Predicting the prognosis of hepatocellular carcinoma with the treatment of transcatheter arterial chemoembolization combined with microwave ablation using pretreatment MR imaging texture features.

Objective: To investigate the prognostic value of baseline magnetic resonance imaging (MRI) texture analysis of hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolization (TACE) and microwave ablation (MWA). Methods: MRI was performed on 102 patients with HCC before receivi...

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Publicado en:Abdominal Radiology Vol. 46; no. 8; pp. 3748 - 3758
Autores principales: Liu, Jun, Pei, Yigang, Zhang, Yu, Wu, Yifan, Liu, Fuquan, Gu, Shanzhi
Formato: Journal Article
Publicado: Springer Nature Aug2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2021
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      pub: Springer Nature
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        atl: Predicting the prognosis of hepatocellular carcinoma with the treatment of transcatheter arterial chemoembolization combined with microwave ablation using pretreatment MR imaging texture features.
      aug:
        au:
          Liu, Jun
          Pei, Yigang
          Zhang, Yu
          Wu, Yifan
          Liu, Fuquan
          Gu, Shanzhi
        affil: Department of Interventional Therapy, Beijing Shijitan Hospital, Affiliated Hospital of Capital Medical University, 100038, Beijing, People's Republic of China
      sug:
      ab: Objective: To investigate the prognostic value of baseline magnetic resonance imaging (MRI) texture analysis of hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolization (TACE) and microwave ablation (MWA). Methods: MRI was performed on 102 patients with HCC before receiving TACE combined with MWA in this retrospective study. The best 10 texture features were screened as a feature group for each MRI sequence by MaZda software using mutual information coefficient (MI), nonlinear discriminant analysis (NDA) and other methods. The optimal feature group with the lowest misdiagnosis rate was achieved on one MRI sequence between two groups dichotomized by 3-year survival, which was used to optimize the significant texture features with the optimal cutoff values. The Cox proportional hazards model was generated for the significant texture features and clinical variables to determine the independent predictors of overall survival (OS). The predictive performance of the model was further evaluated by the area under the ROC curve (AUC). Kaplan–Meier and log-rank tests were performed for disease-free survival (DFS) and Local recurrence-free survival (LRFS). Results: The optimal feature group with the lowest misdiagnosis rate of 8.82% was obtained on T2WI using MI combined with NDA feature analysis. For Cox proportional hazards regression models, the independent prognostic factors associated with OS were albumin (P = 0.047), BCLC stage (P = 0.001), Correlat(1,− 1)T2 (P = 0.01) and SumEntrp(3,0)T2 (P = 0.015), and the prediction efficiency of multivariate model is AUC = 0.876, 95%CI = 0.803–0.949. Kaplan–Meier analyses further demonstrated that BCLC (P < 0.001), Correlat(1,− 1)T2 (P = 0.023) and SumEntrp(3,0)T2 (P < 0.001) were associated with DFS, and BCLC (P = 0.007) related to LRFS. Conclusions: MR imaging texture features may be used to predict the prognosis of HCC treated with TACE combined with MWA.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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