目的：探讨多模态MRI技术对乳腺单发良恶性结节鉴别的意义。方法：收集2013年1月—2016年9月我院乳腺科收治的51例乳腺结节（直径≤3 cm）患者，并对患者的年龄、病灶的形态、毛刺、边界、ADC值、增强曲线类型进行统计学分析。结果：患者的年龄无统计学差异（P=0.382），病灶的形态、毛刺、边界、ADC值、增强曲线类型之间有统计学差异（P<0.05）。另外以上述征象为变量建立Logistic模型，筛选出2个自变量，其模型为：Logit（P）=-0.503+0.387X5+0.257X6，其预报能力的敏感性为91.9%，特异性为92.2%。结论：Logistic回归模型能够找出乳腺单发结节良恶性最具特征的MRI征象，提高乳腺疾病鉴别诊断的能力，为临床诊疗提供更准确的影像信息。
Abstract
Objective: To explore the significance of multimodal MRI in the identification of malignant breast lesions. Methods: We collected 51 cases of mammary gland patients with mammary gland nodules(diameter≤3 cm) from January 2013 to September 2016. The patient’s age, morphology of lesions, spiculation, boundary, ADC values and enhancement curve type were statistical analysis. Results: There was no statistically significant difference in the patient’s age(P=0.382). And there were statistical difference between the shape of the lesion, spiculation, boundary, ADC value, and enhancement curve type(P<0.05). In addition, the Logistic model was established to select two independent variables. The model was: Logit(P)=-0.503+0.387X5+0.257X6. And the sensitivity of its prediction ability was 91.9% and the specificity was 92.2%. Conclusion: Logistic regression model can be used to identify the most characteristic of benign malignant breast nodules, improve the ability of differential diagnosis of breast diseases, and provide more accurate imaging information for clinical diagnosis and treatment.
关键词
乳腺疾病 /
乳腺肿瘤 /
磁共振成像
Key words
Breast diseases /
Breast neoplasms /
Magnetic resonance imaging
中图分类号：
Ｒ655.8
Ｒ737.9
Ｒ445.2
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基金
东莞市医疗卫生科技计划项目：20131051010255。
