18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma

doi:10.1186/s40644-019-0246-0

	18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma
	Kong,Ziren 1,2; Lin,Yusong 3,10; Jiang,Chendan 1; Li,Longfei 3; Liu,Zehua 3; Wang,Yuekun 1; Dai,Congxin 1; Liu,Delin 1,2; Qin,Xuying 5,9; Wang,Yu 1
刊名	Cancer Imaging
	2019-08-19
卷号	19 期号:1
关键词	Radiomics FDG PET MGMT promoter methylation Glioma Prognosis
ISSN号	1470-7330
DOI	10.1186/s40644-019-0246-0
通讯作者	Cheng,Xin(pumch_chengxin@126.com) ; Tian,Jie(jie.tian@ia.ac.cn) ; Ma,Wenbin(mawb2001@hotmail.com)
英文摘要	AbstractBackgroundThe methylation status of the O6-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 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for noninvasive measurement of the MGMT promoter methylation status in glioma.MethodsOne 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 18F-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.ResultsFive 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).Conclusions18F-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.
语种	英语
出版者	BioMed Central
WOS记录号	BMC:10.1186/S40644-019-0246-0
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/26350]
专题	中国科学院自动化研究所
通讯作者	Cheng,Xin; Tian,Jie; Ma,Wenbin
作者单位	1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
推荐引用方式 GB/T 7714	Kong,Ziren,Lin,Yusong,Jiang,Chendan,et al. 18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma[J]. Cancer Imaging,2019,19(1).
APA	Kong,Ziren.,Lin,Yusong.,Jiang,Chendan.,Li,Longfei.,Liu,Zehua.,...&Ma,Wenbin.(2019).18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma.Cancer Imaging,19(1).
MLA	Kong,Ziren,et al."18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma".Cancer Imaging 19.1(2019).