Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Noninvasive model for predicting future ischemic strokes in patients with silent lacunar infarction using radiomics | |
Su,Jie-hua1; Meng,Ling-wei2,3; Dong,Di2,3; Zhuo,Wen-yan1; Wang,Jian-ming4; Liu,Li-bin1; Qin,Yi5; Tian,Ye4; Tian,Jie3,6,7,8; Li,Zhao-hui1 | |
发表期刊 | BMC Medical Imaging |
ISSN | 1471-2342 |
2020-07-08 | |
卷号 | 20期号:1页码:11 |
通讯作者 | Tian,Jie(jie.tian@ia.ac.cn) ; Li,Zhao-hui(lzh_edu@126.com) |
摘要 | AbstractBackgroundThis study aimed to investigate integrating radiomics with clinical factors in cranial computed tomography (CT) to predict ischemic strokes in patients with silent lacunar infarction (SLI).MethodsRadiomic features were extracted from baseline cranial CT images of patients with SLI. A least absolute shrinkage and selection operator (LASSO)–Cox regression analysis was used to select significant prognostic factors based on ModelC with clinical factors, ModelR with radiomic features, and ModelCR with both factors. The Kaplan–Meier method was used to compare stroke-free survival probabilities. A nomogram and a calibration curve were used for further evaluation.ResultsRadiomic signature (p?0.01), age (p?=?0.09), dyslipidemia (p?=?0.03), and multiple infarctions (p?=?0.02) were independently associated with future ischemic strokes. ModelCR had the best accuracy with 6-, 12-, and 18-month areas under the curve of 0.84, 0.81, and 0.79 for the training cohort and 0.79, 0.88, and 0.75 for the validation cohort, respectively. Patients with a ModelCR score?0.17 had higher probabilities of stroke-free survival. The prognostic nomogram and calibration curves of the training and validation cohorts showed acceptable discrimination and calibration capabilities (concordance index [95% confidence interval]: 0.7864 [0.70–0.86]; 0.7140 [0.59–0.83], respectively).ConclusionsRadiomic analysis based on baseline CT images may provide a novel approach for predicting future ischemic strokes in patients with SLI. Older patients and those with dyslipidemia or multiple infarctions are at higher risk for ischemic stroke and require close monitoring and intensive intervention. |
关键词 | Stroke Infarction Radiomics Tomography X-ray computed |
DOI | 10.1186/s12880-020-00470-7 |
关键词[WOS] | HEALTH-CARE PROFESSIONALS ; BRAIN INFARCTION ; RECURRENT STROKE ; BLOOD-PRESSURE ; RISK-FACTORS ; PREVENTION ; GUIDELINES ; MANAGEMENT ; STATEMENT ; ASSOCIATION |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2017YFA0700401] ; National Natural Science Foundation of China[91959130] ; National Natural Science Foundation of China[81971776] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81527805] ; Beijing Natural Science Foundation[L182061] ; Strategic Priority CAS Project[XDB38040200] ; Youth Innovation Promotion Association CAS[2017175] ; Scientific Project of Administration of Traditional Chinese Medicine of Guangdong Province of China[20171253] ; Major Project of Medical Health Science and Technology of Zhuhai Municipal[20171009F060001] |
项目资助者 | National Key R&D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority CAS Project ; Youth Innovation Promotion Association CAS ; Scientific Project of Administration of Traditional Chinese Medicine of Guangdong Province of China ; Major Project of Medical Health Science and Technology of Zhuhai Municipal |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | BMC:10.1186/s12880-020-00470-7 |
出版者 | BioMed Central |
七大方向——子方向分类 | 医学影像处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39845 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Tian,Jie; Li,Zhao-hui |
作者单位 | 1.Zhuhai Hospital Affiliated with Jinan University; Department of Neurology 2.University of Chinese Academy of Sciences; School of Artificial Intelligence 3.Institute of Automation, Chinese Academy of Sciences; CAS Key Laboratory of Molecular Imaging 4.Zhuhai People’s Hospital; Department of Radiology 5.Zhuhai Hospital Affiliated with Jinan University; Department of Orthopedics 6.Beihang University; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering 7.Xidian University; Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology 8.Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Su,Jie-hua,Meng,Ling-wei,Dong,Di,et al. Noninvasive model for predicting future ischemic strokes in patients with silent lacunar infarction using radiomics[J]. BMC Medical Imaging,2020,20(1):11. |
APA | Su,Jie-hua.,Meng,Ling-wei.,Dong,Di.,Zhuo,Wen-yan.,Wang,Jian-ming.,...&Li,Zhao-hui.(2020).Noninvasive model for predicting future ischemic strokes in patients with silent lacunar infarction using radiomics.BMC Medical Imaging,20(1),11. |
MLA | Su,Jie-hua,et al."Noninvasive model for predicting future ischemic strokes in patients with silent lacunar infarction using radiomics".BMC Medical Imaging 20.1(2020):11. |
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