论著摘要 |【MR】低级别神经胶质瘤中突变型和野生型异柠檬酸脱氢酶1之间的解剖位置差异(双语版)

2017-09-22 10:31:47 admin 2

Anatomical location differences between mutated and wild-type isocitrate dehydrogenase 1 in low-grade gliomas.

发表日期: 2017.01.06   来源: International Journal of Neuroscience, 2017: 1-8.

作者

Yu, J., Shi, Z., Ji, C., Lian, Y., Wang, Y., Chen, L., Mao, Y.  

作者介绍:

Jinhua Yu

Department of Electronic Engineering, Fudan University, Shanghai, China; Key laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China. Correspondence: jhyu@fudan.edu.cn

Zhifeng Shi

Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.

Chunhong Ji, Yuxi Lian, Yuanyuan Wang

Department of Electronic Engineering, Fudan University, Shanghai, China.  Correspondence: yywang@fudan.edu.cn

Liang Chen

Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.

Correspondence: clclcl95@sina.com

Ying Mao

Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China

 

摘要

神经胶质瘤的解剖位置被认为是在肿瘤生长期间影响特异性前体细胞的一个因素。异柠檬酸脱氢酶1IDH1)是一种对神经胶质瘤发展有重要影响的病理生物标志物,具有显著的预后作用。本研究定量分析了低级别胶质瘤肿瘤解剖位置与IDH1状态之间的相关性。本研究纳入了92例诊断为低级别神经胶质瘤的患者,其中65IDH1突变型胶质瘤患者,27例野生型IDH1胶质瘤患者。设计卷积神经网络从三维磁共振成像图像中分割肿瘤。然后采用基于体素的病变征象来研究具有突变型和野生型IDH1的胶质瘤之间的肿瘤位置分布差异。为了定量表征位置差异,使用自动解剖标记图谱将标准脑图谱分成116个解剖学兴趣体(AVOI)。计算并比较了116个解剖学兴趣体(AVOI)不同IDH1状态的肿瘤的百分比。基于每个患者的116个位置特征,使用支持向量机和AdaBoost算法来估计IDH1状态。实验结果证明,定量肿瘤位置测量可能是基于神经胶质瘤影像组学分析的生物标志物估计中非常重要的一组成像特征。

 

Abstract

Anatomical location of gliomas has been considered as a factor implicating the contributions of a specific precursor cells during the tumor growth. Isocitrate dehydrogenase 1 (IDH1) is a pathognomonic biomarker with a significant impact on the development of gliomas and remarkable prognostic effect. The correlation between anatomical location of tumor and IDH1 states for low-grade gliomas was analyzed quantitatively in this study. Ninety-two patients diagnosed of low-grade glioma pathologically were recruited in this study, including 65 patients with IDH1-mutated glioma and 27 patients with wide-type IDH1. A convolutional neural network was designed to segment the tumor from three-dimensional magnetic resonance imaging images. Voxel-based lesion symptom mapping was then employed to study the tumor location distribution differences between gliomas with mutated and wild-type IDH1. In order to characterize the location differences quantitatively, the Automated Anatomical Labeling Atlas was used to partition the standard brain atlas into 116 anatomical volumes of interests (AVOIs). The percentages of tumors with different IDH1 states in 116 AVOIs were calculated and compared. Support vector machine and AdaBoost algorithms were used to estimate the IDH1 status based on the 116 location features of each patient. Experimental results proved that the quantitative tumor location measurement could be a very important group of imaging features in biomarker estimation based on radiomics analysis of glioma.

 

 关键词:

低级别胶质瘤,解剖学定位,异柠檬酸脱氢酶1,核磁共振,图像分析

KEYWORDS:

Low-grade glioma, anatomic location, IDH1, MRI, image analysis

阅读原文:http://dx.doi.org/10.1080/00207454.2016.1270278

 


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