The value of texture analysis of T2WI in differential diagnosis between nasopharyngeal carcinoma and nasopharyngeal hyperplasia

YUAN Hu; YE Jing; CAI Junhui; WU Yawei; XU Qing

doi:10.19732/j.cnki.2096-6210.2020.01.006

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The value of texture analysis of T2WI in differential diagnosis between nasopharyngeal carcinoma and nasopharyngeal hyperplasia

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- The value of texture analysis of T2WI in differential diagnosis between nasopharyngeal carcinoma and nasopharyngeal hyperplasia
- Vol. 29, Issue 1, Pages: 27-31(2020)
- 作者机构：
  
  1. 大连医科大学第二临床学院,辽宁,大连,116044
  2. 苏北人民医院影像科,江苏,扬州,225001
- 作者简介：
- 基金信息：
- DOI：10.19732/j.cnki.2096-6210.2020.01.006
  CLC：
- Published Online：28 February 2020，
  
  Published：28 February 2020
- 稿件说明：
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袁虎,叶靖,蔡俊辉,等. 基于T2WI图像的纹理分析对鼻咽癌与鼻咽部炎性增生性疾病的鉴别诊断价值[J]. 肿瘤影像学, 2020, 29(1): 27-31 https://doi.

org/10.19732/j.cnki.2096-6210.2020.01.006
袁虎,叶靖,蔡俊辉,等. 基于T2WI图像的纹理分析对鼻咽癌与鼻咽部炎性增生性疾病的鉴别诊断价值[J]. 肿瘤影像学, 2020, 29(1): 27-31 https://doi. DOI： 10.19732/j.cnki.2096-6210.2020.01.006.

org/10.19732/j.cnki.2096-6210.2020.01.006 DOI：

摘要

目的：

探讨磁共振T2WI图像纹理分析鉴别鼻咽癌（nasopharyngeal carcinoma，NPC）与鼻咽部炎性增生（nasopharyngeal hyperplasia，NPH）的价值。

方法：

收集经手术及病理学检查证实为NPC和NPH的患者共48例，均经过磁共振成像（magnetic resonance imaging，MRI）检查，其中NPC 30例，NPH 18例。应用MaZda软件对两组病灶进行纹理分析，在T2WI图像上选取病灶范围最大层面勾画感兴趣区（region of interest，ROI），测得294组参数，进行统计学分析。最后，利用多参数联合鉴别NPC和NPH。

结果：

两组间S（0，5）熵、S（5，5）熵、S（5，-5）熵、45方向游程长不均匀度、135方向游程长不均匀度、梯度偏度及小波低高频转换系数s-3等7组参数差异有统计学意义（

＜0.05），其中135方向游程长不均匀度、梯度偏度及小波低高频转换系数s-3这3组参数曲线下面积（area under curve，AUC）分别为0.759、0.803及0.731，诊断准确率中等。另外，分析发现，135方向游程长不均匀度联合梯度偏度、梯度偏度联合小波低高频转换系数s-3鉴别两组病变的诊断效能分别为0.824和0.833，诊断准确率较单一参数高。

结论：

基于磁共振T2WI序列的纹理分析可用于鉴别NPC和NPH性疾病。

Abstract

Objective:

To evaluate the value of texture analysis derived from T2WI in differential diagnosis between nasopharyngeal carcinoma (NPC) and nasopharyngeal hyperplasia (NPH).

Methods:

Forty-eight cases of NPC and NPH confirmed by operation and pathology were analyzed retrospectively. All of them were examined by magnetic resonance im

aging (MRI). Thirty cases were NPC and 18 cases were NPH. Two groups of lesions were analyzed by MaZda software. A total of groups of parameters were obtained by selecting the largest layer of the lesion on the T2WI image and measuring the parameters of the region of interest (ROI). Finally

multi-parameter combination were used to identify NPC and NPH.

Results:

The seven parameters of S(0

5) Entropy

S(5

5) Entropy

S(5

-5) Entropy

45dgr_RLNonUni

135dr_RLNonUni

GrSkewness and WavEnLH_s-3 were of statistical significance between the two groups (

＜0.05)

among which

the area under curve (AUC) of 135dr_RLNonUni

GrSkewness and WavEnLH_s-3 were 0.759

0.803 and 0.731

respectively

and the diagnostic accuracy was at a moderate level. In addition

the two- parameter combined analysis of this study found that the diagnostic efficacy of 135dr_RLNonUni + GrSkewness and GrSkewness + WavEnLH_s-3 in the identification of two groups of lesions were 0.824 and 0.833

respectively

and contrast to the single parameter

the accuracy of combined analysis of two parameters was better.

Conclusion:

Texture analysis of T2WI can be used to identify NPC and NPH.

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