基于人工智能的肝细胞癌精准影像学诊断和复发预测

刘一萍; 李新平; 陈磊; 夏金菊; 宋凯荣; 贾宁阳; 刘婉敏

doi:10.3969/j.issn.1001-5256.2022.03.006

基于人工智能的肝细胞癌精准影像学诊断和复发预测

DOI: 10.3969/j.issn.1001-5256.2022.03.006

刘一萍¹,
李新平¹,
陈磊²,
夏金菊¹,
宋凯荣¹,
贾宁阳^1, , ,,
刘婉敏^{1, 3, , ,}

1.
海军军医大学第三附属医院，上海东方肝胆外科医院放射科，上海 200438
2.
上海联影智能医疗科技有限公司，上海 201807
3.
同济大学医学院，同济大学附属同济医院放射科，上海 200331

基金项目:

艾滋病和病毒性肝炎等重大传染病防治专项 (2018ZX10302207-004-005)

利益冲突声明: 所有作者均声明不存在利益冲突。

作者贡献声明: 刘一萍、李新平、夏金菊、宋凯荣负责文献收集与总结; 陈磊、刘婉敏及贾宁阳负责文章攥写及修改。

详细信息

通信作者:
贾宁阳，jiany@sh163.net

刘婉敏，18389376537@163.com

刘一萍、李新平、陈磊对本文贡献等同，同为第一作者

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- 文章访问数: 1212
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- 被引次数: 16
出版历程
- 收稿日期: 2022-01-04
- 录用日期: 2022-01-14
- 出版日期: 2022-03-20

Accurate imaging diagnosis and recurrence prediction of hepatocellular carcinoma based on artificial intelligence

Yiping LIU¹,
Xinping LI¹,
Lei CHEN²,
Jinju XIA¹,
Kairong SONG¹,
Ningyang JIA^{1
, ,
,},
Wanmin LIU^{1, 3
, ,
,}

1.
Department of Radiology, The Third Affiliated Hospital of Navy Medical University & Eastern Hepatobiliary Surgery Hospital, Shanghai 200438, China
2.
Shanghai United Imaging Healthcare Co., Ltd., Shanghai 201807, China
3.
Department of Radiology, Tongji Hospital Affiliated to Tongji University, Tongji University School of Medicine, Shanghai 200331, China

Research funding:

Special Project for Control and Prevention of Major Infectious Diseases such as AIDS and Hepatitis (2018ZX10302207-004-005)

More Information

Corresponding author: JIA Ningyang, jiany@sh163.net(ORCID: 0000-0001-9587-3637); LIU Wanmin, 18389376537@163.com(ORCID: 0000-0002-8216-0424)

摘要

摘要: 人工智能在医疗领域的融合发展迅速，特别在影像医学的诊断、治疗和疗效评估等方面有突破性进展。本文回顾了人工智能在肝细胞癌影像学诊断及其结合临床特征进行疗效评估和预后预测的效能方面的研究进展，展望了在日益增长的临床需求与快速进步的诊疗技术时代，如何将人工智能更好地运用于肝细胞癌影像学实践中。
- 肝细胞癌 /
- 诊断显像 /
- 复发 /
- 预测
Abstract: The integration of artificial intelligence into the medical field is developing rapidly and has achieved ground-breaking advances in the diagnosis, treatment, and efficacy evaluation of imaging medicine. This article reviews the research advances in artificial intelligence in imaging diagnosis of hepatocellular carcinoma and its performance in evaluating treatment outcome and predicting prognosis in combination with clinical features and looks forward to how artificial intelligence can be better used in the practice of hepatocellular carcinoma imaging in the era of growing clinical needs and rapid advances in diagnosis and treatment techniques.
- Hepatocellular Carcinoma /
- Diagnostic Imaging /
- Recurrence /
- Forecasting

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