ArticleEuropean radiology2025
A novel hybrid model for predicting tertiary lymphoid structures and targeted immunotherapy outcomes in hepatocellular carcinoma: a multicenter retrospective study.
Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Deep learning-based CT model for non-invasive prediction of tertiary lymphoid structures in pancreatic cancer: a multicenter study with prospective validation in an immunochemotherapy cohort.Journal for immunotherapy of cancer · 2026Trial
- Review
- Emerging Role of MRI-Based Artificial Intelligence in Individualized Treatment Strategies for Hepatocellular Carcinoma: A Narrative Review.Journal of magnetic resonance imaging : JMRI · 2026Review
- Large Language Models for Preoperative Microvascular Invasion Prediction in Hepatocellular Carcinoma: A Multicenter Comparison with Radiologists and Treatment Outcomes.Journal of hepatocellular carcinoma · 2026Article
- Intratumoral Tertiary Lymphoid Structures in Hepatocellular Carcinoma: Current Evidence and Future Directions - a Narrative Review.Journal of hepatocellular carcinoma · 2026Review
- Research progress of tertiary lymphoid structure in hepatocellular carcinoma: from prognostic biomarkers to new strategies for immunotherapy.Frontiers in immunology · 2026Review
- Comparison of stereotactic body radiotherapy following transcatheter arterial chemoembolizationWorld journal of gastrointestinal surgery · 2025Article
- An Interpretable Radiomics-Based Model Using Susceptibility-Weighted Imaging for Non-Invasive Prediction of Tertiary Lymphoid Structures in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
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10 authors.
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Abstract
objectiveTo develop a novel hybrid model for preoperative prediction of tertiary lymphoid structures (TLSs) of hepatocellular carcinoma (HCC), and to identify patients who may benefit from postoperative targeted immunotherapy.
methodsRetrospective data were gathered from 332 patients with HCC who underwent surgical resection and gadoxetate disodium (Gd-EOB-DTPA) enhanced MRI at two tertiary hospitals (training cohort, n = 205; internal validation cohort, n = 90; and external validation cohort, n = 37) between March 2020 and January 2023. Radiomic features were extracted from Gd-EOB-DTPA-enhanced MRI sequences. These signatures were integrated with clinical-radiologic (CR) factors into a hybrid model and nomogram for clinical application. The performance of the model was assessed using the area under the curve (AUC) and 95% confidence intervals (CI).
resultsThe hybrid model outperformed the radiomics and CR models in the training cohort (AUC = 0.860 [95% CI: 0.805, 0.904], 0.784 [95% CI: 0.721, 0.838], and 0.809 [95% CI: 0.748, 0.860]). The hybrid model showed optimal performance, with AUCs of 0.823 (95% CI: 0.728, 0.895) and 0.875 (95% CI: 0.725, 0.960) in the internal and external validation cohorts, respectively. The calibration curve demonstrated that the nomogram had good diagnostic ability, and decision curve analysis indicated good clinical utility across all cohorts. Importantly, patients with a predicted high risk of TLSs from the hybrid model gained a survival benefit from targeted immunotherapy.
conclusionThe hybrid model showed satisfactory performance in predicting intra-tumoral TLS positivity and targeted immunotherapy benefit in patients with HCC, potentially assisting clinicians in selecting precise individualized therapies. KEY POINTS: Question How can accurate preoperative risk stratification of tertiary lymphoid structures positivity HCC be achieved to support targeted immunotherapy decision-making? Findings A hybrid model combining radiomics model and clinical-radiological model may be a reliable marker for predicting tertiary lymphoid structures positivity HCC. Clinical relevance Using this hybrid model may be useful in predicting tertiary lymphoid structures and screening candidate patients for targeted immunotherapy based on multiparametric MRI, which has potential clinical value in guiding clinical decision-making and improving patient outcomes.
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