Chen Kewei, Yu Chengxin, Pan Junlong, Xu Yaqia, Luo Yuqing, Yang Ting, Yang Xiaoling, Xie Lisi, Zhang Jing, Zhuo Renfeng
Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China; Department of Radiology, Women and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang, Hubei, China.
Magn Reson Imaging. 2024 May;108:168-175. doi: 10.1016/j.mri.2024.02.012. Epub 2024 Feb 24.
To explore the ability of intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and background parenchyma enhancement (BPE) to predict the Nottingham prognostic index (NPI) and molecular subtypes of breast cancer (BC).
In this study, 93 patients with BC were included, and they all underwent DKI, IVIM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) examinations. The corresponding mean kurtosis value (MK), pure diffusion (MD), perfusion fraction (f), pseudo diffusion coefficient (D*), true diffusion coefficient (D), and BPE were measured. We used logistic regression analysis to investigate the relevance between the NPI, molecular subtypes and variables. The diagnostic efficacy was analyzed using receiver operating characteristic curves (ROC).
The MD and D values of the high-level NPI group were significantly lower than those of the low-level NPI group (p < 0.01), and the f value of the high-level NPI group was obviously higher than that of low-level NPI group (p < 0.001). The area under curve (AUC) of the combined model (f + D) was 0.824. Comparing with non-Luminal subtypes, the Luminal subtypes showed obviously lower MK, f and D*, and the AUC of the combined model (MK + f + D*) was 0.785. In comparison to other subtypes, the MK and D* values of triple-negative subtype were higher than other subtypes, and the combined model (MK + D*) represented an AUC of 0.865.
The quantitative parameters of DKI and IVIM have vital value in predicting the NPI and molecular subtypes of BC, while BPE could not provide additional information. Besides, these combined models can obviously improve the prediction performance.
探讨体素内不相干运动（IVIM）、扩散峰度成像（DKI）及背景实质强化（BPE）预测乳腺癌（BC）诺丁汉预后指数（NPI）及分子亚型的能力。
本研究纳入93例BC患者，所有患者均接受DKI、IVIM及动态对比增强磁共振成像（DCE-MRI）检查。测量相应的平均峰度值（MK）、纯扩散（MD）、灌注分数（f）、伪扩散系数（D*）、真扩散系数（D）及BPE。采用逻辑回归分析研究NPI、分子亚型与各变量之间的相关性。使用受试者工作特征曲线（ROC）分析诊断效能。
高水平NPI组的MD和D值显著低于低水平NPI组（p<0.01），高水平NPI组的f值明显高于低水平NPI组（p<0.001）。联合模型（f+D）的曲线下面积（AUC）为0.824。与非Luminal亚型相比，Luminal亚型的MK、f和D明显较低，联合模型（MK+f+D）的AUC为0.785。与其他亚型相比，三阴性亚型的MK和D值高于其他亚型，联合模型（MK+D）的AUC为0.865。
DKI和IVIM的定量参数在预测BC的NPI和分子亚型方面具有重要价值，而BPE不能提供额外信息。此外，这些联合模型可明显提高预测性能。
