Research progress on prediction models related to microvascular invasion in hepatocellular carcinoma

VernacularTitle:肝细胞癌微血管侵犯相关预测模型的研究进展
Author: Weihong ZHUANG ¹ ; Wentian ZHU
Author Information

1. 广东医科大学第一临床学院，湛江　524000
Keywords: Carcinoma, hepatocellular; Microvascular invasion; Prediction models; Radiomics; Deep learning
From: Journal of International Oncology 2025;52(5):315-318
CountryChina
Language:Chinese
Abstract: Hepatocellular carcinoma (HCC) is one of the common malignant tumors of the digestive system, threatening human life and health. Microvascular invasion (MVI) is an important indicator reflecting the prognosis of HCC patients. The individualized treatment plan predicted and provided by MVI before surgery is of great significance to improve the long-term efficacy of HCC patients. Many studies have built various prediction models for MVI in HCC patients, such as logistic regression scoring models, nomogram models, radiomics models, and deep learning models based on clinical features, imaging features, radiomics, proteomics, and genomics. With the deepening of research, the accuracy of MVI prediction in patients with HCC has been continuously improved, which can also better guide the treatment of HCC.