摘要
目的:探讨乳腺影像报告与数据系统(BI-RADS)在乳腺肿块X线诊断中的应用价值。方法:选取我院2010年1月—2013年1月接受数字乳腺X线检查发现的肿块且行手术活检的患者170例175灶,均为女性,平均年龄(46.30±8.53)岁。应用ACR BI-RADS标准评价分类,与术后病理结果进行对照分析其阳性预测值(PPV)。结果:175个肿块术后病理诊断:良性103灶,恶性72灶。X线表现为单纯肿块128灶,其中恶性病灶占32.03%(41/128)。肿块伴钙化47灶,其中恶性占65.96%(31/47)。良性肿块病灶形态、边缘、密度分别以卵圆形40.6%(71/175)、遮蔽状26.3%(46/175)、等密度53.1%(93/175)居多,恶性病变以不规则29.8%(52/175)、模糊20.6%(36/175)、高密度24.6%(43/175)为主。X线诊断BI-RADS 2、3类29灶,BI-RADS 4(a、b、c)、5类共计146灶。良性诊断符合率为100%(29/29),PPV 49.32%。结论:应用BI-RADS对乳腺X线影像发现的肿块进行评估可有效地预测肿块病变的良、恶性。
Abstract
Objective: To investigate the application value of breast imaging reporting and data system(BI-RADS) in mammography. Methods: One hundred and seventy patients with 175 masses were discovered by digital mammography and confirmed by surgical, biopsy and pathology from January 2010 to January 2013. All patients were female, the average age was 46.30±8.53 years old. ACR BI-RADS standard was used for classification. Correlation of the images with pathologic results were carried out and the positive predictive value(PPV) was analyzed. Results: In the 175 masses, pathologic diagnosis after operation: benign lesions n=103, malignant lesions n=72. On X-ray, appearances of simple mass n=128, among which 32.3%(41/128) were malignant, masses with calcification n=47, among which 65.96%(31/47) were malignant. Benign lesion appeared oval in shape 40.6%(71/175), obscured margin 26.3%(45/175), isodensity 53.1%(93/175). Malignant lesions mainly appeared as irregular in shape 29.8%(52/175), ill defined border 20.6%(36/175), hyperdensity 24.6%(43/175). X-ray diagnosis by BI-RADS 2, 3 in 29 lesions, BI-RADS 4(a, b, c) and 5 in 146 lesions. Accuracy rate of benign lesion was 100%(29/29). PPV was 49.32%. Conclusion: Application of BI-RADS can effectively evaluating and predicting benign and malignant masses discovered by mammography.
关键词
乳腺肿瘤 /
乳房X线摄影术
Key words
Breast neoplasms /
Mammography
于代友;刘秀梅;康 鹏;陈 雯;于 洁.
BI-RADS在乳腺肿块X线诊断中的应用价值[J]. 中国临床医学影像杂志. 2014, 25(9): 615-618
YU Dai-you;LIU Xiu-mei;KANG Peng;CHEN Wen;YU Jie.
Application value of BI-RADS in mammography[J]. Journal of China Clinic Medical Imaging. 2014, 25(9): 615-618
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