体素内不相干运动直方图分析在区分HER2零表达、低表达和阳性乳腺癌中的附加价值
本研究回顾性纳入181例乳腺癌患者，评估IVIM直方图参数在常规BI-RADS评估之外区分HER2零表达、低表达和阳性的附加诊断价值。常规BI-RADS特征无法区分HER2零表达与低表达；联合模型在区分HER2低表达与阳性（AUC=0.727 vs 0.587）及零表达与阳性（AUC=0.730 vs 0.700）时优于常规模型。IVIM直方图参数（尤其D_Skewness和D_Entropy）与BI-RADS特征整合可提升HER2表达亚型的鉴别能力。
要点
- 常规BI-RADS特征无法区分HER2零表达与低表达乳腺癌。
- 联合D_Skewness和肿瘤大小可提升HER2低表达与阳性的鉴别（AUC 0.727 vs 0.587）。
- 联合D_Skewness、肿瘤大小和腋窝淋巴结状态可提升HER2零表达与阳性的鉴别（AUC 0.730 vs 0.700）。
诊断标准与关键数值
- HER2零表达与低表达比较：常规BI-RADS特征无法区分；D_Entropy显示中等区分度（AUC=0.569），但仅作描述性分析，未构建预测模型。
- HER2低表达与阳性比较：联合模型（含D_Skewness和肿瘤大小）AUC=0.727，显著高于常规模型（AUC=0.587）。
- HER2零表达与阳性比较：联合模型（D_Skewness、肿瘤大小和腋窝淋巴结状态）AUC=0.730，优于常规模型（肿瘤大小和腋窝淋巴结状态，AUC=0.700）。
局限性
- 回顾性单中心研究。
- HER2零表达与低表达比较仅作描述性分析，未构建预测模型。
以上解读依据论文摘要（全文未开放获取或许可不允许翻译转载）。
英文原文（摘要）· 点击展开
PURPOSE: Accurate differentiation of human epidermal growth factor receptor 2 (HER2)-zero, HER2-low, and HER2-positive breast cancer (BC) is crucial for guiding therapeutic decisions, particularly with the development of novel HER2-targeted treatments. This study aimed to evaluate whether intravoxel incoherent motion (IVIM) imaging histogram parameters could provide additional diagnostic value in distinguishing among these HER2 expression subtypes beyond conventional BI-RADS assessments.
MATERIALS AND METHODS: This retrospective single-center study included 181 breast cancer patients (30 HER2-zero, 107 HER2-low, and 44 HER2-positive). All patients underwent preoperative breast MRI on a 3.0-T scanner, including conventional sequences (T1-weighted, T2-weighted, dynamic contrast-enhanced and diffusion-weighted imaging) and intravoxel incoherent motion (IVIM) imaging. Histogram features derived from IVIM parameters-true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f)-were extracted and compared across the HER2 subgroups. Two diagnostic models were constructed: a conventional model based on BI-RADS features and a combined model incorporating both BI-RADS and IVIM histogram features. Statistical analyses included univariate logistic regression, Akaike information criterion (AIC), area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), net reclassification index (NRI), and DeLong test.
RESULTS: Conventional BI-RADS features alone could not distinguish between HER2-zero and HER2-low tumors. Although D_Entropy demonstrated modest discrimination (AUC = 0.569), this comparison was analyzed descriptively without constructing predictive models. Consequently, conventional and combined models were not constructed for this comparison. For HER2-low versus HER2-positive differentiation, the combined model (including D_Skewness and tumor size) achieved significantly higher performance (AUC = 0.727) than the conventional model (AUC = 0.587). Similarly, for HER2-zero versus HER2-positive, the combined model (D_Skewness, tumor size, and axillary lymph node [ALN] status) outperformed the conventional model (tumor size and ALN status), with AUCs of 0.730 versus 0.700. Improvements in diagnostic performance with the combined model were statistically confirmed by the DeLong test, NRI, and IDI metrics in the HER2-low versus HER2-positive and HER2-zero versus HER2-positive comparisons.
CONCLUSIONS: IVIM histogram parameters, particularly D_Skewness and D_Entropy, may enhance the ability to differentiate HER2 expression subtypes in breast cancer when integrated with conventional BI-RADS features. The combined model improves diagnostic performance, supporting its potential utility in refining HER2 status evaluation and optimizing personalized treatment strategies.
引用
- Chen S, Zhang Y, Chen Y, et al. Added value of intravoxel incoherent motion histogram analysis in differentiating HER2-zero, HER2-low, and HER2-positive breast cancer. Radiol Med. 2026. PMID: 42126725. doi:10.1007/s11547-026-02212-1
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