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Screening MRI in Women With a Personal History of Breast Cancer.对有乳腺癌个人病史的女性进行 MRI 筛查。
J Natl Cancer Inst. 2016 Jan 7;108(3). doi: 10.1093/jnci/djv349. Print 2016 Mar.
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Breast Biopsies Under Magnetic Resonance Imaging Guidance: Challenges of an Essential but Imperfect Technique.磁共振成像引导下的乳腺活检:一项重要但不完善技术的挑战
Curr Probl Diagn Radiol. 2016 May-Jun;45(3):193-204. doi: 10.1067/j.cpradiol.2015.07.002. Epub 2015 Jul 10.
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Subcategorization of Suspicious Breast Lesions (BI-RADS Category 4) According to MRI Criteria: Role of Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging.根据MRI标准对可疑乳腺病变(BI-RADS 4类)进行亚分类:动态对比增强成像和扩散加权成像的作用
AJR Am J Roentgenol. 2015 Jul;205(1):222-31. doi: 10.2214/AJR.14.13834.
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Auditing a breast MRI practice: performance measures for screening and diagnostic breast MRI.乳腺磁共振成像(MRI)实践审计:筛查和诊断性乳腺MRI的性能指标
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Importance of a personal history of breast cancer as a risk factor for the development of subsequent breast cancer: results from screening breast MRI.乳腺癌个人史作为发生后续乳腺癌风险因素的重要性:筛查性乳腺 MRI 的结果。
AJR Am J Roentgenol. 2014 Feb;202(2):289-92. doi: 10.2214/AJR.13.11553.
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Positive predictive value of BI-RADS MR imaging.BI-RADS MR 成像的阳性预测值。
Radiology. 2012 Jul;264(1):51-8. doi: 10.1148/radiol.12110619. Epub 2012 May 15.
8
Breast MRI screening of women with a personal history of breast cancer.具有乳腺癌个人史的女性的乳房 MRI 筛查。
AJR Am J Roentgenol. 2010 Aug;195(2):510-6. doi: 10.2214/AJR.09.3573.
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The positive predictive value of BI-RADS microcalcification descriptors and final assessment categories.BI-RADS 微钙化描述符和最终评估类别阳性预测值。
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Clinical implications of subcategorizing BI-RADS 4 breast lesions associated with microcalcification: a radiology-pathology correlation study.BI-RADS 4 级伴微钙化乳腺病变的亚分类的临床意义:一项放射科-病理相关性研究。
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乳腺影像报告和数据系统(BI-RADS)4类细分在乳腺磁共振成像筛查中的应用

Utility of BI-RADS Assessment Category 4 Subdivisions for Screening Breast MRI.

作者信息

Strigel Roberta M, Burnside Elizabeth S, Elezaby Mai, Fowler Amy M, Kelcz Frederick, Salkowski Lonie R, DeMartini Wendy B

机构信息

1 Department of Radiology, University of Wisconsin, 600 Highland Ave, Madison, WI 53792-3252.

2 Department of Medical Physics, University of Wisconsin, Madison, WI.

出版信息

AJR Am J Roentgenol. 2017 Jun;208(6):1392-1399. doi: 10.2214/AJR.16.16730.

DOI:10.2214/AJR.16.16730
PMID:28792802
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5600516/
Abstract

OBJECTIVE

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.

MATERIALS AND METHODS

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.

RESULTS

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).

CONCLUSION

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.

摘要

目的

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。

材料与方法

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)。

结果

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)。

结论

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。