Department of Radiology, The Affiliated Beijing Friendship Hospital of Capital Medical University of China, Beijing, China.
Clin Breast Cancer. 2012 Apr;12(2):94-101. doi: 10.1016/j.clbc.2011.11.002. Epub 2011 Dec 13.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may have the potential of predicting response to neoadjuvant chemotherapy for patients with breast cancer. However, most of these studies focused on evaluating hot-spot characteristics. To thoroughly reflect tumor status, the cold spot and heterogeneity characteristics should also be evaluated.
DCE-MRIs from 60 patients newly diagnosed with primary invasive breast cancer were reviewed. Kinetic parameters (including cold spot, hot spot, and heterogeneity parameters) derived from DCE-MRI data were used to describe cold spot, hot spot, and heterogeneity features. Patients with a pathologic complete response (pCR) or a ductal carcinoma in situ with microinvasion after chemotherapy were categorized into the pCR group. Pretreatment kinetic parameters in the pCR and non-pCR groups were compared by using univariate tests. Binary logistic regression analysis was used to identify the independent predictors for pCR. The best cutoff value of the independent predictor at pretreatment, with which to differentiate between patients who had a pCR and a non-pCR, was calculated by using receiver operating characteristic curve analysis.
After chemotherapy, 10 (16.7%) patients were categorized into the pCR group and 50 (83.3%) into non-pCR group. Multivariate analysis showed that pretreatment washout slope at a cold spot (washout(C)) was the only significant and independent predictor of pCR (β = 26.128; P = .005). The best pretreatment washout(C) cutoff value with which to differentiate between patients who had pCR and those with non-pCR was 0.0277, which yielded a sensitivity of 80.0% (95% CI, 44.4%-97.5%) and a specificity of 74.0% (95% CI, 59.7%-85.4%).
Washout(C) may be used as a predictor for pCR in patients with breast cancer who undergo neoadjuvant chemotherapy.
动态对比增强磁共振成像（DCE-MRI）有可能预测乳腺癌患者新辅助化疗的反应。然而，大多数研究都集中在评估热点特征上。为了全面反映肿瘤状态，还应评估冷点和异质性特征。
回顾了 60 例新诊断为原发性浸润性乳腺癌患者的 DCE-MRI。从 DCE-MRI 数据中得出的动力学参数（包括冷点、热点和异质性参数）用于描述冷点、热点和异质性特征。化疗后病理完全缓解（pCR）或微浸润性导管原位癌的患者归入 pCR 组。通过单变量检验比较 pCR 和非 pCR 组患者的预处理动力学参数。采用二元逻辑回归分析识别 pCR 的独立预测因子。通过接受者操作特征曲线分析计算出独立预测因子在预处理时区分 pCR 和非 pCR 患者的最佳截断值。
化疗后，10 例（16.7%）患者归入 pCR 组，50 例（83.3%）归入非 pCR 组。多变量分析显示，冷点的预处理洗脱斜率（washout(C)）是 pCR 的唯一显著且独立的预测因子（β=26.128；P=.005）。区分 pCR 患者和非 pCR 患者的最佳预处理洗脱（washout(C)）截断值为 0.0277，其敏感性为 80.0%（95%CI，44.4%-97.5%），特异性为 74.0%（95%CI，59.7%-85.4%）。
washout(C) 可作为预测接受新辅助化疗的乳腺癌患者 pCR 的指标。
