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February 14, 2026Frontiers in OncologyOpen Access

Integration of multiparametric MRI and clinical indicators to predict response to immune-targeted therapy in patients with advanced hepatocellular carcinoma

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Authors

SHShuai HanHenan Cancer HospitalFMFan MengHenan Cancer HospitalLWLi-feng WangHenan Cancer Hospital

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Implication

Retrospective analysis predicts treatment responses in advanced hepatocellular carcinoma, enhancing predictive efficiency.

Key Points

  • This investigation aims to evaluate a predictive model that combines multiparametric MRI with clinical indicators to forecast responses to immune-targeted therapy in advanced hepatocellular carcinoma.
  • Conducted a retrospective analysis with 78 HCC patients receiving immune-targeted therapy.
  • Performed abdominal MRI scans before and after treatment to assess therapy response.
  • Employed LASSO regression for feature selection and multivariate logistic regression to identify predictors.
  • Utilized ROC curves for model evaluation, alongside decision curve and calibration curves.
  • Identified independent predictors such as post-treatment T2 signal intensity ratio, ADC mean value, and neutrophil to lymphocyte ratio.
  • Achieved ROC AUCs of 0.751 for imaging, 0.614 for clinical, and 0.811 for combined models.
  • Patients in the high-risk group demonstrated a median PFS of 5.0 months, significantly shorter than 7.0 months for low-risk patients (p < 0.05).

Cite This Study

Han et al. (2026) studied this question.

synapsesocial.com/papers/699010382ccff479cfe56c83https://doi.org/10.3389/fonc.2026.1689963
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