Trial reportAbdominal radiology (New York)2023
Predictive factors of microvascular invasion in patients with intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance images.
Trial report in Abdominal radiology (New York), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Conventional and drug‑eluting bead transarterial chemoembolization in patients with inoperable intrahepatic cholangiocarcinoma: a meta‑analysis.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2024Pooled it
- Reply to the Letter to the Editor: Preoperative prediction of microvascular invasion in ICCA-how far can gadoxetate MRI go?European radiology · 2026Article
- Preoperative prediction model of microvascular invasion in intrahepatic cholangiocarcinoma patients based on CT radiomics can assist clinical surgical decision-making: a multicenter study.European radiology · 2026Article
- Preoperative scoring system for predicting microvascular invasion in intrahepatic cholangiocarcinoma using gadoxetate-enhanced MRI.European radiology · 2025Article
- MRI-based microvascular invasion prediction in mass-forming intrahepatic cholangiocarcinoma: survival and therapeutic benefit.European radiology · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this retrospective study was to develop and validate a preoperative nomogram for predicting microvascular invasion (MVI) in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) based on magnetic resonance imaging (MRI).
methodsIn this retrospective study, 224 consecutive patients with clinicopathologically confirmed IMCC were enrolled. Patients whose data were collected from February 2010 to December 2020 were randomly divided into the training (131 patients) and internal validation (51 patients) datasets. The data from January 2021 to November 2021 (42 patients) were allocated to the time-independent validation dataset. Univariate and multivariate forward logistic regression analyses were used to identify preoperative MRI features that were significantly related to MVI, which were then used to develop the nomogram. We used the area under the receiver operating characteristic curve (AUC) and calibration curve to evaluate the performance of the nomogram.
resultsInterobserver agreement of MRI qualitative features was good to excellent, with κ values of 0.613-0.882. Multivariate analyses indicated that the following variables were independent predictors of MVI: multiple tumours (odds ratio [OR]) = 4.819, 95% confidence interval [CI] 1.562-14.864, P = 0.006), ill-defined margin (OR = 6.922, 95% CI 2.883-16.633, P < 0.001), and carbohydrate antigen 19-9 (CA 19-9) > 37 U/ml (OR = 2.890, 95% CI 1.211-6.897, P = 0.017). A nomogram incorporating these factors was established using well-fitted calibration curves. The nomogram showed good diagnostic efficacy for MVI, with AUC values of 0.838, 0.819, and 0.874 for the training, internal validation, and time-independent validation datasets, respectively.
conclusionA nomogram constructed using independent factors, namely the presence of multiple tumours, ill-defined margins, and CA 19-9 > 37 U/ml could predict the presence of MVI. This can facilitate personalised therapeutic strategy and clinical management in patients with IMCC.
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