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首页> 外文期刊>Abdominal radiology. >MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases
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MR texture analysis: potential imaging biomarker for predicting the chemotherapeutic response of patients with colorectal liver metastases

机译：MR纹理分析：用于预测结肠直肠肝转移患者的化学治疗响应的潜在成像生物标志物

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Purpose: The purpose of the study was to determine whether the pre-treated MR texture features of colorectal liver metastases (CRLMs) are predictive of therapeutic response after chemotherapy. Methods: The study included twenty-six consecutive patients (a total of 193 liver metastasis) with unre-spectable CRLMs at our institution from August 2014 to February 2016. Lesions were categorized into either responding group or non-responding group according to changes in size. Texture analysis was quantified on T2-weighted images by two radiologists with consensus on regions of interest which were manually drawn on the largest cross-sectional area of the lesions. Five histogram features (mean, variance, skewness, kurtosis, and entropy1) and five gray level co-occurrence matrix features (GLCM; angular second moment (ASM), entropy2, contrast, correlation, and inverse difference moment (IDM)) were extracted. The texture parameters were statistically analyzed to identify the differences between the two groups, and the potential predictive parameters to differentiate the responding group from the non-responding group were subsequently tested using multi-variable logistic regression analysis. Results: A total of 107 responding and 86 non-responding lesions were evaluated. A higher variance, entropy1, contrast, entropy2 and a lower ASM, correlation, IDM were independently (P < 0.05) associated with a good response to chemotherapy with the areas under the ROC curves (AUCs) of 0.602-0.784. Variance (P < 0.001) and ASM (P = 0.001) remained potential predictive values to discriminate responding lesions from non-responding lesions when tested using multivariable logistic regression analysis. The highest AUC of the predictors from the association of variance and ASM was 0.814. Conclusion: MR texture features on pre-treated T2 images have the potential to predict the therapeutic response of colorectal liver metastases.
机译：目的：该研究的目的是确定结肠直肠肝转移（CRLMS）预处理的先生纹理特征是在化疗后的治疗反应预测。方法：该研究包括从2014年8月到2016年8月到2016年2月在我们的机构中​​的二十六名连续患者（共193肝转移）。根据规模的变化，病变分为响应小组或非答复组。 。通过两个放射科医生在T2加权图像上量化纹理分析，该辐射学家在感兴趣的区域上被手动地在病变的最大横截面积上达成了共识。提取五个直方图特征（平均，方差，偏斜，血管增强矩阵和血液级共生矩阵特征（GLCM;角度第二矩（ASM），熵2，对比度，相关性和反差矩（IDM）） 。统计分析纹理参数以识别两组之间的差异，以及通过多变量逻辑回归分析进行随后测试从非响应组中区分响应组的潜在预测参数。结果：评估总共107次响应和86个无响应病变。较高的差异，熵1，对比度，熵2和较低的ASM，相关性，IDM独立地（P <0.05）与与0.602-0.784的ROC曲线（AUC）下的区域的良好反应相关。方差（P <0.001）和ASM（P = 0.001）仍然存在潜在的预测值，以在使用多变量逻辑回归分析测试时判断来自无响应病变的响应病变。来自变异关系和ASM的预测因子的最高AUC为0.814。结论：预处理T2图像上的MR纹理特征具有预测结肠直肠肝转移的治疗响应。

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