ArticleAbdominal radiology (New York)2021
Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics.
Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Comparative multiphase CT radiomics for differentiating isolated hepatic metastasis from intrahepatic cholangiocarcinoma: a two-center study of native, subtraction, peritumoral, and fusion models.Frontiers in oncology · 2026Article
- Leveraging radiomics and AI for precision diagnosis and prognostication of liver malignancies.Frontiers in oncology · 2024Review
- Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative.Insights into imaging · 2023Article
- Personalized intrahepatic cholangiocarcinoma prognosis prediction using radiomics: Application and development trend.Frontiers in oncology · 2023Review
- Role of hepatic metastatic lesion size on inter-reader reproducibility of CT-based radiomics features.European radiology · 2022Article
- An update on radiomics techniques in primary liver cancers.Infectious agents and cancer · 2022Article
- A Novel Clinical-Radiomics Model Based on Sarcopenia and Radiomics for Predicting the Prognosis of Intrahepatic Cholangiocarcinoma After Radical Hepatectomy.Frontiers in oncology · 2021Article
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10 authors.
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Abstract
purposeTo test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model.
methodsHistologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous phase computed tomography (CT), by two readers with different experience (R1 and R2). Morphological CT features included: tumor size, hepatic satellite lesions, lymph node and distant metastases. Radiomic features (RF) were compared across CT protocols and readers. Univariate analysis against overall survival (OS) warranted ranking and selection of RF into radiomic signature (RSign), which was dichotomized into high and low-risk strata (RSign*). Models without and with RSign* (Model 1 and 2, respectively) were compared.
resultsAmong 78 patients (median follow-up 262 days, IQR 73-957), 62/78 (79%) died during the study period, 46/78 (59%) died within 1 year. Up to 10% RF showed variability across CT protocols; 37/108 (34%) RF showed variability due to manual segmentation. RSign stratified OS (univariate: HR 1.37 for R1, HR 1.28 for R2), RSign* was different between readers (R1 0.39; R2 0.57). Model 1 showed AUC 0.71, which increased in Model 2: AUC 0.81 (p < 0.001) and AIC 89 for R1, AUC 0.81 (p = 0.001) and AIC 90.2 for R2.
conclusionThe use of RF into a unified RSign score stratified OS in patients with IMCC. Dichotomized RSign* classified survival strata, its inclusion in risk models showed adjunct yield. The cut-off value of RSign* was different between readers, suggesting that the use of reference values is hampered by interobserver variability.
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