为了确定常规DWI，连续时间随机游走（CTRW），分数阶微积分（FROC）和拉伸指数模型（SEM）在区分乳腺癌（BC）中的人表皮生长因子受体2（HER2）状态的价值。本前瞻性研究纳入了158名进行DWI，CTRW，FROC和SEM的女性，并根据病理学进行了分类，分为HER2零表达组（n = 10），HER2低表达组（n = 86）和HER2过表达组（n = 62）。从四种扩散模型中得出了九个扩散参数，即ADC，αCTRW，βCTRW，DCTRW，βFROC，DFROC，μFROC，αSEM和DDCSEM。比较了这些扩散度量和临床病理特征在不同组之间的差异。应用logistic回归确定最佳扩散度量和临床病理变量以分类HER2表达状态。采用受试者工作特征曲线（ROC曲线）评估它们的区分能力。雌激素受体（ER）状态，孕激素受体（PR）状态和肿瘤大小在HER2低表达组和HER2过表达组之间存在差异（p < 0.001至p = 0.009）。HER2低表达的BC中αCTRW，DCTRW，βFROC，DFROC，μFROC，αSEM和DDCSEM明显低于HER2过表达的BC（p < 0.001至p = 0.01）。进一步的多变量logistic回归分析显示，αCTRW是单一最佳区分度量，其曲线下面积（AUC）高于ADC（0.802 vs. 0.610，p < 0.05）加入ER状态、PR状态和肿瘤大小使AUC提高到0.877.αCTRW有助于区分HER2低表达和HER2过表达的BC。对HER2低表达的乳腺癌（BC）的预测对于适当的治疗非常重要。先进的连续时间随机游走扩散MRI提供了解决这个临床问题的方法。• HER2低表达BC的αCTRW，DCTRW，βFROC，DFROC，μFROC，αSEM和DDCSEM值较HER2过表达乳腺癌低。• αCTRW是区分HER2低表达和HER2过表达乳腺癌的最佳扩散度量（AUC = 0.802）。• 将αCTRW添加到临床病理特征（雌激素受体状态，孕激素受体状态和肿瘤大小）可以进一步提高区分能力。© 2023. 作者授权给欧洲放射学会。

To determine the value of conventional DWI, continuous-time random walk (CTRW), fractional order calculus (FROC), and stretched exponential model (SEM) in discriminating human epidermal growth factor receptor 2 (HER2) status of breast cancer (BC).This prospective study included 158 women who underwent DWI, CTRW, FROC, and SEM and were pathologically categorized into the HER2-zero-expressing group (n = 10), HER2-low-expressing group (n = 86), and HER2-overexpressing group (n = 62). Nine diffusion parameters, namely ADC, αCTRW, βCTRW, DCTRW, βFROC, DFROC, μFROC, αSEM, and DDCSEM of the primary tumor, were derived from four diffusion models. These diffusion metrics and clinicopathologic features were compared between groups. Logistic regression was used to determine the optimal diffusion metrics and clinicopathologic variables for classifying the HER2-expressing statuses. Receiver operating characteristic (ROC) curves were used to evaluate their discriminative ability.The estrogen receptor (ER) status, progesterone receptor (PR) status, and tumor size differed between HER2-low-expressing and HER2-overexpressing groups (p < 0.001 to p = 0.009). The αCTRW, DCTRW, βFROC, DFROC, μFROC, αSEM, and DDCSEM were significantly lower in HER2-low-expressing BCs than those in HER2-overexpressing BCs (p < 0.001 to p = 0.01). Further multivariable logistic regression analysis showed that the αCTRW was the single best discriminative metric, with an area under the curve (AUC) being higher than that of ADC (0.802 vs. 0.610, p < 0.05); the addition of ER status, PR status, and tumor size to the αCTRW improved the AUC to 0.877.The αCTRW could help discriminate the HER2-low-expressing and HER2-overexpressing BCs.Human epidermal growth factor receptor 2 (HER2)-low-expressing breast cancer (BC) might also benefit from the HER2-targeted therapy. Prediction of HER2-low-expressing BC or HER2-overexpressing BC is crucial for appropriate management. Advanced continuous-time random walk diffusion MRI offers a solution to this clinical issue.• Human epidermal receptor 2 (HER2)-low-expressing BC had lower αCTRW, DCTRW, βFROC, DFROC, μFROC, αSEM, and DDCSEM values compared with HER2-overexpressing breast cancer. • The αCTRW was the single best diffusion metric (AUC = 0.802) for discrimination between the HER2-low-expressing and HER2-overexpressing breast cancers. • The addition of αCTRW to the clinicopathologic features (estrogen receptor status, progesterone receptor status, and tumor size) further improved the discriminative ability.© 2023. The Author(s), under exclusive licence to European Society of Radiology.