Zhao Siqi, Wang Shiyu, Li Yuanfei, Wu Yueqi, Zhang Moyun, Ning Ning, Liang Hongbing, Dong Deshuo, Yang Jie, Gao Xue, Guan Haonan, Zhang Lina
Department of Radiology, First Affiliated Hospital of Dalian Medical University, No 222 zhongshan Road, Xigang district, Dalian, Liaoning 116011, PR China (S.Z., S.W., Y.L., Y.W., M.Z., H.L., D.D., L.Z.).
Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, No. 6 Jiefang Street, Zhongshan District, Dalian, Liaoning 116001, PR China (N.N.).
Acad Radiol. 2025 Apr;32(4):1851-1860. doi: 10.1016/j.acra.2024.11.011. Epub 2024 Nov 26.
To explore the predictive value of quantitative parameters from intravoxel incoherent movement (IVIM) imging and dynamic contrast enhancement MRI (DCE-MRI) for HER2 expression in breast cancer.
This retrospective study included 167 women with breast cancer who underwent MRI from December 2019 to December 2023, categorized into 48 HER2-positive, 78 HER2-low and 41 HER2-zero cancers. All patients underwent IVIM imaging and DCE-MRI. Statistical analyses, including one-way ANOVA, Kruskal-Wallis test and χ2 test, were employed to compare clinical data, MRI features, and MRI quantitative parameters including standard ADC(ADC), pure diffusion coefficient(D), perfusion-related diffusion coefficient(D*), perfusion fraction(f), volume transfer constant(K), extravascular extracellular interstitial volume ratio(V) and rate constant(K) between the three groups. Multivariable logistic regression was used to identify independent predictors for distinguishing HER2 expressions. The diagnostic efficacy of significant IVIM and DCE parameters for different HER2 expressions was analyzed using receiver operator characteristic (ROC) curves.
Peritumoral edema, histological grade and K achieved an AUC of 0.86(95%CI:0.78,0.91) in distinguishing HER2-positive tumors from HER2-low expressing tumors and were independent predictors for differentiating these two groups. Among HER2-positive and -zero breast cancers, the combined model of D*, K and K had an AUC of 0.74(95%CI:0.63,0.82) for the prediction of HER2-positive versus HER2-zero cancers, and its prediction efficiency was not improved compared with that of a single parameter(P > .05).
Quantitative parameters from intravoxel incoherent movement imaging and dynamic contrast enhancement MRI can predict different HER2 expressions in breast cancer from different perspectives, with implications for therapy.
探讨体素内不相干运动(IVIM)成像和动态对比增强磁共振成像(DCE-MRI)的定量参数对乳腺癌中HER2表达的预测价值。
本回顾性研究纳入了2019年12月至2023年12月期间接受MRI检查的167例乳腺癌女性患者,分为48例HER2阳性、78例HER2低表达和41例HER2阴性癌症患者。所有患者均接受了IVIM成像和DCE-MRI检查。采用单因素方差分析、Kruskal-Wallis检验和χ²检验等统计分析方法,比较三组患者的临床资料、MRI特征以及MRI定量参数,包括标准表观扩散系数(ADC)、纯扩散系数(D)、灌注相关扩散系数(D*)、灌注分数(f)、容积转移常数(K)、血管外细胞外间隙容积比(V)和速率常数(K)。采用多变量逻辑回归分析确定区分HER2表达的独立预测因素。使用受试者工作特征(ROC)曲线分析显著的IVIM和DCE参数对不同HER2表达的诊断效能。
瘤周水肿、组织学分级和K在区分HER2阳性肿瘤与HER2低表达肿瘤方面的曲线下面积(AUC)为0.86(95%置信区间:0.78,0.91),是区分这两组的独立预测因素。在HER2阳性和阴性乳腺癌中,D*、K和K的联合模型预测HER2阳性与HER2阴性癌症的AUC为 0.74(95%置信区间:0.63,0.82),与单一参数相比,其预测效率未得到提高(P>0.05)。
体素内不相干运动成像和动态对比增强MRI的定量参数可以从不同角度预测乳腺癌中不同的HER2表达,对治疗具有指导意义。