Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

被引:3
|
作者
Jiang, Yu [1 ,2 ]
Wang, Kang [1 ]
Wang, Yu-Ran [1 ,2 ]
Xiang, Yan-Jun [1 ]
Liu, Zong-Han [1 ]
Feng, Jin-Kai [1 ]
Cheng, Shu-Qun [1 ,2 ,3 ]
机构
[1] Second Mil Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Hepat Surg 6, Shanghai, Peoples R China
[2] Univ Shanghai Sci & Technol, Sch Hlth Sci & Engn, Shanghai, Peoples R China
[3] Second Mil Med Univ, Eastern Hepatobiliary Surg Hosp, 225 Changhai Rd, Shanghai 200438, Peoples R China
基金
中国国家自然科学基金;
关键词
hepatocellular carcinoma; microvascular invasion; artificial intelligence; diagnosis; prediction; NEURAL-NETWORK; DIAGNOSIS; MANAGEMENT; IMAGES; CLASSIFICATION; RESECTION; RISK;
D O I
10.1177/15330338231212726
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensus is urgently needed. Recently, artificial intelligence has emerged as an important tool for improving the clinical management of hepatocellular carcinoma. Many studies about microvascular invasion currently focus on preoperative and prognosis prediction of microvascular invasion using artificial intelligence. In this paper, we review the definition and staging of microvascular invasion, especially the diagnosis of it by using artificial intelligence. In preoperative prediction, deep learning based on multimodal data modeling of radiomics-screened features, clinical features, and medical images is currently the most effective means. In prognostic prediction, pathology is the gold standard, and the techniques used should more effectively utilize the global features of the pathology images.
引用
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页数:10
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