CASIA OpenIR
A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas
Liu, Xing1; Li, Yiming1; Qian, Zenghui1; Sun, Zhiyan1; Xu, Kaibin2; Wang, Kai3; Liu, Shuai1; Fan, Xing1; Li, Shaowu4; Zhang, Zhong5; Jiang, Tao1,5,6,7; Wang, Yinyan5
Source PublicationNEUROIMAGE-CLINICAL
ISSN2213-1582
2018
Volume20Pages:1070-1077
Corresponding AuthorJiang, Tao(taojiang1964@163.com) ; Wang, Yinyan(tiantanyinyan@126.com)
AbstractObjective: The aim of this study was to develop a radiomics signature for prediction of progression-free survival (PFS) in lower-grade gliomas and to investigate the genetic background behind the radiomics signature. Methods: In this retrospective study, training (n = 216) and validation (n = 84) cohorts were collected from the Chinese Glioma Genome Atlas and the Cancer Genome Atlas, respectively. For each patient, a total of 431 radiomics features were extracted from preoperative T2-weighted magnetic resonance images. A radiomics signature was generated in the training cohort, and its prognostic value was evaluated in both the training and validation cohorts. The genetic characteristics of the group with high-risk scores were identified by radio-genomic analysis, and a nomogram was established for prediction of PFS. Results: There was a significant association between the radiomics signature (including 9 screened radiomics features) and PFS, which was independent of other clinicopathologic factors in both the training (P < 0.001, multivariable Cox regression) and validation (P = 0.045, multivariable Cox regression) cohorts. Radiogenomic analysis revealed that the radiomics signature was associated with the immune response, programmed cell death, cell proliferation, and vasculature development. A nomogram established using the radiomics signature and clinicopathologic risk factors demonstrated high accuracy and good calibration for prediction of PFS in both the training (C-index, 0.684) and validation (C-index, 0.823) cohorts. Conclusions: PFS can be predicted non-invasively in patients with LGGs by a group of radiomics features that could reflect the biological processes of these tumors.
KeywordRadiomic analysis Lower-grade gliomas Progression-free survival Radiogenomics
DOI10.1016/j.nicl.2018.10.014
WOS KeywordPROGNOSTIC-FACTORS ; IMAGING PREDICTOR ; CT TEXTURE ; FEATURES ; EXPRESSION ; REPRODUCIBILITY ; CLASSIFICATION ; NOMOGRAMS ; BIOMARKER
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[81601452] ; Beijing Natural Science Foundation[7174295] ; National Key Research and Development Plan[2016YFC0902500] ; Capital Medical Development Research Fund[2016-1-1072] ; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support[ZYLX201708]
Funding OrganizationNational Natural Science Foundation of China ; Beijing Natural Science Foundation ; National Key Research and Development Plan ; Capital Medical Development Research Fund ; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support
WOS Research AreaNeurosciences & Neurology
WOS SubjectNeuroimaging
WOS IDWOS:000450799000115
PublisherELSEVIER SCI LTD
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25698
Collection中国科学院自动化研究所
Corresponding AuthorJiang, Tao; Wang, Yinyan
Affiliation1.Capital Med Univ, Beijing Neurosurg Inst, 6 Tiantanxili, Beijing 100050, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
3.Capital Med Univ, Beijing Tiantan Hosp, Dept Nucl Med, Beijing, Peoples R China
4.Capital Med Univ, Beijing Neurosurg Inst, Neurol Imaging Ctr, Beijing, Peoples R China
5.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, 6 Tiantanxili, Beijing 100050, Peoples R China
6.Beijing Inst Brain Disorders, Ctr Brain Tumor, Beijing, Peoples R China
7.China Natl Clin Res Ctr Neurol Dis, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Liu, Xing,Li, Yiming,Qian, Zenghui,et al. A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas[J]. NEUROIMAGE-CLINICAL,2018,20:1070-1077.
APA Liu, Xing.,Li, Yiming.,Qian, Zenghui.,Sun, Zhiyan.,Xu, Kaibin.,...&Wang, Yinyan.(2018).A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas.NEUROIMAGE-CLINICAL,20,1070-1077.
MLA Liu, Xing,et al."A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas".NEUROIMAGE-CLINICAL 20(2018):1070-1077.
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