Radiology Division, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale, Via Mariano Semmola, Naples, Italy.
Radiology Division, Universita' Degli Stui di Napoli Federico II, Via Pansini, Naples, Italy.
Eur Radiol Exp. 2020 Feb 5;4(1):8. doi: 10.1186/s41747-019-0141-2.
To investigate the potential of semiquantitative time-intensity curve parameters compared to textural radiomic features on arterial phase images by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for early prediction of breast cancer neoadjuvant therapy response.
A retrospective study of 45 patients subjected to DCE-MRI by public datasets containing examination performed prior to the start of treatment and after the treatment first cycle ('QIN Breast DCE-MRI' and 'QIN-Breast') was performed. In total, 11 semiquantitative parameters and 50 texture features were extracted. Non-parametric test, receiver operating characteristic analysis with area under the curve (ROC-AUC), Spearman correlation coefficient, and Kruskal-Wallis test with Bonferroni correction were applied.
Fifteen patients with pathological complete response (pCR) and 30 patients with non-pCR were analysed. Significant differences in median values between pCR patients and non-pCR patients were found for entropy, long-run emphasis, and busyness among the textural features, for maximum signal difference, washout slope, washin slope, and standardised index of shape among the dynamic semiquantitative parameters. The standardised index of shape had the best results with a ROC-AUC of 0.93 to differentiate pCR versus non-pCR patients.
The standardised index of shape could become a clinical tool to differentiate, in the early stages of treatment, responding to non-responding patients.
通过动态对比增强磁共振成像（DCE-MRI）研究动脉期图像纹理放射组学特征与半定量时间-强度曲线参数在预测乳腺癌新辅助治疗反应中的潜在价值。
对接受 DCE-MRI 检查的 45 例患者进行回顾性研究，这些患者的检查数据来自包含治疗前和治疗第一个周期后检查的公共数据集（“QIN Breast DCE-MRI”和“QIN-Breast”）。共提取了 11 个半定量参数和 50 个纹理特征。应用非参数检验、曲线下面积（ROC-AUC）的接收者操作特征分析、Spearman 相关系数和 Kruskal-Wallis 检验及 Bonferroni 校正。
分析了 15 例病理完全缓解（pCR）患者和 30 例非 pCR 患者。在纹理特征中，pCR 患者和非 pCR 患者之间的中位数差异具有统计学意义的特征有熵、长运行强调和繁忙度；在动态半定量参数中，最大信号差异、洗脱斜率、洗脱斜率和形状标准化指数具有统计学意义。形状标准化指数在区分 pCR 与非 pCR 患者方面的 ROC-AUC 最佳，为 0.93。
在治疗早期，形状标准化指数可能成为区分有反应和无反应患者的临床工具。
