Prediction of VEGF expression in extrahepatic cholangiocarcinoma based on MRI texture analysis

CHEN Xin; SHU Jian; HUANG Xinqiao; YANG Chunmei

doi:10.19732/j.cnki.2096-6210.2021.04.005

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Prediction of VEGF expression in extrahepatic cholangiocarcinoma based on MRI texture analysis

更新时间：2025-12-15

- Prediction of VEGF expression in extrahepatic cholangiocarcinoma based on MRI texture analysis
- Vol. 30, Issue 4, Pages: 257-262(2021)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.19732/j.cnki.2096-6210.2021.04.005
  CLC：
- Published Online：28 August 2021，
  
  Published：28 August 2021
- 稿件说明：
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陈馨,舒健,黄新荞,等. 基于MRI纹理分析预测肝外胆管癌中VEGF的表达[J]. 肿瘤影像学, 2021, 30(4): 257-262 https://doi.

org/10.19732/j.cnki.2096-6210.2021.04.005
陈馨,舒健,黄新荞,等. 基于MRI纹理分析预测肝外胆管癌中VEGF的表达[J]. 肿瘤影像学, 2021, 30(4): 257-262 https://doi. DOI： 10.19732/j.cnki.2096-6210.2021.04.005.

org/10.19732/j.cnki.2096-6210.2021.04.005 DOI：

摘要

目的：

探讨基于磁共振成像（magnetic resonance imaging，MRI）的纹理分析预测肝外胆管癌（extrahepatic cholangiocarcinoma，ECC）组织中血管内皮生长因子（vascular endothelial growth factor，VEGF）表达的价值。

方法：

回顾并分析经病理学检查证实的ECC患者70例，使用MaZda软件从MRI图像中提取纹理特征。筛选出最优纹理特征并将其纳入二元logistic回归模型进行分析。利用预测概率建立受试者工作特征（receiver operating characteristic，ROC）曲线评估预测效能。分析表观弥散系数（apparent diffusion coefficient，ADC）与VEGF表达的相关性。

结果：

最终有4个纹理特征符合标准并进行logistic回归分析，得出每例患者VEGF表达的预测概率。预测概率的ROC曲线的曲线下面积（area under cure，AUC）为0.708（

=0.003）。其诊断VEGF阳性的灵敏度、特异度、准确度分别为65.6%、78.9%、72.8%。VEGF阴性组及阳性组的ADC值分别为1 368.210

- 6

/s、1 292.210

- 6

/s，两组间差异无统计学意义（

=0.398）。

结论：

基于MRI的纹理分析有助于预测ECC的VEGF表达。

Abstract

Objective:

To explore the value of magnetic resonance imaging (MRI) based texture analysis in predicting the expression of vascular endothelial growth factor (VEGF) in extrahepatic cholangiocarcinoma (ECC).

Methods:

Seventy patients with ECC confirmed by pathology were retrospectively analyzed. The texture features w

ere extracted from MRI images using Mazda software. After texture feature selection

binary logistic regression analysis was performed. Receiver operating characteristic (ROC) curve was established to evaluate the prediction efficiency. The correlation between apparent diffusion coefficient (ADC) and VEGF expression was analyzed.

Results:

Four texture features met the standard

and logistic regression analysis was performed to obtain the prediction probability of VEGF expression in each patient. The area under curve (AUC) of prediction probability was 0.708 (

=0.003). The sensitivity

specificity and accuracy were 65.6%

78.9% and 72.8%

respectively. The ADC values of VEGF negative group and VEGF positive group were 1 368.210

- 6

/s and 1 292.210

- 6

respectively. There was no significant difference between the two groups (

=0.398).

Conclusion:

MRI based texture analysis is helpful to predict the expression of VEGF in ECC.

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