Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas

ObjectivesTo 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.MethodsWe analyzed 128 patients with pathologi...

Full description

Saved in:
Bibliographic Details
Main Authors: Xinli Zhang, Jue Lu, Xiaoming Liu, Peng Sun, Qian Qin, Zhengdong Xiang, Lan Cheng, Xiaoxiao Zhang, Xiaotong Guo, Jing Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2024.1507335/full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850122992085893120
author Xinli Zhang
Jue Lu
Xiaoming Liu
Peng Sun
Qian Qin
Zhengdong Xiang
Lan Cheng
Xiaoxiao Zhang
Xiaotong Guo
Jing Wang
author_facet Xinli Zhang
Jue Lu
Xiaoming Liu
Peng Sun
Qian Qin
Zhengdong Xiang
Lan Cheng
Xiaoxiao Zhang
Xiaotong Guo
Jing Wang
author_sort Xinli Zhang
collection DOAJ
description ObjectivesTo 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.MethodsWe 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.ResultsThe 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 MTR3.5 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 MTR3.5 was the only indicator which can distinguish MGMT promoter methylation and unmethylation gliomas, within MTR3.5 90th percentile performed best (AUC = 0.79, 95% CI: 0.61- 0.91).ConclusionCEST-based tumor pH assessment and metabolic profiling demonstrated promising potential for predicting glioma grade, IDH mutation status, 1p/19q codeletion, and MGMT genotype.
format Article
id doaj-art-111b4ba28ae7499d8f4a3dab4b1f3d96
institution OA Journals
issn 2234-943X
language English
publishDate 2024-12-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Oncology
spelling doaj-art-111b4ba28ae7499d8f4a3dab4b1f3d962025-08-20T02:34:42ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2024-12-011410.3389/fonc.2024.15073351507335Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomasXinli Zhang0Jue Lu1Xiaoming Liu2Peng Sun3Qian Qin4Zhengdong Xiang5Lan Cheng6Xiaoxiao Zhang7Xiaotong Guo8Jing Wang9Department of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Clinical & Technical Solutions, Philips Healthcare, Beijing, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Clinical & Technical Solutions, Philips Healthcare, Beijing, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Radiology, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaObjectivesTo 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.MethodsWe 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.ResultsThe 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 MTR3.5 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 MTR3.5 was the only indicator which can distinguish MGMT promoter methylation and unmethylation gliomas, within MTR3.5 90th percentile performed best (AUC = 0.79, 95% CI: 0.61- 0.91).ConclusionCEST-based tumor pH assessment and metabolic profiling demonstrated promising potential for predicting glioma grade, IDH mutation status, 1p/19q codeletion, and MGMT genotype.https://www.frontiersin.org/articles/10.3389/fonc.2024.1507335/fullgliomaIDH1p/19q codeletionMGMTpH assessment
spellingShingle Xinli Zhang
Jue Lu
Xiaoming Liu
Peng Sun
Qian Qin
Zhengdong Xiang
Lan Cheng
Xiaoxiao Zhang
Xiaotong Guo
Jing Wang
Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas
Frontiers in Oncology
glioma
IDH
1p/19q codeletion
MGMT
pH assessment
title Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas
title_full Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas
title_fullStr Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas
title_full_unstemmed Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas
title_short Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas
title_sort multipool cest and cest based ph assessment as predictive tools for glioma grading idh mutation 1p 19q codeletion and mgmt promoter methylation in gliomas
topic glioma
IDH
1p/19q codeletion
MGMT
pH assessment
url https://www.frontiersin.org/articles/10.3389/fonc.2024.1507335/full
work_keys_str_mv AT xinlizhang multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT juelu multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT xiaomingliu multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT pengsun multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT qianqin multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT zhengdongxiang multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT lancheng multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT xiaoxiaozhang multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT xiaotongguo multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas
AT jingwang multipoolcestandcestbasedphassessmentaspredictivetoolsforgliomagradingidhmutation1p19qcodeletionandmgmtpromotermethylationingliomas