多参数扩散加权成像在乳腺病变中的应用：与病理诊断和预后因素的相关性。
Multiparametric diffusion-weighted imaging in breast lesions: Association with pathologic diagnosis and prognostic factors.
机构信息
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China.
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, PR China.
出版信息
J Magn Reson Imaging. 2017 Sep;46(3):740-750. doi: 10.1002/jmri.25612. Epub 2017 Jan 31.
PURPOSE
To determine the utility of multiparametric diffusion-weighted imaging (DWI) including monoexponential (apparent diffusion coefficient [ADC]), biexponential (D , D , and f), stretched-exponential (distributed diffusion coefficient [DDC] and α), and kurtosis (mean diffusivity [MD] and mean kurtosis [MK]) models in the differentiation and characterization of breast lesions, and assess their associations with prognostic factors in invasive breast cancer.
MATERIALS AND METHODS
This study included 101 patients (44 benign and 57 malignant lesions) who underwent 3T breast multi-b-value DWI. Diffusion model selection was investigated in benign and malignant lesions using the Akaike information criteria (AIC). Mann-Whitney U-test and receiver operating characteristic (ROC) curves were used for statistical analysis.
RESULTS
Goodness-of-fit analysis showed that most benign lesion voxels (50.5%) were preferred by the kurtosis model, and most malignant lesion voxels (51.2%) by the stretched-exponential model. All diffusion measures showed significant differences between benign and malignant lesions (P < 0.05), and between in situ and invasive cancers (P < 0.05) except MD (P = 0.103). There were no significant differences in areas under the ROC curves (AUCs) between ADC and non-monoexponential diffusion parameters (P > 0.05), except D and α, whose AUCs were significantly lower than AUC of ADC for differentiating benign from malignant lesions (P = 0.03 and P < 0.01, respectively). In patients with invasive breast cancer, α was significantly correlated with tumor size (P = 0.007) and Ki-67 expression (P = 0.012), D was significantly correlated with lymph node metastasis (P = 0.021) and Ki-67 expression (P = 0.042), and ADC, D , f, DDC, and MD were significantly correlated with estrogen receptor status (all P < 0.05).
CONCLUSION
Multiparametric DWI shows relationships with pathologic outcomes and prognostic factors of breast lesions.
LEVEL OF EVIDENCE
3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:740-750.
目的
旨在确定包括单指数（表观扩散系数 [ADC]）、双指数（D、D 和 f）、扩展指数（分布扩散系数 [DDC] 和 α）和峰度（平均扩散系数 [MD] 和平均峰度 [MK]）模型的多参数扩散加权成像（DWI）在鉴别和特征化乳腺病变中的效用，并评估它们与浸润性乳腺癌中预后因素的相关性。
材料与方法
本研究纳入了 101 名患者（44 例良性病变和 57 例恶性病变），这些患者接受了 3T 乳腺多 b 值 DWI。使用赤池信息量准则（AIC）研究了良性和恶性病变中扩散模型的选择。采用曼-惠特尼 U 检验和受试者工作特征（ROC）曲线进行统计学分析。
结果
拟合优度分析显示，大多数良性病变体素（50.5%）优选峰度模型，而大多数恶性病变体素（51.2%）优选扩展指数模型。所有扩散指标在良性和恶性病变之间（P < 0.05）以及原位癌和浸润性癌之间（P < 0.05）均存在显著差异，除 MD（P = 0.103）外。ADC 和非单指数扩散参数之间的 ROC 曲线下面积（AUC）差异无统计学意义（P > 0.05），除 D 和 α 外，其 AUC 显著低于 ADC 用于鉴别良性和恶性病变的 AUC（P = 0.03 和 P < 0.01）。在浸润性乳腺癌患者中，α 与肿瘤大小显著相关（P = 0.007）和 Ki-67 表达显著相关（P = 0.012），D 与淋巴结转移和 Ki-67 表达显著相关（P = 0.021 和 P < 0.01），ADC、D、f、DDC 和 MD 与雌激素受体状态显著相关（均 P < 0.05）。
结论
多参数 DWI 与乳腺病变的病理结果和预后因素有关。
证据水平
3 级 技术功效：2 级 J. MAGN. RESON. IMAGING 2017；46：740-750.
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