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目的分析MRI的乳腺影像报告和数据系统(breast imaging reporting and data system,BI-RADS-MRI)4类病例乳腺癌阳性预测值(positive predictive value,PPV),初步探讨其亚分类。方法回顾性总结BI-RADS-MRI4类286例患者的MRI资料,以病理及随访结果为金标准,统计该类病例活检率及PPV,并用Logistic回归法分析各征象的PPV和优势比(OR)。结果 BI-RADS-MRI 4类活检率为75.5%,PPV为30.6%。不规则型肿块呈不均匀强化,平台型或流出型曲线的PPV为0.56;毛刺肿块,强化均匀的PPV为0.45;圆形/椭圆形肿块,边缘光滑,强化均匀的PPV为0.11。病灶呈导管/段样分布、不均匀强化的PPV为0.35;病灶呈局灶/区域/广泛分布、强化均匀的PPV为0.22。结论 PPV能初步对BI-RADS-MRI 4类行亚分类,但仍需进一步研究。
Objective To analyze the positive predictive value (PPV) of breast cancer in 4 cases of MRI imaging and breast imaging reporting and data system (BI-RADS-MRI). Methods The MRI data of 286 patients with BI-RADS-MRI4 were retrospectively reviewed. The biopsy rate and PPV were calculated by pathology and follow-up. The PPV and odds ratio (OR) of each symptom were analyzed by Logistic regression ). Results The BI-RADS-MRI 4 biopsy rate was 75.5% and PPV was 30.6%. The irregular mass showed a non-uniform enhancement with a PPV of 0.56 for the plateau or outflow curve; the spicule mass showed an even PPV of 0.45; the round / oval mass had a smooth edge and a uniform PPV of 0.11. The lesions showed a catheter / segment-like distribution with an uneven enhancement PPV of 0.35; the lesions were focal / regional / extensive with a uniform PPV of 0.22. Conclusions PPV can preliminarily classify BI-RADS-MRI into 4 categories, but further study is needed.