Noninvasive model for predicting future ischemic strokes in patients with silent lacunar infarction using radiomics
文献类型:期刊论文
作者 | Su,Jie-hua4; Meng,Ling-wei2,3; Dong,Di2,3; Zhuo,Wen-yan4; Wang,Jian-ming1; Liu,Li-bin4; Qin,Yi8; Tian,Ye1; Tian,Jie2,5,6,7; Li,Zhao-hui4 |
刊名 | BMC Medical Imaging |
出版日期 | 2020-07-08 |
卷号 | 20期号:1 |
关键词 | Stroke Infarction Radiomics Tomography X-ray computed |
DOI | 10.1186/s12880-020-00470-7 |
通讯作者 | Tian,Jie(jie.tian@ia.ac.cn) ; Li,Zhao-hui(lzh_edu@126.com) |
英文摘要 | 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. |
语种 | 英语 |
出版者 | BioMed Central |
WOS记录号 | BMC:10.1186/S12880-020-00470-7 |
源URL | [http://ir.ia.ac.cn/handle/173211/39844] |
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 | Tian,Jie; Li,Zhao-hui |
作者单位 | 1.Zhuhai People’s Hospital; Department of Radiology 2.Institute of Automation, Chinese Academy of Sciences; CAS Key Laboratory of Molecular Imaging 3.University of Chinese Academy of Sciences; School of Artificial Intelligence 4.Zhuhai Hospital Affiliated with Jinan University; Department of Neurology 5.Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology 6.Xidian University; Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology 7.Beihang University; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering 8.Zhuhai Hospital Affiliated with Jinan University; Department of Orthopedics |
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). |
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). |
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). |
入库方式: OAI收割
来源:自动化研究所
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