Contributing to the prediction of prognosis for treated hepatocellular carcinoma: Imaging aspects that sculpt the future

A novel nomogram model to predict the prognosis of hepatocellular carcinoma (HCC) treated with radiofrequency ablation and transarterial chemoembolization was recently published in the <i>World Journal of Gastrointestinal Surgery</i>. This model includes clinical and laboratory factors, but emerging imaging aspects, particularly from magnetic resonance imaging (MRI) and radiomics, could enhance the predictive accuracy thereof. Multiparametric MRI and deep learning radiomics models significantly improve prognostic predictions for the treatment of HCC. Incorporating advanced imaging features, such as peritumoral hypointensity and radiomics scores, alongside clinical factors, can refine prognostic models, aiding in personalized treatment and better predicting outcomes. This letter underscores the importance of integrating novel imaging techniques into prognostic tools to better manage and treat HCC.

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Publication Details

Journal
World Journal of Gastrointestinal Surgery
Published
2024-09-27
DOI
https://doi.org/10.4240/wjgs.v16.i10.3377
Citations
2
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
0.74
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article

Contributing to the prediction of prognosis for treated hepatocellular carcinoma: Imaging aspects that sculpt the future

Cristian Lindner
2 citations
World Journal of Gastrointestinal Surgery
Hepatocellular Carcinoma Treatment and Prognosis
0.74
article

Contributing to the prediction of prognosis for treated hepatocellular carcinoma: Imaging aspects that sculpt the future

Cristian Lindner
article en
2 citations

Abstract

A novel nomogram model to predict the prognosis of hepatocellular carcinoma (HCC) treated with radiofrequency ablation and transarterial chemoembolization was recently published in the <i>World Journal of Gastrointestinal Surgery</i>. This model includes clinical and laboratory factors, but emerging imaging aspects, particularly from magnetic resonance imaging (MRI) and radiomics, could enhance the predictive accuracy thereof. Multiparametric MRI and deep learning radiomics models significantly improve prognostic predictions for the treatment of HCC. Incorporating advanced imaging features, such as peritumoral hypointensity and radiomics scores, alongside clinical factors, can refine prognostic models, aiding in personalized treatment and better predicting outcomes. This letter underscores the importance of integrating novel imaging techniques into prognostic tools to better manage and treat HCC.

World Journal of Gastrointestinal SurgeryVol. 16(10)
University of Concepción (CL), Hospital Regional de Concepción (CL), University of Bío-Bío (CL)
Good health and well-being
Openalex Percentile: Top 28%
Hepatocellular Carcinoma Treatment and Prognosis
0.74
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