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Related Experiment Video

Updated: Jun 7, 2025

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Preoperative Noninvasive Prediction of Recurrence-Free Survival in Hepatocellular Carcinoma Using CT-Based Radiomics

Ting Dai1, Qian-Biao Gu1, Ying-Jie Peng1

  • 1Department of Radiology, The First Affiliated Hospital of Hunan Normal University (Hunan Provincial People's Hospital), Changsha, Hunan, People's Republic of China.

Journal of Hepatocellular Carcinoma
|November 19, 2024
PubMed
Summary

This study shows that combining radiomics and clinical data improves recurrence-free survival prediction in hepatocellular carcinoma (HCC) patients after surgery. The developed model accurately identifies high-risk individuals for recurrence.

Keywords:
Hepatocellular carcinomacomputed tomographyradiomicsrecurrence-free survival

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Area of Science:

  • Radiology
  • Oncology
  • Data Science

Background:

  • Hepatocellular carcinoma (HCC) recurrence after surgical resection remains a significant clinical challenge.
  • Accurate prediction of recurrence-free survival (RFS) is crucial for patient management and treatment planning.

Purpose of the Study:

  • To evaluate the efficacy of a combined radiomics and clinical parameter model in predicting RFS in HCC patients post-resection.
  • To compare the predictive performance of the combined model against clinical-only and radiomics-only models.

Main Methods:

  • Retrospective analysis of 322 HCC patients who underwent contrast-enhanced CT and radical resection.
  • Development of clinical, radiomics, and combined clinical-radiomics models using Cox regression and LASSO.
  • Assessment of model performance using time-dependent AUC and calibration curves; Kaplan-Meier analysis for RFS evaluation.

Main Results:

  • The combined clinical-radiomics model demonstrated superior RFS prediction accuracy compared to individual models in both training and validation cohorts (AUCs ranging from 0.715 to 0.834).
  • The clinical-radiomics nomogram effectively stratified patients into high- and low-risk subgroups with distinct RFS.
  • Radiomics score correlated positively with microvascular invasion and Edmondson-Steiner grade.

Conclusions:

  • The integrated clinical-radiomics model offers a robust tool for predicting RFS in HCC patients.
  • This model aids in identifying high-risk individuals, facilitating personalized risk stratification and management strategies.