Purpose

Category 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to < 95%. We classified category 4 lesions into three subcategories and analyzed the positive predictive value (PPV) of malignancy in a tertiary hospital.

Materials and methods

This retrospective study included 346 breast MRIs with 434 category 2–5 lesions. All enhancing lesions were classified as category 2 (0% probability of malignancy), 3 (> 0%, ≤ 2%), 4 (> 2%, < 95%) and 5 (≥ 95%); category 4 lesions were further subcategorized into 4A (> 2%, ≤ 10%), 4B (> 10%, ≤ 50%) and 4C (> 50%, < 95%) at the time of diagnosis. Radiological and pathological reports were retrospectively analyzed, and the PPVs were calculated.

Results

We included 149 malignant and 285 benign lesions. The PPVs of subcategories 4A, 4B and 4C were 1.8%, 11.8% and 67.5%, respectively. The PPVs were higher for lesions coexisting with category 5 or 6 lesions compared with those for isolated lesions.

Conclusion

Category 4 lesions can be classified into three subcategories depending on the likelihood of malignancy. Lesions coexisting with category 5 or 6 lesions are more likely to be malignant.

中文翻译：

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MRI上的乳房成像和数据系统（BI-RADS）4类病变的子类别分类。

目的

用于磁共振成像（MRI）的BI-RADS中的类别4具有广泛的恶性可能性，范围从> 2到<95％。我们将第4类病变分为三个子类别，并分析了三级医院恶性肿瘤的阳性预测值（PPV）。

材料和方法

这项回顾性研究包括346例MRI，共434个2-5类病变。所有增强病灶分为2类（恶性可能性为0％），3类（> 0％，≤2％），4类（> 2％，<95％）和5类（≥95％）；在诊断时，第4类病变进一步分为4A（> 2％，≤10％），4B（> 10％，≤50％）和4C（> 50％，<95％）。回顾性分析放射和病理报告，并计算PPV。

结果

我们纳入了149例恶性和285例良性病变。子类别4A，4B和4C的PPV分别为1.8％，11.8％和67.5％。与单独的病变相比，与5或6类病变共存的PPV更高。

结论

根据恶性肿瘤的可能性，第4类病变可分为三个亚类。与5或6类病变并存的病变更可能是恶性的。