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Prediction of microvascular invasion in hepatocellular carcinoma based on multi-phase dynamic enhanced CT radiomics feature and multi-classifier hierarchical fusion model

Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2024-02, Vol.44 (2), p.260-269

ISSN: 1673-4254 ;DOI: 10.12122/j.issn.1673-4254.2024.02.08 ;PMID: 38501411

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  • Title:
    Prediction of microvascular invasion in hepatocellular carcinoma based on multi-phase dynamic enhanced CT radiomics feature and multi-classifier hierarchical fusion model
  • Author: Zhong, W ; Liang, F ; Yang, R ; Zhen, X
  • Subjects: Carcinoma, Hepatocellular - pathology ; Humans ; Liver Neoplasms - pathology ; Radiomics ; Retrospective Studies ; Tomography, X-Ray Computed - methods
  • Is Part Of: Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2024-02, Vol.44 (2), p.260-269
  • Description: To predict microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using a model based on multiphase dynamic-enhanced CT (DCE-CT) radiomics feature and hierarchical fusion of multiple classifiers. We retrospectively collected preoperative DCE-CT images from 111 patients with pathologically confirmed HCC in Guangzhou First People's Hospital between January, 2016 and April, 2020. The volume of interest was outlined in the early arterial phase, late arterial phase, portal venous phase and equilibrium phase, and radiomics features of these 4 phases were extracted. Seven classifiers based on different algorithms were trained using the filtered feature subsets to obtain multiple base classifiers under each phase. According to the hierarchical fusion strategy, a multi-criteria decision-making-based weight assignment algorithm was used for fusing each base classifier under the same phase with the model after extracting the phase information to obtain the prediction model. The proposed model was evaluated using
  • Publisher: China
  • Language: Chinese
  • Identifier: ISSN: 1673-4254
    DOI: 10.12122/j.issn.1673-4254.2024.02.08
    PMID: 38501411
  • Source: MEDLINE
    PubMed Central
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