Department of Diagnostic Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Eur J Radiol. 2012 Sep;81(9):2179-83. doi: 10.1016/j.ejrad.2011.06.043. Epub 2011 Jul 2.
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.
From October to December 2010, 208 patients were subjected to an ABVS examination in the supine position, and data were automatically sent to the ABVS workstation. Two radiologists independently evaluated 234 breast masses (148 benign and 86 malignant masses) using a unique descriptor from the 3D 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.
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, 0.71 and 0.70, respectively). Fair agreement was obtained for retraction phenomenon and lesion boundary (κ=0.54 and 0.42, respectively).
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-plane 3D US, needs to be improved.
评估使用三维超声(3D US)和乳腺影像报告和数据系统(BI-RADS)US 词汇的唯一描述符对自动乳腺容积扫描仪(ABVS)获得的乳腺超声的描述和最终评估的观察者间一致性。
2010 年 10 月至 12 月,208 例患者仰卧位接受 ABVS 检查,数据自动发送至 ABVS 工作站。两位放射科医生使用 3D US 和 BI-RADS US 词汇表的唯一描述符独立评估 234 个乳腺肿块(148 个良性肿块和 86 个恶性肿块)。两位观察者均对患者的乳腺 X 线照片、病史和病理结果不知情。观察者间一致性使用 Kappa 统计进行测量。
病变形状、方位、边界、回声模式、后方声学特征、钙化和最终评估的一致性较好(κ=0.79、0.74、0.76、0.69、0.68、0.71 和 0.70)。回缩现象和病变边界的一致性为中等(κ=0.54 和 0.42)。
ABVS 获得的乳腺超声的观察者间一致性较好,特别是对于病变形状和边界;然而,冠状面 3D US 的唯一描述符回缩现象的观察者间一致性需要改进。