Wang Honghong, Wang Qian, Zhang Yadi, Peng Yang
Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.
Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.
Exp Ther Med. 2023 Feb 14;25(4):143. doi: 10.3892/etm.2023.11842. eCollection 2023 Apr.
The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) classification has been used for the diagnosis of breast masses for several decades and constantly updated, but the terminology used to describe breast ultrasound findings is still evolving and a great amount of large sample data is necessary to verify and improve ultrasound BI-RADS. The objective of the present study was to explore the value of ultrasound Breast Imaging Reporting and Data System (US BI-RADS) classification in the preoperative evaluation of the US-guided Mammotome-assisted minimally invasive resection of breast masses. A total of 1,028 patients with 1,341 breast masses from a single hospital were selected for retrospective analysis. All patients underwent minimally invasive resection using a US-guided Mammotome device, and postoperative pathological examinations were performed for all samples. The preoperative US BI-RADS classification and postoperative pathological examination results were compared and analyzed. A receiver operating characteristic (ROC) curve was used to analyze the preoperative evaluation efficacy of the US BI-RADS classification in US-guided Mammotome-assisted minimally invasive breast mass resection. Among the 1,341 breast masses that underwent resection, 1,307 were benign and 34 were malignant. The specificity, sensitivity, accuracy, positive predictive value and negative predictive value of the US BI-RADS classification in the preoperative diagnosis of malignant breast masses were 83.47, 100.00, 83.89, 13.60 and 100.00%, respectively, and the area under the ROC curve was 0.917. It may be concluded that the US BI-RADS classification has a good preoperative diagnostic performance and can provide an accurate assessment prior to Mammotome-assisted minimally invasive resection. It may help surgeons to make reasonable decisions for subsequent therapy and therefore is worthy of further clinical use.
美国放射学会乳腺影像报告和数据系统（BI-RADS）分类已用于乳腺肿块的诊断数十年且不断更新，但用于描述乳腺超声检查结果的术语仍在演变，需要大量的大样本数据来验证和改进超声BI-RADS。本研究的目的是探讨超声乳腺影像报告和数据系统（US BI-RADS）分类在超声引导下麦默通辅助乳腺肿块微创切除术前评估中的价值。选取一家医院的1028例患者的1341个乳腺肿块进行回顾性分析。所有患者均使用超声引导下的麦默通设备进行微创切除，并对所有样本进行术后病理检查。比较并分析术前US BI-RADS分类与术后病理检查结果。采用受试者操作特征（ROC）曲线分析US BI-RADS分类在超声引导下麦默通辅助乳腺肿块微创切除术前评估中的效能。在1341个接受切除的乳腺肿块中，1307个为良性，34个为恶性。US BI-RADS分类在乳腺恶性肿块术前诊断中的特异性、敏感性、准确性、阳性预测值和阴性预测值分别为83.47%、100.00%、83.89%、13.60%和100.00%，ROC曲线下面积为0.917。可以得出结论，US BI-RADS分类具有良好的术前诊断性能，可在麦默通辅助微创切除术前提供准确评估。它可能有助于外科医生对后续治疗做出合理决策，因此值得进一步临床应用。
