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Delta-radiomics models based on multi-phase contrast-enhanced magnetic resonance imaging can preoperatively predict glypican-3-positive hepatocellular carcinoma.
Han, Zewen; Dai, Hanting; Chen, Xiaolin; Gao, Lanmei; Chen, Xiaojie; Yan, Chuan; Ye, Rongping; Li, Yueming.
Afiliação
  • Han Z; Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Dai H; School of Medical Imaging, Fujian Medical University, Fuzhou, China.
  • Chen X; Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Gao L; School of Medical Imaging, Fujian Medical University, Fuzhou, China.
  • Chen X; Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Yan C; Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Ye R; Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Li Y; Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Front Physiol ; 14: 1138239, 2023.
Article em En | MEDLINE | ID: mdl-37601639
Objectives: The aim of this study is to investigate the value of multi-phase contrast-enhanced magnetic resonance imaging (CE-MRI) based on the delta radiomics model for identifying glypican-3 (GPC3)-positive hepatocellular carcinoma (HCC). Methods: One hundred and twenty-six patients with pathologically confirmed HCC (training cohort: n = 88 and validation cohort: n = 38) were retrospectively recruited. Basic information was obtained from medical records. Preoperative multi-phase CE-MRI images were reviewed, and the 3D volumes of interest (VOIs) of the whole tumor were delineated on non-contrast T1-weighted imaging (T1), arterial phase (AP), portal venous phase (PVP), delayed phase (DP), and hepatobiliary phase (HBP). One hundred and seven original radiomics features were extracted from each phase, and delta-radiomics features were calculated. After a two-step feature selection strategy, radiomics models were built using two classification algorithms. A nomogram was constructed by combining the best radiomics model and clinical risk factors. Results: Serum alpha-fetoprotein (AFP) (p = 0.013) was significantly related to GPC3-positive HCC. The optimal radiomics model is composed of eight delta-radiomics features with the AUC of 0.805 and 0.857 in the training and validation cohorts, respectively. The nomogram integrated the radiomics score, and AFP performed excellently (training cohort: AUC = 0.844 and validation cohort: AUC = 0.862). The calibration curve showed good agreement between the nomogram-predicted probabilities and GPC3 actual expression in both training and validation cohorts. Decision curve analysis further demonstrates the clinical practicality of the nomogram. Conclusion: Multi-phase CE-MRI based on the delta-radiomics model can non-invasively predict GPC3-positive HCC and can be a useful method for individualized diagnosis and treatment.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article