18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma
18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma
复制标题
基于 F-18-FDG-PET 的放射组学特征可预测原发性弥漫性胶质瘤中 MGMT 启动子甲基化状态
DOI：
10.1186/s40644-019-0246-0
复制
发表时间：
2019-08-19
期刊：
影响因子：
4.9
通讯作者：
Ma, Wenbin
中科院分区：
文献类型：
--
作者：
Kong, Ziren;Lin, Yusong;Ma, Wenbin
背景：O-6-甲基鸟嘌呤-DNA甲基转移酶（MGMT）启动子的甲基化状态已成为胶质瘤中一个有利的独立预后和预测生物标志物。本研究旨在建立一种基于F-18-氟脱氧葡萄糖（FDG）正电子发射断层扫描（PET）的放射组学标记，用于无创测量胶质瘤中MGMT启动子甲基化状态。方法回顾性分析107例经病理证实的弥漫性胶质瘤患者，随机分为原发组（n = 71）和验证组（n = 36）。通过焦磷酸测序测量MGMT启动子甲基化状态。从标准摄取值（SUV）图上的三维感兴趣区域（ROI）中提取了总共1561个放射组学特征，这些标准摄取值（SUV）图是从原始F-18-FDG PET数据生成的。生成放射组学特征、临床特征和将临床和放射组学特征组合在一起的融合特征。通过受试者工作特征（ROC）曲线分析评估三种标记的性能，并基于MGMT启动子甲基化状态和具有最佳性能的标记对患者预后进行分层。结果选择5个放射组学特征构建放射组学特征，初步和验证队列的受试者工作特征（ROC）曲线下面积（AUC）分别达到0.94和0.86，优于临床特征和融合特征。中位随访时间为32.4个月，放射组学特征将胶质瘤患者分为两个风险组，具有显著差异（p = 0.04）。结论F-18-FDG-PET放射组学技术可用于胶质瘤MGMT基因启动子区甲基化状态的评估，并可无创性地预测胶质瘤患者的预后。
Background The methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter has emerged as a favorable independent prognostic and predictive biomarker in glioma. This study aimed to build a radiomics signature based on F-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) for noninvasive measurement of the MGMT promoter methylation status in glioma. Methods One hundred and seven pathology-confirmed primary diffuse glioma patients were retrospectively included and randomly assigned to the primary (n = 71) or validation cohort (n = 36). The MGMT promoter methylation status was measured by pyrosequencing. A total of 1561 radiomics features were extracted from the three-dimensional region of interest (ROI) on the standard uptake value (SUV) maps that were generated from the original F-18-FDG PET data. A radiomics signature, a clinical signature and a fusion signature that combined the clinical and radiomics features together were generated. The performance of the three signatures was evaluated by receiver operating characteristic (ROC) curve analysis, and the patient prognosis was stratified based on the MGMT promoter methylation status and the signature with the best performance. Results Five radiomics features were selected to construct the radiomics signature, and displayed the best performance with area under the receiver operating characteristic (ROC) curve (AUC) reaching 0.94 and 0.86 in the primary and validation cohorts, respectively, which outweigh the performances of clinical signature and fusion signature. With a median follow-up time of 32.4 months, the radiomics signature stratified the glioma patients into two risk groups with significantly different prognoses (p = 0.04). Conclusions F-18-FDG-PET-based radiomics is a promising approach for preoperatively evaluating the MGMT promoter methylation status in glioma and predicting the prognosis of glioma patients noninvasively.