Strigel Roberta M, Burnside Elizabeth S, Elezaby Mai, Fowler Amy M, Kelcz Frederick, Salkowski Lonie R, DeMartini Wendy B
1 Department of Radiology, University of Wisconsin, 600 Highland Ave, Madison, WI 53792-3252.
2 Department of Medical Physics, University of Wisconsin, Madison, WI.
AJR Am J Roentgenol. 2017 Jun;208(6):1392-1399. doi: 10.2214/AJR.16.16730.
BI-RADS for mammography and ultrasound subdivides category 4 assessments by likelihood of malignancy into categories 4A (> 2% to ≤ 10%), 4B (> 10% to ≤ 50%), and 4C (> 50% to < 95%). Category 4 is not subdivided for breast MRI because of a paucity of data. The purpose of the present study is to determine the utility of categories 4A, 4B, and 4C for MRI by calculating their positive predictive values (PPVs) and comparing them with BI-RADS-specified rates of malignancy for mammography and ultrasound.
All screening breast MRI examinations performed from July 1, 2010, through June 30, 2013, were included in this study. We identified in medical records prospectively assigned MRI BI-RADS categories, including category 4 subdivisions, which are used routinely in our practice. Benign versus malignant outcomes were determined by pathologic analysis, findings from 12 months or more clinical or imaging follow-up, or a combination of these methods. Distribution of BI-RADS categories and positive predictive value level 2 (PPV2; based on recommendation for tissue diagnosis) for categories 4 (including its subdivisions) and 5 were calculated.
Of 860 screening breast MRI examinations performed for 566 women (mean age, 47 years), 82 with a BI-RADS category 4 assessment were identified. A total of 18 malignancies were found among 84 category 4 and 5 assessments, for an overall PPV2 of 21.4% (18/84). For category 4 subdivisions, PPV2s were as follows: for category 4A, 2.5% (1/40); for category 4B, 27.6% (8/29); for category 4C, 83.3% (5/6); and for category 4 (not otherwise specified), 28.6% (2/7).
Category 4 subdivisions for MRI yielded malignancy rates within BI-RADS-specified ranges, supporting their use for benefits to patient care and more meaningful practice audits.
乳腺钼靶摄影和超声检查的乳腺影像报告和数据系统(BI-RADS)将4类评估按恶性可能性细分为4A类(>2%至≤10%)、4B类(>10%至≤50%)和4C类(>50%至<95%)。由于数据匮乏,乳腺MRI的4类不进行细分。本研究的目的是通过计算4A、4B和4C类的阳性预测值(PPV)并将其与BI-RADS规定的乳腺钼靶摄影和超声检查的恶性率进行比较,来确定其对MRI的实用性。
本研究纳入了2010年7月1日至2013年6月30日期间进行的所有乳腺筛查MRI检查。我们在病历中确定了前瞻性分配的MRI BI-RADS类别,包括4类细分,这些在我们的实践中常规使用。通过病理分析、12个月或更长时间的临床或影像随访结果或这些方法的组合来确定良性与恶性结果。计算了BI-RADS类别的分布以及4类(包括其细分)和5类的阳性预测值水平2(PPV2;基于组织诊断建议)。
对566名女性(平均年龄47岁)进行了860次乳腺筛查MRI检查,其中82例为BI-RADS 4类评估。在84例4类和5类评估中,共发现18例恶性肿瘤,总体PPV2为21.4%(18/84)。对于4类细分,PPV2如下:4A类为2.5%(1/40);4B类为27.6%(八/二十九);4C类为83.3%(五/六);4类(未另行规定)为28.6%(2/7)。
MRI的4类细分产生的恶性率在BI-RADS规定的范围内,支持其用于患者护理并进行更有意义的实践审核。