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Novel radiomics features from CCTA images for the functional evaluation of significant ischaemic lesions based on the coronary fractional flow reserve score

文献类型：期刊论文

作者Hu, Wenchao1,8,9,10; Wu, Xiangjun6,7; Dong, Di6,7; Cui, Long-Biao3,9,10; Jiang, Min1,8,9,10; Zhang, Jibin1,8,9,10; Wang, Yabin2,9,10; Wang, Xinjiang9,10; Gao, Lei9,10; Tian, Jie4,5,6
刊名INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING
出版日期2020-06-03
页码12
ISSN号1569-5794
关键词Coronary artery disease CT angiography Radiomics Myocardial ischaemia
DOI10.1007/s10554-020-01896-4
通讯作者Tian, Jie(jie.tian@ia.ac.cn) ; Cao, Feng(fengcao8828@163.com)
英文摘要To explore the superiority of radiomics analysis in the diagnostic performance of coronary computed tomography angiography (CCTA) for identifying myocardial ischaemia and predicting major adverse cardiovascular events (MACE). A total of 105 lesions from 88 patients who underwent CCTA and invasive fractional flow reserve measurement were collected as the training set, and another 31 patients with CCTA and clinical outcome information were used as the validation set. Conventional CCTA features included the stenosis diameter, length, Agatston score and high-risk plaque characteristics. After extracting and selecting radiomics features, the robustness of the radiomics features was examined, and then conventional and radiomics models were established using logistic regressions. The area under the receiver operating characteristic (ROC) curve (AUC) and Net Reclassification Index (NRI) were analysed to compare the discrimination and classification abilities between the two models in both the training and validation sets. A total of 1409 radiomics features were extracted, and three wavelet features were finally screened out. The robustness test showed good stability for the refined radiomics features. Compared with the conventional model, the radiomics model displayed a significantly improved diagnostic performance in the training set (AUC 0.762 vs. 0.631, 95% confidence interval [CI] 0.671-0.853 vs. 0.519-0.742, P = 0.058) but a slightly improved diagnostic performance in the validation set (AUC 0.671 vs. 0.592, 95% CI 0.466-0.875 vs. 0.519-0.742, P = 0.448). The NRI of the radiomics model was increased in both the training and validation sets (NRI 0.198 and 0.238, respectively). Quantitative radiomics analysis was feasible and might help to improve the diagnostic performance of CCTA but is still controversial for predicting MACE.
WOS关键词CARDIOVASCULAR COMPUTED-TOMOGRAPHY ; CT ANGIOGRAPHY ; HEART-ASSOCIATION ; AMERICAN SOCIETY ; SCCT GUIDELINES ; TASK-FORCE ; DISEASE ; PREDICTION ; CARDIOLOGY ; STENOSES
资助项目National Natural Science Foundation of China[91939303] ; National Natural Science Foundation of China[81820108019] ; National Natural Science Foundation of China[81971776] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[91959130] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81227901] ; 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] ; Beijing Natural Science Foundation[L182061] ; Translational Medicine Project of Chinese PLA General Hospital[2017TM-003] ; Youth Innovation Promotion Association CAS[2017175]
WOS研究方向Cardiovascular System & Cardiology ; Radiology, Nuclear Medicine & Medical Imaging
语种英语
出版者SPRINGER
WOS记录号WOS:000537356200001
资助机构National Natural Science Foundation of China ; National Key R&D Program of China ; Beijing Natural Science Foundation ; Translational Medicine Project of Chinese PLA General Hospital ; Youth Innovation Promotion Association CAS
源URL[http://ir.ia.ac.cn/handle/173211/39626]  
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; Cao, Feng
作者单位1.Chinese Peoples Liberat Army Gen Hosp, Dept Cardiol, Beijing, Peoples R China
2.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Dept Cardiol, Beijing, Peoples R China
3.PLA Air Force Med Univ, Sch Med Psychol, Dept Clin Psychol, Xian, Peoples R China
4.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Peoples R China
5.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China
6.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China
7.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
8.Chinese PLA, Med Sch, Beijing, Peoples R China
9.Chinese Peoples Liberat Army Gen Hosp, Natl Res Ctr Geriatr Dis, Beijing, Peoples R China
10.Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Hu, Wenchao,Wu, Xiangjun,Dong, Di,et al. Novel radiomics features from CCTA images for the functional evaluation of significant ischaemic lesions based on the coronary fractional flow reserve score[J]. INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING,2020:12.
APA Hu, Wenchao.,Wu, Xiangjun.,Dong, Di.,Cui, Long-Biao.,Jiang, Min.,...&Cao, Feng.(2020).Novel radiomics features from CCTA images for the functional evaluation of significant ischaemic lesions based on the coronary fractional flow reserve score.INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING,12.
MLA Hu, Wenchao,et al."Novel radiomics features from CCTA images for the functional evaluation of significant ischaemic lesions based on the coronary fractional flow reserve score".INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING (2020):12.

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来源：自动化研究所

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