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Sci Rep ; 14(1): 11538, 2024 05 21.
Artigo em Inglês | MEDLINE | ID: mdl-38773179

RESUMO

Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for personalized treatment. This study explored the role of ultrasound-based radiomics of peritumoral tissues for predicting HCC features, focusing on differentiation, cytokeratin 7 (CK7) and Ki67 expression, and p53 mutation status. A cohort of 153 patients with HCC underwent ultrasound examinations and radiomics features were extracted from peritumoral tissues. Subgroups were formed based on HCC characteristics. Predictive modeling was carried out using the XGBOOST algorithm in the differentiation subgroup, logistic regression in the CK7 and Ki67 expression subgroups, and support vector machine learning in the p53 mutation status subgroups. The predictive models demonstrated robust performance, with areas under the curves of 0.815 (0.683-0.948) in the differentiation subgroup, 0.922 (0.785-1) in the CK7 subgroup, 0.762 (0.618-0.906) in the Ki67 subgroup, and 0.849 (0.667-1) in the p53 mutation status subgroup. Confusion matrices and waterfall plots highlighted the good performance of the models. Comprehensive evaluation was carried out using SHapley Additive exPlanations plots, which revealed notable contributions from wavelet filter features. This study highlights the potential of ultrasound-based radiomics, specifically the importance of peritumoral tissue analysis, for predicting HCC characteristics. The results warrant further validation of peritumoral tissue radiomics in larger, multicenter studies.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Ultrassonografia , Humanos , Carcinoma Hepatocelular/diagnóstico por imagem , Carcinoma Hepatocelular/patologia , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/metabolismo , Neoplasias Hepáticas/diagnóstico por imagem , Neoplasias Hepáticas/patologia , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismo , Masculino , Feminino , Ultrassonografia/métodos , Pessoa de Meia-Idade , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismo , Idoso , Antígeno Ki-67/metabolismo , Mutação , Adulto , Radiômica
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