The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China; Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China.
The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China.
Crit Rev Oncol Hematol. 2023 Oct;190:104107. doi: 10.1016/j.critrevonc.2023.104107. Epub 2023 Aug 24.
Hepatocellular carcinoma (HCC) is one of the most common and highly lethal tumors worldwide. Microvascular invasion (MVI) is a significant risk factor for recurrence and poor prognosis after surgical resection for HCC patients. Accurately predicting the status of MVI preoperatively is critical for clinicians to select treatment modalities and improve overall survival. However, MVI can only be diagnosed by pathological analysis of postoperative specimens. Currently, numerous indicators in serology (including liquid biopsies) and imaging have been identified to effective in predicting the occurrence of MVI, and the multi-indicator model based on deep learning greatly improves accuracy of prediction. Moreover, several genes and proteins have been identified as risk factors that are strictly associated with the occurrence of MVI. Therefore, this review evaluates various predictors and risk factors, and provides guidance for subsequent efforts to explore more accurate predictive methods and to facilitate the conversion of risk factors into reliable predictors.
肝细胞癌 (HCC) 是全球最常见且致死率极高的肿瘤之一。微血管侵犯 (MVI) 是 HCC 患者手术后复发和预后不良的重要危险因素。准确预测术前 MVI 状态对临床医生选择治疗方式和提高总体生存率至关重要。然而，MVI 只能通过术后标本的病理分析来诊断。目前，已发现众多血清学指标（包括液体活检）和影像学指标可有效预测 MVI 的发生，基于深度学习的多指标模型可极大提高预测准确性。此外，一些基因和蛋白已被确定为与 MVI 发生严格相关的危险因素。因此，本综述评估了各种预测指标和危险因素，为后续探索更准确的预测方法以及将危险因素转化为可靠预测指标的努力提供了指导。
