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基于普美显增强磁共振的影像组学鉴别肝细胞癌与肝血管瘤

陈茂东 张静 杨桂香 林杰民 冯衍秋

南方医科大学学报2018,Vol.38Issue(4):428-433,6.
南方医科大学学报2018,Vol.38Issue(4):428-433,6.DOI:10.3969/j.issn.1673-4254.2018.04.10

基于普美显增强磁共振的影像组学鉴别肝细胞癌与肝血管瘤

Differential diagnosis of hepatocellular carcinoma and hepatic hemangiomas based on radiomic features of gadoxetate disodium-enhanced magnetic resonance imaging

陈茂东 1张静 2杨桂香 2林杰民 3冯衍秋1

作者信息

  • 1. 南方医科大学生物医学工程学院,广东 广州510515
  • 2. 南方医科大学南方医院影像中心,广东 广州510515
  • 3. 汕头市中心医院肿瘤放疗科,广东 汕头515000
  • 折叠

摘要

Abstract

Objective To evaluate the feasibility of using radiomic features for differential diagnosis of hepatocellular carcinoma (HCC) and hepatic cavernous hemangioma (HHE). Methods Gadoxetate disodium-enhanced magnetic resonance imaging data were collected from a total of 135 HCC and HHE lesions.The radiomic texture features of each lesion were extracted on the hepatobiliary phase images,and the performance of each feature was assessed in differentiation and classification of HCC and HHE. In multivariate analysis, the performance of 3 feature selection algorithms (namely minimum redundancy-maximum relevance, mRmR; neighborhood component analysis, NCA; and sequence forward selection, SFS) was compared. The optimal feature subset was determined according to the optimal feature selection algorithm and used for testing the 3 classifier algorithms (namely the support vector machine, RBF-SVM; linear discriminant analysis, LDA; and logistic regression). All the tests were repeated 5 times with 10-fold cross validation experiments. Results More than 50% of the radiomic features exhibited strong distinguishing ability, among which gray level co-occurrence matrix feature S (3,-3) SumEntrp showed a good classification performance with an AUC of 0.72(P<0.01),a sensitivity of 0.83 and a specificity of 0.57. For the multivariate analysis, 15 features were selected based on the SFS algorithm, which produced better results than the other two algorithms. Testing of these 15 selected features for their average cross-validation performance with RBF-SVM classifier yielded a test accuracy of 0.82±0.09, an AUC of 0.86±0.12, a sensitivity of 0.88±0.11, and a specificity of 0.76±0.18. Conclusion The radiomic features based on gadoxetate disodium-enhanced magnetic resonance images allow efficient differential diagnosis of HCC and HHE, and can potentially provide important assistance in clinical diagnosis of the two diseases.

关键词

肝细胞癌/肝血管瘤/普美显增强磁共振/影像组学/鉴别诊断

Key words

hepatocellular carcinoma/hepatic hemangiomas/gadoxetate disodium-enhanced magnetic resonance imaging/radiomic features/differential diagnosis

引用本文复制引用

陈茂东,张静,杨桂香,林杰民,冯衍秋..基于普美显增强磁共振的影像组学鉴别肝细胞癌与肝血管瘤[J].南方医科大学学报,2018,38(4):428-433,6.

基金项目

国家重点研发计划(2016YFC0107104) (2016YFC0107104)

广东省科技计划项目(2015B010131011)Supported by National Key Research and Development Program of China(2016YFC0107104). (2015B010131011)

南方医科大学学报

OA北大核心CSCDCSTPCDMEDLINE

1673-4254

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