放射基因组学
无线电技术
医学
肝细胞癌
临床影像学
病理
放射科
生物信息学
内科学
生物
作者
Aman Saini,Ilana Breen,Yash Pershad,Sailendra Naidu,M-Grace Knuttinen,Sadeer Alzubaidi,Rahul A. Sheth,Hassan Albadawi,Malia Kuo,Rahmi Öklü
出处
期刊:Diagnostics
[Multidisciplinary Digital Publishing Institute]
日期:2018-12-27
卷期号:9 (1): 4-4
被引量:53
标识
DOI:10.3390/diagnostics9010004
摘要
Radiogenomics is a computational discipline that identifies correlations between cross-sectional imaging features and tissue-based molecular data. These imaging phenotypic correlations can then potentially be used to longitudinally and non-invasively predict a tumor's molecular profile. A different, but related field termed radiomics examines the extraction of quantitative data from imaging data and the subsequent combination of these data with clinical information in an attempt to provide prognostic information and guide clinical decision making. Together, these fields represent the evolution of biomedical imaging from a descriptive, qualitative specialty to a predictive, quantitative discipline. It is anticipated that radiomics and radiogenomics will not only identify pathologic processes, but also unveil their underlying pathophysiological mechanisms through clinical imaging alone. Here, we review recent studies on radiogenomics and radiomics in liver cancers, including hepatocellular carcinoma, intrahepatic cholangiocarcinoma, and metastases to the liver.
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