVS may help to distinguish between real lesions and inhomogeneous areas, find small lesions, and demonstrate the presence of intraductal lesions. This technique is feasible for clinical applications and is a promising new technique in breast imaging.
Part II Inter-observer Variability of Sonograms of Breast Lesions Obtained by Automated Breast Volume Scanner
OBJECTIVE:To evaluate the interobserver agreement of radiologists in the description and final assessment of breast sonograms obtained using an automated breast volume scanner (ABVS) using a unique descriptor of three-dimensional ultrasound (3D US) and the Breast Imaging Reporting and Data System (BI-RADS) US lexicon.
METHODS:From August to December2010,208patients were subjected to an ABVS examination in the supine position, and data were automatically sent to the ABVS workstation. Two radiologists independently evaluated234breast masses (148benign and86malignant masses) using a unique descriptor from the3D US and the BI-RADS US lexicon. The reviewers were blinded to the patient's mammographic images, medical history, and pathologic findings. The interobserver agreement was measured using kappa statistics.
RESULTS:Substantial agreement was obtained for lesion shape, orientation, margin, echo pattern, posterior acoustic features, calcification and final assessment (κ=0.79,0.74,0.76,0.69,0.68,0.71and0.70, respectively). Fair agreement was obtained for retraction phenomenon and lesion boundary (κ=0.54and0.42, respectively).
CONCLUSIONS:The interobserver agreement for breast sonograms obtained by ABVS is good, especially for lesion shape and margin; however, the interobserver agreement for the retraction phenomenon, which is a unique descriptor of coronal-plane3D US, needs to be improved.
引文
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