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首页> 外文期刊>AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences >BI-RADS lesion characteristics predict likelihood of malignancy in breast MRI for masses but not for nonmasslike enhancement.
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BI-RADS lesion characteristics predict likelihood of malignancy in breast MRI for masses but not for nonmasslike enhancement.

机译:BI-RADS病变特征可预测乳腺MRI肿块的恶性可能性,而非非肿块样增强的恶性可能性。

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摘要

OBJECTIVE: The purpose of our study was to evaluate the predictive features of BI-RADS lesion characteristics and the risk of malignancy for mammographically and clinically occult lesions detected initially on breast MRI. MATERIALS AND METHODS: We reviewed 1,523 consecutive breast MRI examinations performed from January 1, 2003, to June 30, 2005, to identify all lesions initially detected on MRI and assessed as BI-RADS 4 or 5 for which the patient underwent subsequent imaging-guided needle or excisional biopsy. BI-RADS lesion features were recorded for each case, and the risk of malignancy was assessed using generalized estimating equations. Separate multivariate models were constructed for lesions classified as masses. RESULTS: Included in the analysis were 258 suspicious lesions in 196 women. Among all lesions, those of 1 cm or greater were significantly more often malignant (50/147, 34%) than lesions of less than 1 cm (22/111, 20%; odds ratio, 2.09; 95% CI, 1.13-3.83). For masses, size, BI-RADS margin, and enhancement pattern predicted malignancy. In multivariate analysis of combinations of features, masses of 1 cm or greater with heterogeneous enhancement and irregular margins had a 68% probability of malignancy. Masses of 1 cm or greater with smooth margins and homogeneous enhancement had the lowest predicted probability of malignancy of 3%. BI-RADS descriptors and size were not significant predictors of malignancy for nonmasslike enhancement (NMLE). CONCLUSION: Combinations of BI-RADS lesion descriptors can predict the probability of malignancy for breast MRI masses but not for NMLE. If our model is validated, masses with a low probability of malignancy may be eligible for short-interval follow-up rather than biopsy. Further research focused on predictive features of NMLE is needed.
机译:目的:本研究的目的是评估BI-RADS病变特征的预测特征,以及最初在乳腺MRI上发现的乳腺和临床隐匿性病变的恶性风险。材料与方法:我们回顾了从2003年1月1日至2005年6月30日进行的1,523例乳房MRI连续检查,以鉴定最初在MRI上发现并评估为BI-RADS 4或5的所有病变,并对其进行了后续影像学检查针头或切除活检。记录每种情况下的BI-RADS病变特征,并使用广义估计方程评估恶性肿瘤的风险。为分类为肿块的病变建立了单独的多元模型。结果:分析包括196位女性中的258位可疑病变。在所有病变中,1 cm或更大的病变的恶性率(50 / 147,34%)明显少于1 cm(22/111,20%;优势比,2.09; 95%CI,1.13-3.83 )。对于肿块,大小,BI-RADS边缘和增强模式可预测恶性肿瘤。在特征组合的多变量分析中,肿块1 cm或更大且异质性增强且边缘不规则,恶性可能性为68%。 1 cm或更大的肿块具有平滑的边缘和均一的增强,具有3%的最低恶性预测概率。 BI-RADS描述符和大小不是非块状增强(NMLE)恶性程度的重要预测指标。结论:结合BI-RADS病变描述子可以预测乳腺MRI肿块而不是NMLE的恶性可能性。如果我们的模型得到验证,则恶性可能性低的肿块可能适合进行短间隔随访而不是活检。需要对NMLE的预测特征进行进一步研究。

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