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应用容积定量动态对比增强磁共振成像鉴别乳腺良恶性病变。

Discrimination between benign and malignant breast lesions using volumetric quantitative dynamic contrast-enhanced MR imaging.

机构信息

Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, Guangdong, 510120, China.

Guangdong Provincial Key Laboratory of Malignant Tumour Epigenetics and Gene Regulation, Medical Research Centre, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.

出版信息

Eur Radiol. 2018 Mar;28(3):982-991. doi: 10.1007/s00330-017-5050-2. Epub 2017 Sep 19.

Abstract

OBJECTIVE

To determine the diagnostic performance of volumetric quantitative dynamic contrast-enhanced MRI (qDCE-MRI) in differentiation between malignant and benign breast lesions.

METHODS

DCE-MRI was performed in 124 patients with 136 breast lesions. Quantitative pharmacokinetic parameters K, K, V, V and semi-quantitative parameters TTP, MaxCon, MaxSlope, AUC were obtained by using a two-compartment extended Tofts model and three-dimensional volume of interest. Morphologic features (lesion size, margin, internal enhancement pattern) and time-signal intensity curve (TIC) type were also assessed. Logistic regression analysis was used to determine predictors of malignancy, followed by receiver operating characteristics (ROC) analysis to evaluate the diagnostic performance.

RESULTS

qDCE parameters (K, K, V, TTP, MaxCon, MaxSlope and AUC), morphological parameters and TIC type were significantly different between malignant and benign lesions (P≤0.001). Multivariate logistic regression analyses showed that K, K, MaxSlope, size, margin and TIC type were independent predictors of malignancy. The diagnostic accuracy of logistic models based on qDCE parameters alone, morphological features plus TIC type, and all parameters combined was 94.9%, 89.0%, and 95.6% respectively.

CONCLUSION

qDCE-MRI can be used to improve diagnostic differentiation between benign and malignant breast lesions in relation to morphology and kinetic analysis.

KEY POINTS

• qDCE-MRI parameters are useful for discriminating between malignant and benign breast lesions. • K , K and MaxSlope were independent predictors of breast malignancy. • qDCE-MRI has a better diagnostic ability than morphology and kinetic analysis. • qDCE-MRI can be used to improve the diagnostic accuracy of breast malignancy.

摘要

目的

评估容积定量动态对比增强磁共振成像(qDCE-MRI)在鉴别乳腺良恶性病变中的诊断效能。

方法

对 124 例 136 个乳腺病灶行 DCE-MRI 检查,采用两室扩展 Tofts 模型及三维容积感兴趣区技术获得定量药代动力学参数 Ktrans、Kep、Ve、Vp,半定量参数 TTP、MaxCon、MaxSlope、AUC,同时评估病灶形态学特征(大小、边界、内部强化方式)及时间-信号强度曲线(TIC)类型。采用 Logistic 回归分析确定良恶性的预测因素,然后通过受试者工作特征(ROC)曲线分析评估诊断效能。

结果

qDCE 参数(Ktrans、Kep、Ve、TTP、MaxCon、MaxSlope、AUC)、形态学参数及 TIC 类型在良恶性病变间差异均有统计学意义(P≤0.001)。多因素 Logistic 回归分析显示,Ktrans、Kep、MaxSlope、大小、边界及 TIC 类型是良恶性的独立预测因素。基于 qDCE 参数、形态学特征联合 TIC 类型及所有参数构建的 Logistic 模型的诊断准确率分别为 94.9%、89.0%、95.6%。

结论

qDCE-MRI 可通过形态学及动力学分析提高乳腺良恶性病变的鉴别诊断能力。

关键点

• qDCE-MRI 参数有助于鉴别乳腺良恶性病变。

• Ktrans、Kep 和 MaxSlope 是乳腺恶性肿瘤的独立预测因素。

• qDCE-MRI 比形态学及动力学分析具有更好的诊断效能。

• qDCE-MRI 有助于提高乳腺恶性肿瘤的诊断准确率。

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