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Updated: Jan 5, 2026

A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma
Published on: September 30, 2021
Pathobiological and Radiological Approach For Hepatocellular Carcinoma Subclassification
Francesco Vasuri1, Matteo Renzulli2, Silvia Fittipaldi1
1Pathology Unit, S. Orsola University Hospital, Bologna, Italy.
Magnetic resonance imaging (MRI) can identify aggressive hepatocellular carcinoma (HCC) patterns. New morphovascular patterns linked to MRI features help predict HCC prognosis before surgery.
Area of Science:
- Hepatobiliary imaging
- Oncologic pathology
- Radiology
Background:
- Classic imaging and histopathological features of hepatocellular carcinoma (HCC) are insufficient for predicting patient prognosis.
- Advances in imaging and histopathology necessitate novel methods for assessing HCC aggressiveness.
Purpose of the Study:
- To establish a correlation between novel morphovascular patterns of HCC and their magnetic resonance imaging (MRI) characteristics.
- To identify pre-operative MRI markers indicative of biologically aggressive HCC.
Main Methods:
- Histopathological analysis and immunohistochemistry (CD34, Nestin) were used to classify four HCC morphovascular patterns in 39 liver nodules from 22 patients.
- MRI was performed using gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid to evaluate nodule characteristics.
Main Results:
- Three of the four morphovascular HCC patterns exhibited distinct MRI features.
- Pattern D (aggressive HCCs with CD34+/Nestin+ neovascularization) showed isointensity on T1-weighted imaging (T1-WI) in 83% and hyperintensity on T2-weighted imaging (T2-WI) in 50% of cases.
- Five HCCs (Pattern A) were misclassified as non-malignant on MRI due to early vascularization and low aggressiveness.
Conclusions:
- A subclassification of HCC based on morphovascular patterns is feasible in the pre-operative setting using MRI.
- MRI can effectively differentiate HCC morphovascular patterns, aiding in the pre-operative identification of biologically aggressive tumors.
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