Contrast-Enhanced MRI Texture Parameters as Potential Prognostic Factors for Primary Central Nervous System Lymphoma Patients Receiving High-Dose Methotrexate-Based Chemotherapy
Contrast-Enhanced MRI Texture Parameters as Potential Prognostic Factors for Primary Central Nervous System Lymphoma Patients Receiving High-Dose Methotrexate-Based Chemotherapy
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DOI：
10.1155/2019/5481491
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发表时间：
2019-11-12
影响因子：
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通讯作者：
Ma, Xuelei
中科院分区：
文献类型：
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作者：
Chen, Chaoyue;Zhuo, Hongyu;Ma, Xuelei
导论.本研究的目的是评估对比增强磁共振成像（MRI）纹理特征对原发性中枢神经系统淋巴瘤（PCNSL）患者的预后价值。方法.在这项回顾性研究中，2010年10月至2017年3月入组了52例诊断为PCNSL的患者。在任何抗肿瘤治疗之前，通过对比增强T1加权成像检索基于直方图的矩阵（histo-）和灰度共生矩阵（GLCM）上的肿瘤组织的纹理特征。进行受试者工作特征曲线分析，以获得其最佳截止值，在此基础上，我们将患者分为亚组。采用Kaplan-Meier分析比较各亚组的总生存期（OS），并采用多因素考克斯回归分析确定各亚组是否可作为独立的预后因素。结果从MR图像中提取了10个纹理特征，包括基于直方图的矩阵的能量、熵、峰度、偏度，以及基于灰度共生矩阵的相关性、对比度、相异性、能量、熵和均匀性。其中三个（GLCM-对比度、GLCM-差异性和GLCM-同质性）与总生存期（OS）相关。多元考克斯回归分析表明，GLCM同质性可以作为独立的预测因素。结论.对比增强磁共振成像（MRI）的纹理特征可能作为PCNSL患者的预后生物标志物。
Introduction. The purpose of this study was to evaluate the prognostic value of texture features on contrast-enhanced magnetic resonance imaging (MRI) for patients with primary central nervous system lymphoma (PCNSL). Methods. In this retrospective study, fifty-two patients diagnosed with PCNSL were enrolled from October 2010 to March 2017. The texture feature of tumor tissue on the histogram-based matrix (histo-) and the grey-level co-occurrence matrix (GLCM) was retrieved by contrast-enhanced T1-weighted imaging before any antitumor treatment. Receiver operating characteristic curve analyses were performed to obtain their optimal cutoff values, based on which we dichotomized patients into subgroups. The Kaplan-Meier analyses were conducted to compare overall survival (OS) of subgroups, and multivariate Cox regression analyses were used to determine if they could be taken as independent prognostic factors. Results. Ten texture features were extracted from the MR image, including Energy, Entropy, Kurtosis, Skewness on the histogram-based matrix, and Correlation, Contrast, Dissimilarity, Energy, Entropy, and Homogeneity on the grey-level co-occurrence matrix. Three of them (GLCM-Contrast, GLCM-Dissimilarity, and GLCM-Homogeneity) are shown to be significant in relation to overall survival (OS). The multivariate Cox regression analyses suggest that GLCM-Homogeneity could be taken as independent predictors. Conclusions. The texture features of contrast-enhanced magnetic resonance imaging (MRI) could potentially serve as prognostic biomarkers for PCNSL patients.