磁共振动态对比增强不同后处理模型在脑胶质瘤分级中的应用

陈鹏; 康厚艺; 张乐天; 李晓光; 郭广阔; 张伟国

doi:10.16016/j.1000-5404.202106043

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磁共振动态对比增强不同后处理模型在脑胶质瘤分级中的应用

神经科学 | 更新时间：2026-01-09

- 磁共振动态对比增强不同后处理模型在脑胶质瘤分级中的应用
- Application of different post-processing modes of dynamic contrast enhanced magnetic resonance imaging in glioma grading
- 第三军医大学学报 2021年43卷第23期页码：2577-2583
- 作者机构：
  
  400042 重庆，陆军军医大学(第三军医大学)大坪医院放射科
- 作者简介：
  
  [张伟国，E-mail: wgzhang01@163.com ZHANG Weiguo, E-mail: wgzhang01@163.com
- 基金信息：
  
  国家重点研发计划(2018YFC0115004);国家自然科学基金面上项目(81871421);重庆市影像医学与核医学临床研究中心科技计划项目(CSTC2015YFPT-gcjsyjzx0175)
- DOI：10.16016/j.1000-5404.202106043
  中图分类号： R445.2;R730.42;R739.41
- 收稿：2021-06-06，
  
  修回：2021-07-07，
  
  纸质出版：2021-12-15
- 稿件说明：
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陈鹏, 康厚艺, 张乐天, 等. 磁共振动态对比增强不同后处理模型在脑胶质瘤分级中的应用[J]. 第三军医大学学报, 2021,43(23):2577-2583.

Peng CHEN, Houyi KANG, Letian ZHANG, et al. Application of different post-processing modes of dynamic contrast enhanced magnetic resonance imaging in glioma grading[J]. Journal of Third Military Medical University, 2021, 43(23): 2577-2583.
陈鹏, 康厚艺, 张乐天, 等. 磁共振动态对比增强不同后处理模型在脑胶质瘤分级中的应用[J]. 第三军医大学学报, 2021,43(23):2577-2583. DOI： 10.16016/j.1000-5404.202106043.

Peng CHEN, Houyi KANG, Letian ZHANG, et al. Application of different post-processing modes of dynamic contrast enhanced magnetic resonance imaging in glioma grading[J]. Journal of Third Military Medical University, 2021, 43(23): 2577-2583. DOI： 10.16016/j.1000-5404.202106043.

摘要

目的

探讨磁共振动态对比增强(dynamic contrast enhanced magnetic resonance imaging，DCE-MRI) 的不同后处理模型[Tissue-4D和Omni-Kinetics(OK)软件]在鉴别脑胶质瘤不同级别中的价值。

方法

收集本院2013年1月至2019年7月共89例经术后病理证实的胶质瘤患者

其中Ⅱ级29例、Ⅲ级24例、Ⅳ级36例。患者均于术前行DCE-MRI检查，分别用Tissue-4D及OK后处理软件获得相应参数值。运用单因素方差分析比较不同级别胶质瘤参数差异，Spearman等级相关分析不同参数与胶质瘤分级的相关性，受试者工作特征(receiver operating characteristic，ROC)曲线分析各参数的曲线下面积(area under the curve，AUC)。

结果

两种后处理模型热点分析的Ktrans值、Tissue-4D的iAUC值和OK的Vp值在不同级别胶质瘤间差异均有统计学意义(

0.05)，Ⅳ级胶质瘤的Kep值低于Ⅱ级(

0.05)，Ⅳ级和Ⅲ级胶质瘤的Ve值高于Ⅱ级(

0.05)。Ktrans参数AUC值为0.949(Ⅱ级

Ⅳ级，

0.01)，诊断效能最高。Ktrans(OK)与胶质瘤级别之间相关性最强(

=0.775，

0.01)。OK软件直方图参数，Ktrans值的第50百分位数(50th)，Ve值的平均值、第75百分位数(75th)、第90百分位数(90th)

Kep值的平均值、熵、50th及Vp值的平均值在鉴别Ⅱ级与Ⅲ级、Ⅱ级与Ⅳ级间差异均具有统计学意义(

0.05)，Vp值的能量、熵、50th、75th、90th及Kep值的能量，在鉴别Ⅱ级与Ⅳ级、Ⅲ级与Ⅳ级间的差异均具有统计学意义(

0.05)。

结论

两种模型热点分析的Ktrans值及Ve值对胶质瘤分级均有较高的诊断效能，OK软件中直方图分析较热点分析参数更丰富、更全面。

Abstract

Objective

To explore the diagnostic values of different post-processing modes of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in the differentiation of glioma grade.

Methods

A total of 89 patients with glioma confirmed by postoperative pathology in our hospital from January 2013 to July 2019 were enrolled

including 29 patients of gradeⅡ

24 of grade Ⅲ and 36 of grade Ⅳ. All patients underwent preoperative DCE-MRI examination

and corresponding parameters were collected and processed using post-processing software Tissue-4D and Omni-Kinetics (OK) respectively. One-way ANOVA was adopted to compare the differences of the obtained parameters among glioma of different grades. Spearman rank correlation analysis was performed to analyze the correlation between each parameter and glioma grade

and receiver operating characteristic (ROC) curve was used to evaluate the area under the curve (AUC) of each parameter.

Results

In hot spot analysis

the Ktrans values of both post-processing modes

as well as the iAUC value of Tissue-4D and the Vp value of OK were all significantly different among glioma of different grades (

0.05). The Kep value of grade Ⅳ glioma was obviously lower than that of grade Ⅱ glioma (

0.05)

while the Ve values of grade Ⅳ and Ⅲ tumors were notably higher than that of gradeⅡ one (

0.05).

The AUC value of Ktrans (Tissue-4D) was 0.949 in the differentiation of gradeⅡ from grade Ⅳ glioma (

0.01)

indicating the highest diagnostic efficiency

and the correlation between Ktrans (OK) and glioma grade was the highest (

=0.775

0.01). In the histogram analysis of OK

the 50th percentile of Ktrans value

the mean and the 75th and 90th percentiles of Ve value

the mean

entropy and the 50th percentile of Kep value

as well as the mean value of Vp showed significances in the differentiation of grade Ⅱ from grade Ⅲ and grade Ⅱ from grade Ⅳ glioma (

0.05). Moreover

the energy

entropy and 50th

75th

90th percentiles of Vp value

and the energy of Kep value were statistically different in the identification of grade Ⅳ from grade Ⅱ and grade Ⅳ from grade Ⅲ (

0.05).

Conclusion

The Ktrans and Ve values of the 2 post-processing modes have rather high diagnostic efficiency for glioma grading in the hotspot analysis

and the histogram analysis of OK software involves more abundant and comprehensive parameters.

关键词

Keywords

references

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