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

doi:10.1186/s40644-019-0246-0

	F-18-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma
	Kong, Ziren 1,2,3; Lin, Yusong 4,11; Jiang, Chendan 2,3; Li, Longfei 4; Liu, Zehua 4; Wang, Yuekun 2,3; Dai, Congxin 2,3; Liu, Delin 1,2,3; Qin, Xuying 3,6,10; Wang, Yu 2
刊名	CANCER IMAGING
	2019-08-19
卷号	19 期号:1 页码:10
关键词	Radiomics FDG PET MGMT promoter methylation Glioma Prognosis
ISSN号	1740-5025
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	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.
资助项目	Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences[2016-I2M-2-001] ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences[2018-I2M-3-001] ; Fundamental Research Funds for the Central Universities[3332018029] ; National Natural Science Foundation of China[81772009] ; National Natural Science Foundation of China[81772012] ; Scientific and Technological Research Project of Henan Province[182102310162] ; Beijing Natural Science Foundation[7182109] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2019136]
WOS关键词	GLIOBLASTOMA ; TEMOZOLOMIDE ; SURVIVAL ; DISEASE ; PET
WOS研究方向	Oncology ; Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	BMC
WOS记录号	WOS:000486718800001
资助机构	Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences ; Fundamental Research Funds for the Central Universities ; National Natural Science Foundation of China ; Scientific and Technological Research Project of Henan Province ; Beijing Natural Science Foundation ; Chinese Academy of Sciences ; Youth Innovation Promotion Association of Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/27026]
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.Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Nucl Med, 1 Shuaifuyuan Wangfujing, Beijing, Peoples R China 2.Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Neurosurg, 1 Shuaifuyuan Wangfujing, Beijing, Peoples R China 3.Peking Union Med Coll, 1 Shuaifuyuan Wangfujing, Beijing, Peoples R China 4.Zhengzhou Univ, Collaborat Innovat Ctr Internet Healthcare, 75 Daxue Rd, Zhengzhou, Henan, Peoples R China 5.Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, 80 East Zhongguancun Rd, Beijing, Peoples R China 6.Chinese Acad Med Sci, Peking Union Med Coll Hosp, Dept Pathol, 1 Shuaifuyuan, Beijing, Peoples R China 7.Beihang Univ, Sch Med, Beijing Adv Innovat Ctr Big Data Based Precis Med, 37 Xueyuan Rd, Beijing, Peoples R China 8.Xidian Univ, Sch Life Sci & Technol, Minist Educ, Engn Res Ctr Mol & Neuro Imaging, 266 Xinglong Sect,Xifeng Rd, Xian, Shaanxi, Peoples R China 9.Univ Chinese Acad Sci, 80 East Zhongguancun Rd, Beijing, Peoples R China 10.Tianjin Univ Sci & Technol, Key Lab Ind Microbiol, 1038 Dagu Nanlu, Tianjin, Peoples R China
推荐引用方式 GB/T 7714	Kong, Ziren,Lin, Yusong,Jiang, Chendan,et al. F-18-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma[J]. CANCER IMAGING,2019,19(1):10.
APA	Kong, Ziren.,Lin, Yusong.,Jiang, Chendan.,Li, Longfei.,Liu, Zehua.,...&Ma, Wenbin.(2019).F-18-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma.CANCER IMAGING,19(1),10.
MLA	Kong, Ziren,et al."F-18-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma".CANCER IMAGING 19.1(2019):10.