Application value of MRI features in growing BI-RADS class 3 breast lesions
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摘要:
目的 分析MRI在生长型BI-RADS 3类乳腺病变中的应用价值。 方法 选择2021年11月~2022年6月本院确诊BI-RADS 3类乳腺病变的115例患者作为研究对象，分析其MRI影像学特征及其对此类患者病情变化预测价值。 结果 115例患者经乳腺超声随访检查发现87例生长型BI-RADS 3类病变分级下降或者稳定，28例病变分级升级；降级或稳定组与升级组患者形态、边界、内部强化、时间-信号强度曲线(TIC)、表观扩散系数(ADC)值等MIR放射学表现的差异有统计学意义(P < 0.05)；多因素Logistic回归分析结果显示，内部强化、TIC曲线、ADC值是生长型BI-RADS 3类乳腺病变变化影响因素(P < 0.05)；ROC曲线显示，内部强化、TIC曲线、ADC值用于预测生长型BI-RADS 3类病变变化曲线下面积分别为0.669、0.582、0.844(P < 0.05)。 结论 生长型BI-RADS 3类乳腺病变患者MRI放射学特征与病变分级升级密切相关，其中内部强化、TIC曲线、ADC值等MRI放射学特征可作为预测BI-RADS 3类病变升级的重要指标，对乳腺病变良恶性诊断及病情进展预测提供可靠依据。 -
关键词:
- 乳腺影像报告和数据系统 /
- 磁共振 /
- 影像学特征
Abstract:Objective To analyze the application value of MRI in growing BI-RADS class 3 breast lesions. Methods A total of 115 patients who diagnosed with growing BI-RADS class 3 lesions in the hospital from November 2021 to June 2022 were selected as the study subjects. The MRI features and their predictive value for condition changes were analyzed. Results Breast ultrasound follow- up found that among the 115 patients, there were 87 patients with decreased grade of BI-RADS class 3 lesions or stable BI-RADS class 3 lesions, and 28 patients with increased grade of BI-RADS 3 lesions. There was statistically significant differences in MRI findings such as morphology, boundary, internal enhancement, time-signal intensity curve (TIC) and apparent diffusion coefficient (ADC) value between the decreased grade or stable group and the increased grade group (P < 0.05). Multivariate logistic regression analysis found that internal enhancement, TIC curve and ADC value were influencing factors of changes in growing BI-RADS class 3 lesions (P < 0.05). ROC curve showed that the area under the curve values of internal enhancement, TIC curve and ADC value to predict changes in growing BI-RADS class 3 lesions were 0.669, 0.582 and 0.844, respectively (P < 0.05). Conclusion MRI features of patients with growing BI-RADS class 3 breast lesions are closely related to the grading and upgrading of lesions. Features such as internal enhancement, tic curve and ADC value can be used as important indicators to predict the upgrading of BI-RADS class 3 lesions, it provides a reliable basis for the diagnosis of benign and malignant breast lesions and the prediction of disease progression. -
图 1 生长型BI-RADS 3类乳腺病变随访稳定患者病例
Figure 1. Follow-up images of a patient with stable growing BIRADS class 3 breast lesions. The patient was a 51-year-old female with left breast mass of growing BI-RADS class 3. A: MRI showed clear boundary. B: TIC was type III, Follow-up diagnosis showed the condition was stable and the lesion was still BI-RADS class 3.
图 2 生长型BI-RADS 3类乳腺病变随访升级患者
Figure 2. Follow-up images of patients with upgraded growing BI-RADS class 3 breast lesions.The patient was a 42-year-old female with left breast mass of growing BI-RADS class 3. A: MRI showed irregular boundary; B: TIC was type III. Follow-up diagnosis showed upgrading to BI-RADS class 4. Later, the patient was confirmed as breast invasive ductal carcinoma.
图 3 内部强化、TIC曲线、ADC值对生长型BI-RADS 3类乳腺病变升级的预测价值分析
Figure 3. The predictive value of internal enhancement, TIC and ADC value for upgrading of growing BI-RADS class 3 breast lesions.
表 1 生长型BI-RADS 3类乳腺病变升级与MRI检查放射学表现的关系
Table 1. Relationship between upgrading of growing BI-RADS class 3 breast lesions and MRI findings [n(%)]
MRI findings Downgrading/stable group (n=87) Upgrading group (n=28) t/χ2 P Morphology 4.164 0.041 Irregular (n=32) 20(22.99) 12(42.86) Round/roundish (n=83) 67(77.01) 16(57.14) Boundary 7.332 0.026 Spiculation (n=13) 6(6.90) 7(25.00) Blurry and irregular (n=28) 21(24.14) 7(25.00) Smooth (n=74) 60(68.97) 14(50.00) Composition of breast fibrograndular tissue 0.745 0.863 Inhomogeneous dense type (n=62) 46(52.87) 16(57.14) Extremely dense type (n=34) 26(29.89) 8(28.57) Small amount type (n=11) 8(9.20) 3(10.71) Fat type (n=8) 7(8.05) 1(3.57) Internal enhancement 8.717 0.013 Homogeneous enhancement (n=36) 33(37.93) 3(10.71) Inhomogeneous enhancement (n=57) 41(47.13) 16(57.14) Ring enhancement (n=22) 13(14.94) 9(32.14) Background enhancement of breast parenchyma 0.556 0.907 No enhancement (n=43) 34(39.08) 9(32.14) Mild enhancement (n=38) 28(32.18) 10(35.71) Moderate enhancement (n=25) 18(20.69) 7(25.00) Severe enhancement (n=9) 7(8.05) 2(7.14) TIC 9.534 0.009 Inflow type (n=31) 29(33.33) 2(7.14) Outflow type (n=36) 22(25.29) 14(50.00) Platform type (n=48) 36(41.38) 12(42.38) ADC value(×10-3mm2/s, Mean±SD) 1.96±0.41 1.28±0.24 8.314 ＜0.001 TIC: Time-signal intensity curve; ADC: Apparent diffusion coefficient. 
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表 2 生长型BI-RADS 3类病变变化影响因素分析
Table 2. Influencing factors of condition changes of growing BI-RADS class 3 lesions
Factors β SE Wald χ2 OR 95% CI P Morphology Irregular 1.000 Round/roundish 0.528 0.327 2.607 1.696 0.893-3.219 0.107 Boundary Boundary 1.000 Blurry and irregular -0.327 0.196 2.783 0.721 0.491-1.059 0.096 Smooth -0.423 0.241 3.081 0.655 0.408-1.051 0.080 Internal enhancement Homogeneous enhancement 1.000 Inhomogeneous enhancement 0.454 0.181 6.292 1.575 1.104-2.245 0.013 Ring enhancement 0.549 0.256 4.599 1.732 1.048-2.860 0.033 TIC Inflow type 1.000 Outflow type 0.495 0.147 11.339 1.640 1.230-2.188 0.001 Platform type 0.324 0.108 9.000 1.383 1.119-1.709 0.003 ADC value (×10-3mm2/s) 0.576 0.216 7.111 1.779 1.165-2.717 0.008
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表 3 内部强化、TIC曲线、ADC值对生长型BI-RADS 3类乳腺病变升级的预测价值分析
Table 3. The predictive value of internal enhancement, TIC and ADC value for upgrading of growing BI-RADS class 3 breast lesions
Index AUC Sensitivity (%) Specificity (%) 95% CI P Internal enhancement 0.669 89.31 37.92 0.559-0.779 0.007 TIC 0.582 92.88 33.29 0.472-0.691 0.195 ADC value 0.844 96.38 70.08 0.775-0.914 < 0.001
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