Radiomics and MGMT promoter methylation for prognostication of newly diagnosed glioblastoma
Radiomics and MGMT promoter methylation for prognostication of newly diagnosed glioblastoma
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DOI：
10.1038/s41598-019-50849-y
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发表时间：
2019-10-08
影响因子：
4.6
通讯作者：
Kanemura, Yonehiro
中科院分区：
文献类型：
--
作者：
Sasaki, Takahiro;Kinoshita, Manabu;Kanemura, Yonehiro
我们试图建立一个基于磁共振成像（MRI）的放射学模型，用于对新诊断的胶质母细胞瘤（GBM）患者的预后亚组进行分层，并预测肿瘤的O(6)-甲基鸟嘌呤- dna甲基转移酶启动子甲基化（pMGMT-met）状态。本研究纳入了201例新诊断的GBM患者的术前MRI扫描。共收集了162个数据集的一阶特征、二阶特征和182个数据集的位置数据共489个纹理特征。使用监督主成分分析进行预测，并基于最小绝对收缩和选择算子回归对pmgmt -满足状态进行预测建模。利用与预后相关的22个放射学特征成功地将患者分为高危组和低危组（p = 0.004， Log-rank检验）。放射学的高、低危险分层和pMGMT状态是独立的预后因素。事实上，当用两个重要的放射学特征建模时，pMGMT甲基化状态的预测准确性为67%。合并高危组、合并中危组（由放射组低危且pmgmt未达标或放射组高风险且pmgmt未达标组成）和合并低危组的生存率差异有统计学意义（p = 0.0003， Log-rank检验）。放射组学可以用来建立一个预后评分，对高、低风险GBM进行分层，这是一个独立于pMGMT甲基化状态的预后因素。另一方面，放射组学分析对pMGMT甲基化状态的预测准确性不足以用于实际应用。
We attempted to establish a magnetic resonance imaging (MRI)-based radiomic model for stratifying prognostic subgroups of newly diagnosed glioblastoma (GBM) patients and predicting O (6)-methylguanine-DNA methyltransferase promotor methylation (pMGMT-met) status of the tumor. Preoperative MRI scans from 201 newly diagnosed GBM patients were included in this study. A total of 489 texture features including the first-order feature, second-order features from 162 datasets, and location data from 182 datasets were collected. Supervised principal component analysis was used for prognostication and predictive modeling for pMGMT-met status was performed based on least absolute shrinkage and selection operator regression. 22 radiomic features that were correlated with prognosis were used to successfully stratify patients into high-risk and low-risk groups (p = 0.004, Log-rank test). The radiomic high- and low-risk stratification and pMGMT status were independent prognostic factors. As a matter of fact, predictive accuracy of the pMGMT methylation status was 67% when modeled by two significant radiomic features. A significant survival difference was observed among the combined high-risk group, combined intermediate-risk group (this group consists of radiomic low risk and pMGMT-unmet or radiomic high risk and pMGMT-met), and combined low-risk group (p = 0.0003, Log-rank test). Radiomics can be used to build a prognostic score for stratifying high- and low-risk GBM, which was an independent prognostic factor from pMGMT methylation status. On the other hand, predictive accuracy of the pMGMT methylation status by radiomic analysis was insufficient for practical use.