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Radiomic features predict Ki-67 expression level and survival in lower grade gliomas
Li, Yiming1; Qian, Zenghui1; Xu, Kaibin2; Wang, Kai3; Fan, Xing1; Li, Shaowu1; Liu, Xing1; Wang, Yinyan4; Jiang, Tao1,5,6
Source PublicationJOURNAL OF NEURO-ONCOLOGY
2017-11-01
Volume135Issue:2Pages:317-324
SubtypeArticle
AbstractTo investigate the radiomic features associated with Ki-67 expression in lower grade gliomas and assess the prognostic values of these features. Patients with lower grade gliomas (n = 117) were randomly assigned into the training (n = 78) and validation (n = 39) sets. A total of 431 radiological features were extracted from each patient. Differential radiological features between the low and high Ki-67 expression groups were screened by significance analysis of microarrays. Then, generalized linear analysis was performed to select features that could predict the Ki-67 expression level. Predictive efficiencies were further evaluated in the validation set. Cox regression analysis was performed to investigate the prognostic values of Ki-67 expression level and Ki-67-related radiological features. A group of nine radiological features were screened for prediction of Ki-67 expression status; these achieved accuracies of 83.3% and 88.6% (areas under the curves, 0.91 and 0.93) in the training and validation sets, respectively. Of these features, only spherical disproportion (SD) was found to be a prognostic factor. Patients in the high SD group exhibited worse outcomes in the whole cohort (overall survival, p < 0.0001; progression-free survival, p < 0.0001). Ki-67 expression level and SD were independent prognostic factors in the multivariate Cox regression analysis. This study identified a radiomic signature for prediction of Ki-67 expression level as well as a prognostic radiological feature in patients with lower grade gliomas.
KeywordKi-67 Lower Grade Gliomas Radiogenomics Prediction Survival
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1007/s11060-017-2576-8
WOS KeywordLABELING INDEX ; DIFFUSION TENSOR ; ASTROCYTOMAS ; RADIOGENOMICS ; MRI
Indexed BySCI
Language英语
Funding OrganizationBeijing Natural Science Foundation(7174295) ; National Natural Science Foundation of China(81601452)
WOS Research AreaOncology ; Neurosciences & Neurology
WOS SubjectOncology ; Clinical Neurology
WOS IDWOS:000414212300011
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20748
Collection脑网络组研究中心
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 Neuroradiol, Beijing, Peoples R China
4.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, 6 Tiantanxili, Beijing 100050, Peoples R China
5.Beijing Inst Brain Disorders, Ctr Brain Tumor, Beijing, Peoples R China
6.China Natl Clin Res Ctr Neurol Dis, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Li, Yiming,Qian, Zenghui,Xu, Kaibin,et al. Radiomic features predict Ki-67 expression level and survival in lower grade gliomas[J]. JOURNAL OF NEURO-ONCOLOGY,2017,135(2):317-324.
APA Li, Yiming.,Qian, Zenghui.,Xu, Kaibin.,Wang, Kai.,Fan, Xing.,...&Jiang, Tao.(2017).Radiomic features predict Ki-67 expression level and survival in lower grade gliomas.JOURNAL OF NEURO-ONCOLOGY,135(2),317-324.
MLA Li, Yiming,et al."Radiomic features predict Ki-67 expression level and survival in lower grade gliomas".JOURNAL OF NEURO-ONCOLOGY 135.2(2017):317-324.
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