ArticleInsights into imaging2023
A CT-based radiomics approach to predict intra-tumoral tertiary lymphoid structures and recurrence of intrahepatic cholangiocarcinoma.
Article in Insights into imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Development of an HDL-C combined with AJCC staging system for predicting overall survival after curative resection of intrahepatic cholangiocarcinoma without metabolic comorbidities.Frontiers in oncology · 2026Article
- Tertiary lymphoid structure topotypes in intrahepatic cholangiocarcinoma: spatial immunity, checkpoint-response associations, and therapeutic reprogramming.Frontiers in immunology · 2026Review
- Artificial intelligence in the diagnosis and prognosis of intrahepatic cholangiocarcinoma: Applications and challenges.World journal of gastrointestinal oncology · 2025Review
- Radiomics-based machine-learning method to predict extrahepatic metastasis in hepatocellular carcinoma after hepatectomy: a multicenter study.Scientific reports · 2025Article
- A novel hybrid model for predicting tertiary lymphoid structures and targeted immunotherapy outcomes in hepatocellular carcinoma: a multicenter retrospective study.European radiology · 2025Article
- Prediction of Ki-67 expression in hepatocellular carcinoma with machine learning models based on intratumoral and peritumoral radiomic features.World journal of gastrointestinal oncology · 2025Article
- Diagnosis of Cholangiocarcinoma: The New Biological and Technological Horizons.Diagnostics (Basel, Switzerland) · 2025Review
- ChatGPT as an effective tool for quality evaluation of radiomics research.European radiology · 2025Article
- Transfer learning radiomic model predicts intratumoral tertiary lymphoid structures in hepatocellular carcinoma: a multicenter study.Journal for immunotherapy of cancer · 2025Article
- Overlooked and underpowered: a meta-research addressing sample size in radiomics prediction models for binary outcomes.European radiology · 2025Article
- B cells and tertiary lymphoid structures in tumors: immunity cycle, clinical impact, and therapeutic applications.Theranostics · 2025Review
- Machine learning-driven prediction of intratumoral tertiary lymphoid structures in hepatocellular carcinoma using contrast-enhanced CT imaging and integrated clinical data.Frontiers in oncology · 2025Article
- Tertiary lymphoid structures: exploring opportunities to improve immunotherapy in ovarian cancer.Frontiers in immunology · 2025Review
- Tertiary lymphoid structures in renal cell carcinoma: from heterogeneity dissection to translational precision immunotherapy.Frontiers in immunology · 2025Review
- Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study.Journal for immunotherapy of cancer · 2024Article
- Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application.Molecular cancer · 2024Review
- Review
- Multi-omics profiling and experimental verification of tertiary lymphoid structure-related genes: molecular subgroups, immune infiltration, and prognostic implications in lung adenocarcinoma.Frontiers in immunology · 2024Article
- Global trends in tertiary lymphoid structures: a bibliometric analysis from 2014 to 2023.Frontiers in immunology · 2024Article
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14 authors.
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Abstract
purposeTo predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative CT radiomics. PATIENTS AND
methodsA total of 116 ICC patients were included (training: 86; external validation: 30). The enhanced CT images were performed for the radiomics model. The logistic regression analysis was applied for the clinical model. The combined model was based on the clinical and radiomics models.
resultsA total of 107 radiomics features were extracted, and after being eliminated and selected, six features were combined to establish a radiomics model for TLSs prediction. Arterial phase diffuse hyperenhancement and AJCC 8th stage were combined to construct a clinical model. The combined (radiomics nomogram) model outperformed both the independent radiomics model and clinical model in the training cohort (AUC, 0.85 vs. 0.82 and 0.75, respectively) and was validated in the external validation cohort (AUC, 0.88 vs. 0.86 and 0.71, respectively). Patients in the rad-score no less than -0.76 (low-risk) group showed significantly better RFS than those in the less than -0.76 (high-risk) group (p < 0.001, C-index = 0.678). Patients in the nomogram score no less than -1.16 (low-risk) group showed significantly better RFS than those of the less than -1.16 (high-risk) group (p < 0.001, C-index = 0.723).
conclusionsCT radiomics nomogram could serve as a preoperative biomarker of intra-tumoral TLSs status, better than independent radiomics or clinical models; preoperative CT radiomics nomogram achieved accurate stratification for RFS of ICC patients, better than the postoperative pathologic TLSs status. CRITICAL RELEVANCE STATEMENT: The radiomics nomogram showed better performance in predicting TLSs than independent radiomics or clinical models and better prognosis stratification than postoperative pathologic TLSs status in ICC patients, which may facilitate identifying patients benefiting most from surgery and subsequent immunotherapy. KEY POINTS: • The combined (radiomics nomogram) model consisted of the radiomics model and clinical model (arterial phase diffuse hyperenhancement and AJCC 8th stage). • The radiomics nomogram showed better performance in predicting TLSs than independent radiomics or clinical models in ICC patients. • Preoperative CT radiomics nomogram achieved more accurate stratification for RFS of ICC patients than the postoperative pathologic TLSs status.
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