Intraindividual comparison of CT and MRI for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma
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Summary
This summary is machine-generated.Computed tomography (CT) and magnetic resonance imaging (MRI) show similar performance in identifying vessels encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC). These imaging models offer promising predictive capabilities for VETC-positive HCC.
Area Of Science
- Radiology
- Oncology
- Medical Imaging
Background
- Vessels encapsulating tumor clusters (VETC) are a significant indicator of poor prognosis in hepatocellular carcinoma (HCC).
- Accurate preoperative identification of VETC is crucial for treatment planning and patient management.
Purpose Of The Study
- To develop and validate predictive scoring models for VETC in HCC using both computed tomography (CT) and magnetic resonance imaging (MRI).
- To compare the intra-individual predictive performance of CT and MRI for VETC-positive HCC.
Main Methods
- Retrospective analysis of 324 HCC patients who underwent preoperative dynamic CT and MRI.
- Development of separate CT-based and MRI-based logistic regression scoring models.
- Validation of models in a separate cohort and comparison of diagnostic performance using generalized estimating equations.
Main Results
- VETC-positive HCCs showed distinct imaging features on both CT and MRI, including larger size, necrosis, non-smooth margins, targetoid appearance, intratumor artery, and heterogeneous enhancement.
- VETC-positive HCCs were more frequently categorized as LR-M (Liver Imaging Reporting and Data System) on both modalities.
- In the validation cohort, CT and MRI models demonstrated comparable sensitivity, specificity, and AUC values for predicting VETC-positive HCC.
Conclusions
- Preoperative CT and MRI exhibit comparable performance in identifying VETC-positive HCC.
- The developed scoring models show promising predictive capabilities for VETC in HCC.
- Both imaging modalities can provide valuable prognostic information for HCC patients.
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