Radiomics signature based on FDG-PET predicts proliferative activity in primary glioma
文献类型:期刊论文
作者 | Kong, Z.2,3,4; Li, J.2,3,5; Liu, Zehua6; Liu, Zhenyu7,8; Zhao, D.1,3; Cheng, X.3,4; Li, L.6; Lin, Y.6,11; Wang, Y.2,3; Tian, J.7,8,9,10 |
刊名 | CLINICAL RADIOLOGY |
出版日期 | 2019-10-01 |
卷号 | 74期号:10页码:9 |
ISSN号 | 0009-9260 |
DOI | 10.1016/j.crad.2019.06.019 |
通讯作者 | Wang, Y.(ywang@pumch.cn) ; Tian, J.(jie.tian@ia.ac.cn) ; Ma, W.(mawb2001@hotmail.com) |
英文摘要 | AIM: To investigate a radiomics method based on 2[F-18]-fluoro-2-deoxy-D-glucose (FDG) positron-emission tomography (PET) to non-invasively evaluate proliferative activity in gliomas. MATERIALS AND METHODS: A total of 123 patients with histopathologically confirmed primary glioma were reviewed retrospectively and assigned randomly into the primary cohort (n=82) and validation cohort (n=41). Tumour proliferative activity was defined by the Ki-67 index based on immunohistochemistry. Standard uptake value (SUV) maps were generated, and 1,561 radiomics features were extracted. Radiomics features were selected through the sequential application of three algorithms. Three predictive signatures were generated: a radiomics signature, a clinical signature, and a fusion signature. The predictive performances were evaluated by receiver operating characteristic (ROC) curve analysis, and patient prognoses were stratified based on the Ki-67 index and the signature with the most reliable performance. RESULTS: Nine radiomics features were selected to construct the radiomics signature that achieved an accuracy of 81.7% and 73.2% and an area under the curve (AUC) of 0.88 and 0.76 in the primary cohort and the validation cohort, respectively. The clinical signature and fusion signature demonstrated comparable performance in the primary cohort but were over-fitted judging from the result in the validation cohort. Both the Ki-67 index and the radiomics signature could stratify patients into two distinctive prognostic groups, and the difference within each prognostic group was not statistically significant. CONCLUSION: Radiomics signature based on F-18-FDG-PET is a promising method for the non-invasive measurement of glioma proliferative activity and facilitates the prediction of patient prognoses. (C) 2019 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved. |
WOS关键词 | KI-67 LABELING INDEX ; TUMOR HETEROGENEITY ; MONOCLONAL-ANTIBODY ; DIFFUSION TENSOR ; BRAIN-TUMORS ; GRADE ; IMMUNOHISTOCHEMISTRY ; TOMOGRAPHY ; DIAGNOSIS ; SELECTION |
资助项目 | Chinese Academy of Medical Sciences ; 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] |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
语种 | 英语 |
出版者 | W B SAUNDERS CO LTD |
WOS记录号 | WOS:000484770700018 |
资助机构 | Chinese Academy of Medical Sciences ; 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 |
源URL | [http://ir.ia.ac.cn/handle/173211/27262] |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
通讯作者 | Wang, Y.; Tian, J.; Ma, W. |
作者单位 | 1.Chinese Acad Med Sci, Dept Pathol, Peking Union Med Coll Hosp, Beijing, Peoples R China 2.Chinese Acad Med Sci, Dept Neurosurg, Peking Union Med Coll Hosp, Beijing, Peoples R China 3.Peking Union Med Coll, Beijing, Peoples R China 4.Chinese Acad Med Sci, Dept Nucl Med, Peking Union Med Coll Hosp, Beijing, Peoples R China 5.Tsinghua Univ, Sch Med, Beijing, Peoples R China 6.Zhengzhou Univ, Collaborat Innovat Ctr Internet Healthcare, Zhengzhou, Henan, Peoples R China 7.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 8.Univ Chinese Acad Sci, Beijing, Peoples R China 9.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China 10.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Minist Educ, Sch Life Sci & Technol, Xian, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Kong, Z.,Li, J.,Liu, Zehua,et al. Radiomics signature based on FDG-PET predicts proliferative activity in primary glioma[J]. CLINICAL RADIOLOGY,2019,74(10):9. |
APA | Kong, Z..,Li, J..,Liu, Zehua.,Liu, Zhenyu.,Zhao, D..,...&Ma, W..(2019).Radiomics signature based on FDG-PET predicts proliferative activity in primary glioma.CLINICAL RADIOLOGY,74(10),9. |
MLA | Kong, Z.,et al."Radiomics signature based on FDG-PET predicts proliferative activity in primary glioma".CLINICAL RADIOLOGY 74.10(2019):9. |
入库方式: OAI收割
来源:自动化研究所
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