Mao Chunping, Jiang Wei, Huang Jiayi, Wang Mengzhu, Yan Xu, Yang Zehong, Wang Dongye, Zhang Xiang, Shen Jun
Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
Department of Radiology, Shenshan Central Hospital, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Shanwei, China.
Front Oncol. 2022 Feb 3;12:817070. doi: 10.3389/fonc.2022.817070. eCollection 2022.
To explore the value of quantitative parameters derived from diffusion spectrum imaging (DSI) in preoperatively predicting human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer.
In this prospective study, 114 and 56 female patients with invasive ductal carcinoma were consecutively included in a derivation cohort and an independent validation cohort, respectively. Each patient was categorized into HER2-positive or HER2-negative groups based on the pathologic result. All patients underwent DSI and conventional MRI including dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). The tumor size, type of the time-signal intensity curve (TIC) from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, and quantitative parameters derived from DSI, including diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) of primary tumors, were measured and compared between the HER2-positive and HER2-negative groups in the derivation cohort. Univariable and multivariable logistic regression analyses were used to determine the potential independent predictors of HER2 status. The discriminative ability of quantitative parameters was assessed by receiver operating characteristic (ROC) curve analyses and validated in the independent cohort.
In the derivation cohort, the tumor size, TIC type, and ADC values did not differ between the HER2-positive and HER2-negative groups ( = 0.126-0.961). DSI quantitative parameters including axial kurtosis of DKI (DKI_AK), non-Gaussianity (MAP_NG), axial non-Gaussianity (MAP_NG), radial non-Gaussianity (MAP_NG), return-to-origin probability (MAP_RTOP), return-to-axis probability of MAP (MAP_RTAP), and intracellular volume fraction of NODDI (NODDI_ICVF) were lower in the HER2-positive group than in the HER2-negative group ( ≤ 0.001-0.035). DSI quantitative parameters including radial diffusivity (DTI_RD), mean diffusivity of DTI (DTI_MD), mean squared diffusion (MAP_MSD), and q-space inverse variance of MAP (MAP_QIV) were higher in the HER2-positive group than in the HER2-negative group ( = 0.016-0.049). The ROC analysis showed that the area under the curve (AUC) of ADC was 0.632 and 0.568, respectively, in the derivation and validation cohorts. The AUC values of DSI quantitative parameters ranged from 0.628 to 0.700 and from 0.673 to 0.721, respectively, in the derivation and validation cohorts. Logistic regression analysis showed that only NODDI_ICVF was an independent predictor of HER2 status ( = 0.001), with an AUC of 0.700 and 0.721, respectively, in the derivation and validation cohorts.
DSI could be helpful for preoperative prediction of HER2, but DSI alone may not be sufficient in predicting HER2 status preoperatively in patients with breast cancer.
探讨扩散谱成像(DSI)衍生的定量参数在术前预测乳腺癌患者人表皮生长因子受体2(HER2)状态中的价值。
在这项前瞻性研究中,分别有114例和56例浸润性导管癌女性患者连续纳入推导队列和独立验证队列。根据病理结果将每位患者分为HER2阳性或HER2阴性组。所有患者均接受DSI及常规MRI检查,包括动态对比增强MRI(DCE-MRI)和扩散加权成像(DWI)。测量并比较推导队列中HER2阳性组和HER2阴性组的肿瘤大小、DCE-MRI的时间-信号强度曲线(TIC)类型、DWI的表观扩散系数(ADC)以及DSI衍生的定量参数,包括原发肿瘤的扩散张量成像(DTI)、扩散峰度成像(DKI)、平均表观传播子(MAP)和神经突方向离散度与密度成像(NODDI)。采用单变量和多变量逻辑回归分析确定HER2状态的潜在独立预测因素。通过受试者工作特征(ROC)曲线分析评估定量参数的判别能力,并在独立队列中进行验证。
在推导队列中,HER2阳性组和HER2阴性组之间的肿瘤大小、TIC类型和ADC值无差异(P = 0.126 - 0.961)。HER2阳性组中DSI定量参数,包括DKI的轴向峰度(DKI_AK)、非高斯性(MAP_NG)、轴向非高斯性(MAP_NG)、径向非高斯性(MAP_NG)、返回原点概率(MAP_RTOP)、MAP的返回轴概率(MAP_RTAP)以及NODDI的细胞内体积分数(NODDI_ICVF)均低于HER2阴性组(P≤0.001 - 0.035)。HER2阳性组中DSI定量参数,包括径向扩散率(DTI_RD)、DTI的平均扩散率(DTI_MD)、MAP的均方扩散(MAP_MSD)和MAP的q空间逆方差(MAP_QIV)高于HER2阴性组(P = 0.016 - 0.049)。ROC分析显示,推导队列和验证队列中ADC的曲线下面积(AUC)分别为0.632和0.568。推导队列和验证队列中DSI定量参数的AUC值分别为0.628至0.700和0.673至0.721。逻辑回归分析显示,只有NODDI_ICVF是HER2状态的独立预测因素(P = 0.001),在推导队列和验证队列中的AUC分别为0.700和0.721。
DSI有助于术前预测HER2,但仅靠DSI可能不足以术前预测乳腺癌患者的HER2状态。