Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma

doi:10.1016/j.radonc.2019.10.002

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma
	Wei, Wei 2,6,7,8; Wang, Ke 4,5; Liu, Zhenyu 1,6; Tian, Kaibing 4,5; Wang, Liang 4,5; Du, Jiang 3; Ma, Junpeng 4,5; Wang, Shuo 6,8; Li, Longfei 6; Zhao, Rui 2,7
刊名	RADIOTHERAPY AND ONCOLOGY
	2019-12-01
卷号	141 页码:239-246
关键词	Biomarkers Magnetic resonance imaging Prognosis Progression-free survival Radiomics Skull base chordoma
ISSN号	0167-8140
DOI	10.1016/j.radonc.2019.10.002
通讯作者	Wu, Zhen(wuzhen1966@aliyun.com) ; Tian, Jie(jie.tian@ia.ac.cn)
英文摘要	Background and purpose: We used radiomic analysis to establish a radiomic signature based on anatomical magnetic resonance imaging (MRI) sequences and explore its effectiveness as a novel prognostic biomarker for skull base chordoma (SBC). Materials and methods: In this retrospective study, radiomic analysis was performed using preoperative axial T-1 FLAIR, T-2-weighted, and enhanced T-1 FLAIR from a single hospital. The primary clinical endpoint was progression-free survival. A total of 1860 3-D radiomic features were extracted from manually segmented region of interest. Pearson correlation coefficient was used for feature dimensional reduction and a ridge regression-based Cox proportional hazards model was used to determine a radiomic signature. Afterwards, radiomic signature and nine other potential prognostic factors, including age, gender, histological subtype, dural invasion, blood supply, adjuvant radiotherapy, extent of resection, preoperative KPS, and postoperative KPS were analyzed to build a radiomic nomogram and a clinical model. Finally, we compared the nomogram with each prognostic factor/model by DeLong's test. Results: A total of 148 SBC patients were enrolled, including 64 with disease progression. The median follow-up time was 52 months (range 4-122 months). The Harrell's concordance index of the radiomic signature was 0.745 (95% CI, 0.709-0.781) for the validation cohort, and its discrimination accuracy in predicting progression risk at 5 years in the same cohort was 82.4% (95% CI, 72.6-89.7%). Conclusions: The radiomics is a low-cost, non-invasive method to predict SBC prognosis preoperatively. Radiomic signature is a potential prognostic biomarker that may allow the individualized evaluation of patients with SBC. (C) 2019 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[81922040] ; National Natural Science Foundation of China[81772012] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81672506] ; National Natural Science Foundation of China[81802683] ; National Key Research and Development Plan of China[2017YFA0205200] ; National Key Research and Development Plan of China[2016YFA0100900] ; National Key Research and Development Plan of China[2016YFA0100902] ; Beijing Natural Science Foundation[7182109] ; Youth Innovation Promotion Association CAS[2019136] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Special Found for The Talents of Beijing[2016000021469G212]
WOS关键词	RETROSPECTIVE ANALYSIS ; SURVIVAL PATTERNS ; PREDICTION ; MODEL ; CLASSIFICATION ; VALIDATION ; MANAGEMENT ; DIAGNOSIS ; NETWORKS ; ONCOLOGY
WOS研究方向	Oncology ; Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	ELSEVIER IRELAND LTD
WOS记录号	WOS:000500572800035
资助机构	National Natural Science Foundation of China ; National Key Research and Development Plan of China ; Beijing Natural Science Foundation ; Youth Innovation Promotion Association CAS ; Chinese Academy of Sciences ; Special Found for The Talents of Beijing
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/29369]
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	Wu, Zhen; Tian, Jie
作者单位	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 2.Xian Polytech Univ, Sch Elect & Informat, Xian, Shaanxi, Peoples R China 3.Beijing Neurosurg Inst, Dept Neuropathol, Beijing, Peoples R China 4.China Natl Clin Res Ctr Neurol Dis, Beijing, Peoples R China 5.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, 119 West Rd South Fourth Ring, Beijing 100050, Peoples R China 6.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 7.Xidian Univ, Sch Life Sci & Technol, Minist Educ, Engn Res Ctr Mol & Neuro Imaging, Xian, Shaanxi, Peoples R China 8.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wei, Wei,Wang, Ke,Liu, Zhenyu,et al. Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma[J]. RADIOTHERAPY AND ONCOLOGY,2019,141:239-246.
APA	Wei, Wei.,Wang, Ke.,Liu, Zhenyu.,Tian, Kaibing.,Wang, Liang.,...&Tian, Jie.(2019).Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma.RADIOTHERAPY AND ONCOLOGY,141,239-246.
MLA	Wei, Wei,et al."Radiomic signature: A novel magnetic resonance imaging-based prognostic biomarker in patients with skull base chordoma".RADIOTHERAPY AND ONCOLOGY 141(2019):239-246.