多池化学交换饱和转移（CEST）及基于CEST的pH评估作为胶质瘤分级、异柠檬酸脱氢酶（IDH）突变、1p/19q共缺失和胶质瘤中O6-甲基鸟嘌呤-DNA甲基转移酶（MGMT）启动子甲基化的预测工具。
Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas.
作者信息
Zhang Xinli, Lu Jue, Liu Xiaoming, Sun Peng, Qin Qian, Xiang Zhengdong, Cheng Lan, Zhang Xiaoxiao, Guo Xiaotong, Wang Jing
机构信息
Department of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Clinical & Technical Solutions, Philips Healthcare, Beijing, China.
出版信息
Front Oncol. 2024 Dec 20;14:1507335. doi: 10.3389/fonc.2024.1507335. eCollection 2024.
OBJECTIVES
To comprehensively and noninvasively predict glioma grade, IDH mutation status, 1p/19q codeletion status, and MGMT promoter methylation status using chemical exchange saturation transfer (CEST)-based tumor pH assessment and metabolic profiling.
METHODS
We analyzed 128 patients with pathologically confirmed adult diffuse glioma. CEST-derived metrics based on tumor regions were obtained using five-pool Lorentzian analysis and pH_weighted analysis. Histogram features of these metrics were computed to characterize tumor heterogeneity. These features were subsequently employed for glioma grading and molecular genotyping of IDH, 1p/19q and MGMT. Logistic regression analysis was used to predict the grade and IDH genotypes. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis.
RESULTS
The DS, MT and pH_weighted differed significantly between grade II and III, as well as grade III and IV. The amide, NOE, pH_weighted and MTR showed significantly differences within IDH genotypes. Regression models achieved the highest AUC for differentiating grade II from III (0.80, 95% CI: 0.64-0.91), grade III from IV (0.83, 95% CI: 0.74-0.90), and IDH mutant from wild status (0.84, 95% CI: 0.77-0.90). MT and pH_weighted metrics were the only indicators for identifying 1p/19q codeletion in grade II and grade III gliomas, respectively. MT 90th percentile (0.87, 95% CI: 0.65-0.98) and pH_weighted 25th percentile (0.83, 95% CI: 0.56-0.97) showed the best performance, respectively. The MTR was the only indicator which can distinguish MGMT promoter methylation and unmethylation gliomas, within MTR 90th percentile performed best (AUC = 0.79, 95% CI: 0.61- 0.91).
CONCLUSION
CEST-based tumor pH assessment and metabolic profiling demonstrated promising potential for predicting glioma grade, IDH mutation status, 1p/19q codeletion, and MGMT genotype.
目的
使用基于化学交换饱和转移（CEST）的肿瘤pH评估和代谢谱分析，全面且无创地预测胶质瘤分级、异柠檬酸脱氢酶（IDH）突变状态、1p/19q共缺失状态和O6-甲基鸟嘌呤-DNA甲基转移酶（MGMT）启动子甲基化状态。
方法
我们分析了128例经病理证实的成人弥漫性胶质瘤患者。基于肿瘤区域的CEST衍生指标通过五池洛伦兹分析和pH加权分析获得。计算这些指标的直方图特征以表征肿瘤异质性。随后将这些特征用于胶质瘤分级以及IDH、1p/19q和MGMT的分子基因分型。采用逻辑回归分析预测分级和IDH基因型。使用受试者工作特征（ROC）曲线和曲线下面积（AUC）分析评估诊断性能。
结果
II级和III级以及III级和IV级之间的DS、MT和pH加权指标存在显著差异。酰胺、NOE、pH加权和MTR在IDH基因型之间存在显著差异。回归模型在区分II级和III级（AUC = 0.80，95%置信区间：0.64 - 0.91）、III级和IV级（AUC = 0.83，95%置信区间：0.74 - 0.90）以及IDH突变型和野生型状态（AUC = 0.84，95%置信区间：0.77 - 0.90）方面达到了最高的AUC。MT和pH加权指标分别是识别II级和III级胶质瘤中1p/19q共缺失的唯一指标。MT第90百分位数（AUC = 0.87，95%置信区间：0.65 - 0.98）和pH加权第25百分位数（AUC = 0.83，95%置信区间：0.56 - 0.97）分别表现出最佳性能。MTR是唯一能够区分MGMT启动子甲基化和未甲基化胶质瘤的指标，其中MTR第90百分位数表现最佳（AUC = 0.79，95%置信区间：0.61 - 0.91）。
结论
基于CEST的肿瘤pH评估和代谢谱分析在预测胶质瘤分级、IDH突变状态、1p/19q共缺失和MGMT基因型方面显示出有前景的潜力。
Zotero 插件