目的:分析3.0T MR动态增强曲线联合ADC用于乳腺良恶性病变鉴别诊断中的应用价值。方法:将我院2017年1月—2019年3月间收治乳腺病变患者依照病理诊断的良恶性分为良性病变组及恶性病变组;对受试者采用3.0T MR进行检查,绘制ROC曲线分析动态增强曲线联合ADC用于乳腺良恶性病变鉴别。结果:良性病变组与恶性病变组患者动态增强曲线存在明显差异,且差异有统计学意义(P<0.05),恶性病变组患者ADC值明显低于良性病变组,且差异有统计学意义(P<0.05);动态增强曲线分析结果为乳腺良性病变的73例,ADC值分析结果为乳腺良性病变的72例,联合应用分析结果为乳腺良性病变的70例;动态增强曲线与ADC值联合应用鉴别诊断乳腺良恶性的敏感度、特异度及AUC均明显高于各指标单独应用,且差异有统计学意义(P<0.05)。结论:采用3.0T MR动态增强曲线联合ADC对乳腺良恶性病变进行鉴别诊断的敏感度及特异度均明显高于增强曲线或ADC单独应用。
Abstract
Objective: To analyze the application value of 3.0T MR dynamic enhancement curve combined with ADC in differential diagnosis of benign and malignant breast lesions. Methods: The patients with breast lesions from January 2017 to March 2019 in our hospital were divided into benign lesion group and malignant lesion group according to the pathological diagnosis. The subjects were examined with 3.0T MR and the ROC curve analysis was dynamically enhanced. Curve combined with ADC was for the differential diagnosis of benign and malignant breast lesions. Results: There were significant differences in the dynamic enhancement curves between the benign lesion group and the malignant lesion group, and the difference was statistically significant(P<0.05). The ADC value of the benign lesion group was significantly lower than that of the malignant lesion group, and the difference was statistically significant(P<0.05). The results of dynamic enhancement curve analysis were 73 cases of benign breast lesions. The results of ADC analysis were 72 cases of benign breast lesions. The combined application analysis showed 70 cases of benign breast lesions. The combination of dynamic enhancement curve and ADC value was used to differentially diagnose breast. The sensitivity, specificity and AUC of benign and malignant were significantly higher than those of each index, and the difference was statistically significant(P<0.05). Conclusion: The sensitivity and specificity of the differential diagnosis of benign and malignant breast lesions using 3.0T MR dynamic enhancement curve combined with ADC were significantly higher than those of the enhancement curve or ADC alone.
关键词
乳腺肿瘤 /
乳腺疾病 /
磁共振成像
Key words
Breast neoplasms /
Breast diseases /
Magnetic resonance imaging
中图分类号:
R737.9
R655.8
R445.2
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参考文献
[1]Durur-Subasi I, Durur-Karakaya A, Karaman A, et al. Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions?[J]. Brit J Radiol, 2017, 90(1073):20160803.
[2]Cheng Z, Wu Z, Shi G, et al. Discrimination between benign and malignant breast lesions using volumetric quantitative dynamic contrast-enhanced MR imaging[J]. Eur Radiol, 2017, 28(3): 1-10.
[3]邓佳敏,韩秉艳,马景旭,等. MRI早期强化比值联合周围血管管径鉴别诊断乳腺病变的价值[J]. 医学影像学杂志,2017,27(7):1254-1257.
[4]Yan X, Yao S, Li X, et al. Benign and malignant breast lesions identification through the values derived from shear wave elastography: evidence for the meta-analysis[J]. Oncotarget, 2017, 8(51): 89173-89181.
[5]Hu B, Xu K, Zhang Z, et al. A radiomic nomogram based on an apparent diffusion coefficient map for differential diagnosis of suspicious breast findings[J]. Chinese J Cancer Res, 2018, 30(4): 432-438.
[6]李丹. 磁共振DWI成像ADC值在评价肝脏功能Child-Pugh分级中的作用[D]. 沈阳:中国医科大学,2016.
[7]吕艳丽,李毅. 乳腺良恶性疾病的危险因素分析[J]. 山西医药杂志,2018,47(20):2387-2389.
[8]Feng Z, Zhou Z, Tang D, et al. Diffusion-weighted MRI in solitary pulmonary lesions: associations between apparent diffusion coefficient and multiple histopathological parameters[J]. Sci Rep, 2018, 8(1): 224.
[9]Shen Y, Zhong Y, Wang H, et al. Ultra-high b-value diffusion-weighted imaging features of the prostatic leiomyoma-case report[J]. BMC Med Imaging, 2017, 17(1): 63.
[10]Pierre T, Cornud F, CollaTer L, et al. Diffusion-weighted imaging of the prostate: should we use quantitative metrics to better characterize focal lesions originating in the peripheral zone?[J]. Eur Radiol, 2017, 28(5): 1-10.
[11]李柠肖,王乐华,邝永卫,等. 3D-PDS联合BI-RADS在乳腺良、恶性病灶鉴别诊断中的价值分析[J]. 河北医药,2018,40(16):2488-2491.
[12]Jiang X, Fei X, Liu L, et al. Discrimination of malignant and benign breast masses using automatic segmentation and features extracted from dynamic contrast-enhanced and diffusion-weighted MRI[J]. Oncol Lett, 2018, 16(2): 1521-1528.
[13]Yin J, Yang J, Jiang Z. Discrimination between malignant and benign mass-like lesions from breast dynamic contrast enhanced MRI: semi-automatic vs. manual analysis of the signal time-intensity curves[J]. J Cancer, 2018, 9(5): 834-840.
[14]王富民,印隆林,陈晓煜,等. 3.0T磁共振联合序列检查对乳腺良恶性病变的鉴别诊断价值[J]. 中国普外基础与临床杂志,2018,25(7):817-823.
[15]Fan WX, Chen XF, Cheng FY, et al. Retrospective analysis of the utility of multiparametric MRI for differentiating between benign and malignant breast lesions in women in China[J]. Medicine, 2018, 97(4): e9666.