A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma.

Purpose: We aimed to develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).Methods: A total of 304 eligible patients with HCC were randomly divided into training (n=184) and independent...

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Publicado en:Diagnostic & Interventional Radiology Vol. 24; no. 3; pp. 121 - 131
Autores principales: Jie Peng, Jing Zhang, Qifan Zhang, Yikai Xu, Jie Zhou, Li Liu, Peng, Jie, Zhang, Jing, Zhang, Qifan, Xu, Yikai, Zhou, Jie, Liu, Li
Formato: Journal Article
Publicado: Galenos Yayinevi Tic. LTD. STI May/Jun2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May/Jun2018
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      pub: Galenos Yayinevi Tic. LTD. STI
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        atl: A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma.
      aug:
        au:
          Jie Peng
          Jing Zhang
          Qifan Zhang
          Yikai Xu
          Jie Zhou
          Li Liu
          Peng, Jie
          Zhang, Jing
          Zhang, Qifan
          Xu, Yikai
          Zhou, Jie
          Liu, Li
        affil: Hepatology Unit and Department of Infectious Diseases Nanfang Hospital, Southern Medical University, Guangzhou, China
      sug:
        subj:
          Carcinoma, Hepatocellular
          Models, Statistical
          Blood Vessels Pathology
          Liver Neoplasms Blood Supply
          Carcinoma, Hepatocellular Pathology
          Retrospective Design
          Neoplasm Invasiveness Pathology
          Hepatitis Viruses Immunology
          Algorithms
          Tomography, X-Ray Computed Methods
          Adolescence
          Middle Age
          Young Adult
          Female
          Predictive Value of Tests
          Portal Vein
          Adult
          Portal Vein Pathology
          alpha Fetoproteins Analysis
          Risk Factors
          Carcinoma, Hepatocellular Blood Supply
          Male
          Liver Neoplasms Pathology
          Preoperative Period
          Aged
          Neoplasm Invasiveness
          Scales
          Adolescent: 13-18 years
          Middle Aged: 45-64 years
          Adult: 19-44 years
          Aged: 65+ years
          Female
          Male
      ab: Purpose: We aimed to develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).Methods: A total of 304 eligible patients with HCC were randomly divided into training (n=184) and independent validation (n=120) cohorts. Portal venous and arterial phase computed tomography data of the HCCs were collected to extract radiomic features. Using the least absolute shrinkage and selection operator algorithm, the training set was processed to reduce data dimensions, feature selection, and construction of a radiomics signature. Then, a prediction model including the radiomics signature, radiologic features, and alpha-fetoprotein (AFP) level, as presented in a radiomics nomogram, was developed using multivariable logistic regression analysis. The radiomics nomogram was analyzed based on its discrimination ability, calibration, and clinical usefulness. Internal cohort data were validated using the radiomics nomogram.Results: The radiomics signature was significantly associated with MVI status (P < 0.001, both cohorts). Predictors, including the radiomics signature, nonsmooth tumor margin, hypoattenuating halos, internal arteries, and alpha-fetoprotein level were reserved in the individualized prediction nomogram. The model exhibited good calibration and discrimination in the training and validation cohorts (C-index [95% confidence interval]: 0.846 [0.787-0.905] and 0.844 [0.774-0.915], respectively). Its clinical usefulness was confirmed using a decision curve analysis.Conclusion: The radiomics nomogram, as a noninvasive preoperative prediction method, shows a favorable predictive accuracy for MVI status in patients with HBV-related HCC.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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