ArticleFrontiers in oncology2021
A Novel Clinical-Radiomics Model Based on Sarcopenia and Radiomics for Predicting the Prognosis of Intrahepatic Cholangiocarcinoma After Radical Hepatectomy.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 18 citations in OpenAlex.
- A novel interpretable machine learning framework integrating clinicopathological and radiomic features for early recurrence prediction in mass-forming intrahepatic cholangiocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Global trends in sarcopenia and cancer over the past 10 years: a bibliometric analysis.Discover oncology · 2025Article
- Preoperative prediction of textbook outcome in intrahepatic cholangiocarcinoma by interpretable machine learning: A multicenter cohort study.World journal of gastroenterology · 2025Article
- Contrast-Enhanced Imaging in the Management of Intrahepatic Cholangiocarcinoma: State of Art and Future Perspectives.Cancers · 2023Review
- Prognostic value of computed tomography radiomics features in patients with gastric neuroendocrine neoplasm.Frontiers in oncology · 2023Article
- Development of sarcopenia-based nomograms predicting postoperative complications of benign liver diseases undergoing hepatectomy: A multicenter cohort study.Frontiers in nutrition · 2023Article
- Personalized intrahepatic cholangiocarcinoma prognosis prediction using radiomics: Application and development trend.Frontiers in oncology · 2023Review
- Multi-phase-combined CECT radiomics models for Fuhrman grade prediction of clear cell renal cell carcinoma.Frontiers in oncology · 2023Article
- Conventional, functional and radiomics assessment for intrahepatic cholangiocarcinoma.Infectious agents and cancer · 2022Article
- Preoperative Assessment of Skeletal Muscle Mass and Muscle Quality Using Computed Tomography: Incidence of Sarcopenia in Patients with Intrahepatic Cholangiocarcinoma Selected for Liver Resection.Journal of clinical medicine · 2022Article
- An update on radiomics techniques in primary liver cancers.Infectious agents and cancer · 2022Article
- Establish a New Diagnosis of Sarcopenia Based on Extracted Radiomic Features to Predict Prognosis of Patients With Gastric Cancer.Frontiers in nutrition · 2022Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntrahepatic cholangiocarcinoma (ICC) is a highly aggressive malignant tumor with a poor prognosis. This study aimed to establish a novel clinical-radiomics model for predicting the prognosis of ICC after radical hepatectomy.
methodsA clinical-radiomics model was established for 82 cases of ICC treated with radical hepatectomy in our hospital from May 2011 to December 2020. Radiomics features were extracted from venous-phase and arterial-phase images of computed tomography. Kaplan-Meier survival analysis was generated to compare overall survival (OS) between different groups. The independent factors were identified by univariate and multivariate Cox regression analyses. Nomogram performance was evaluated regarding discrimination, calibration, and clinical utility. C-index and area under the curve (AUC) were utilized to compare the predictive performance between the clinical-radiomics model and conventional staging systems.
resultsThe radiomics model included five features. The AUC of the radiomics model was 0.817 in the training cohort, and 0.684 in the validation cohort. The clinical-radiomics model included psoas muscle index, radiomics score, hepatolithiasis, carcinoembryonic antigen, and neutrophil/lymphocyte ratio. The reliable C-index of the model was 0.768, which was higher than that of other models. The AUC of the model for predicting OS at 1, and 3 years was 0.809 and 0.886, which was significantly higher than that of the American Joint Committee on Cancer 8
conclusionThe clinical-radiomics model integrating sarcopenia, clinical features, and radiomics score was accurate for prognostic prediction for mass-forming ICC patients. It provided an individualized prognostic evaluation in patients with mass-forming ICC and could helped surgeons with clinical decision-making.
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