动态增强MRI在乳腺非肿块样强化良恶性病变鉴别诊断中的临床应用研究-东南大学学报医学版

动态增强MRI在乳腺非肿块样强化良恶性病变鉴别诊断中的临床应用研究

单位：南京中医药大学附属江苏省中医院放射科, 江苏南京 210029

分类号：R737.9; R445.2

出版年·卷·期（页码）：2023·42·第六期（903-908）

摘要：

目的:探讨动态增强MRI(DCE-MRI)技术在乳腺非肿块样强化(NME)良恶性病变鉴别诊断中的诊断效能与临床应用价值。方法:回顾性分析在本院经穿刺或手术病理证实且均进行MRI检查的126例乳腺NME患者的影像资料,其中NME良性病变组44例,NME恶性病变组82例,均为女性,平均年龄(45.6±11.6)岁。分析比较两组NME病灶在DCE-MRI上的分布类型、强化特点、表观弥散系数(ADC)值及时间-信号强度曲线(TIC),并对有意义的影响因素进行多因素二元Logistic回归分析筛选出预测恶性病变的危险因素。结果:局灶、线样、段样、多区域、弥漫型分布在NME良恶性病变组间差异有统计学意义(P＜0.05);均匀强化及簇环样强化在NME良恶性病变组间差异具有统计学意义(P＜0.05);Ⅰ型及Ⅲ型时间-信号强度曲线在NME良恶性病变组间差异具有统计学意义(P＜0.05);NME良恶性病变ADC值组间差异具有统计学意义(t＝6.502,P＜0.05);多因素二元Logistic回归分析显示,段样分布、簇环样强化及ADC值可以作为预测乳腺NME恶性病变的危险因素(P＜0.05)。结论:DCE-MRI技术所提供的形态学及血流动力学特点有助于提高乳腺NME良恶性病变的诊断效能。

Objective: To explore the efficacy and clinical value of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI) in the differential diagnosis of benign and malignant breast lesions with non-mass enhancement(NME). Methods: A retrospective analysis was conducted on imaging data of 126 female patients with breast NME who underwent MRI examination and confirmed by biopsy or surgical pathology in our hospital, including 44 cases of benign lesions and 82 cases of malignant lesions, with a mean age of(45.6±11.6) years old. The distribution patterns, enhancement characteristics, apparent diffusion coefficient(ADC) values, and time-signal intensity curves(TIC) of NME lesions on DCE-MRI were analyzed and compared between the NME benign and malignant groups. Multivariate binary Logistic regression analysis was performed to identify significant factors associated with predicting malignant lesions. Results: There were statistically significant differences between the NME benign and malignant groups in terms of focal, linear, segmental, multi-regional, and diffuse distribution patterns(P<0.05). Homogeneous enhancement and cluster ring enhancement showed statistically significant differences between the NME benign and malignant groups(P<0.05). Type I and type III time-signal intensity curves(TIC)showed statistically significant differences between the NME benign and malignant groups(P<0.05). There was a statistically significant difference in ADC values between the NME benign and malignant groups(t=6.502,P<0.05). Multivariate binary Logistic regression analysis showed that segmental distribution, cluster ring enhancement, and ADC values were identified as significant factors for predicting malignant breast NME lesions(P<0.05). Conclusion: The morphological and hemodynamic characteristics provided by DCE-MRI can improve the diagnostic efficacy of benign and malignant breast NME lesions.

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