Value of Dynamic Contrast-Enhanced (DCE) MRI in Predicting Response to Foam Sclerotherapy of Venous Malformations
Value of Dynamic Contrast-Enhanced (DCE) MRI in Predicting Response to Foam Sclerotherapy of Venous Malformations
复制标题
动态对比增强 (DCE) MRI 在预测静脉畸形泡沫硬化治疗反应中的价值
DOI：
10.1002/jmri.27657
复制
发表时间：
2021-05-15
影响因子：
4.4
通讯作者：
Tao, Xiaofeng
中科院分区：
文献类型：
--
作者：
Xia, Zhipeng;Gu, Hao;Tao, Xiaofeng
背景：DCE-MRI可以实现对静脉畸形的术前影像评估和泡沫硬化治疗效果的预测，但缺乏详细的定量分析。目的评价DCE-MRI在预测静脉畸形泡沫硬化治疗效果中的价值。平均年龄+/-SD，15.4+/-13.0岁)。场强/序列3Tesla MRI三维T-1加权体积内插身体检查。根据泡沫硬化治疗的反应将接受DCE-MRI治疗的患者分为有效组和无效组。对其临床特征和形态特征进行评价。根据感兴趣区(ROI)和感兴趣体积(VOI)获得最大强度时间比(MITR)、增强率(ER)和斜率(Slope)等半定量参数。这些参数的四分位数和平均值从VOI获得，平均值(#)表示从ROI获得。建立两个预测模型，分别基于ROI和VOI。模型1基于形态参数和ROI半定量参数，模型2基于形态参数和VOI半定量参数。统计分析采用Mann-Whitney U检验、Cohen‘s kappa、多元逐步Logistic回归分析和ROC分析。结果两组的病变分类、静脉血栓的存在、VOI的半定量参数(四分位数和MITR均值)、ROI的半定量参数(斜率(均值)(#)、MITR均值(#))均有显著差异。多变量二元Logistic回归分析表明，病变分类(P=0.002)和MITR平均数(P=0.027)是模型1疗效差的独立预测因素。对于模型2，病变分类(P=0.006)和MITR25(P=0.001)是独立的预测因素。基于VOI的预测模型(AUC=0.961)优于基于ROI的预测模型(AUC=0.909)。数据结论DCE-MRI在预测泡沫硬化治疗的疗效方面具有较好的应用前景。基于VOI的整体损伤模型表现出更好的性能，并可以指导未来的手术方法。证据级别3技术疗效阶段4
Background Preoperative imaging assessment of venous malformations (VMs) and prediction of foam sclerotherapy efficacy might be achievable by DCE-MRI but elaborate quantitive analysis was absent.Purpose To evaluate the value of DCE-MRI in predicting the effectiveness of foam sclerotherapy in VMs.Study Type Retrospective.Population Fifty-five patients (M:F = 17:38; mean age +/- SD, 15.4 +/- 13.0 years) with VMs.Field Strength/Sequence Three Tesla MRI with 3D T-1-weighted volume interpolated body examination.Assessment Patients who underwent pretreatment DCE-MRI were divided into "effective" and "ineffective" groups according to the response to foam sclerotherapy. Clinical characteristics and morphologic features were assessed. The semiquantitative parameters, such as maximum intensity time ratio (MITR), enhancement ratio (ER), and Slope, were obtained from ROI and volume of interest (VOI). The quartile and mean values of these parameters were acquired from VOI, while mean values denoted as Mean(#) were acquired from ROI. Establishment of two predictive models was based on ROI and VOI respectively. Model 1 was based on morphologic parameters and ROI semiquantitative parameters, while model 2 was based on morphologic parameters and VOI semiquantitative parameters.Statistical Analysis Mann-Whitney U-test, Cohen's kappa, multivariate logistic regression analysis (backward stepwise), and ROC analyses.Results The lesion classification, presence of phlebolith, semiquantitative parameters of VOI (quartile and mean of MITR), and semiquantitative parameters of ROI (Slope(mean)(#), MITRmean#) were significantly different between two groups. Lesion classification (P = 0.002) and MITRmean# (P = 0.027) were independent predictors for poor efficacy in model 1 as determined by multivariate binary logistic regression analysis. For model 2, lesion classification (P = 0.006) and MITR25 (P = 0.001) were independent predictors. The predictive model based on VOI (AUC = 0.961) performed better than that based on ROI (AUC = 0.909) in predicting therapeutic response.Data Conclusion DCE-MRI is promising in predicting the response to foam sclerotherapy for VMs. The whole lesion VOI-based model showed better performance and could instruct surgical approach in the future.Evidence Level 3Technical Efficacy Stage 4