当前位置: X-MOL 学术Eur. Radiol. Exp. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Textural radiomic features and time-intensity curve data analysis by dynamic contrast-enhanced MRI for early prediction of breast cancer therapy response: preliminary data.
European Radiology Experimental ( IF 3.7 ) Pub Date : 2020-02-05 , DOI: 10.1186/s41747-019-0141-2
Roberta Fusco 1 , Vincenza Granata 1 , Francesca Maio 2 , Mario Sansone 3 , Antonella Petrillo 1
Affiliation  

Background

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.

Methods

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.

Results

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.

Conclusions

The standardised index of shape could become a clinical tool to differentiate, in the early stages of treatment, responding to non-responding patients.


中文翻译:

动态对比增强MRI的质地放射学特征和时间强度曲线数据分析,可早期预测乳腺癌治疗反应:初步数据。

背景

通过动态对比增强磁共振成像(DCE-MRI)研究早期定量预测乳腺癌新辅助治疗反应的潜力,以期将半定量时间强度曲线参数与动脉影像上的纹理放射特征相比较。

方法

回顾性研究了45例接受DCE-MRI检查的患者,这些数据包含在治疗开始之前和治疗第一个周期后(“ QIN乳腺DCE-MRI”和“ QIN-Breast”)进行的检查。总共提取了11个半定量参数和50个纹理特征。应用非参数测试,具有曲线下面积的接收器工作特性分析(ROC-AUC),Spearman相关系数以及带有Bonferroni校正的Kruskal-Wallis测试。

结果

分析了15例病理完全缓解(pCR)和30例非pCR患者。pCR患者和非pCR患者之间的中位值之间存在显着差异,包括纹理特征之间的熵,长期强调和忙度,动态半定量之间的最大信号差,冲洗斜率,洗涤斜率和形状标准化指数参数。标准化的形状指数具有最佳结果,ROC-AUC为0.93,可区分pCR非pCR患者。

结论

标准化的体形指数可能会成为临床工具,以在治疗的早期阶段区分对无反应的患者的反应。
更新日期:2020-02-05
down
wechat
bug