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Diagnostics 2019, 9(1), 4;

Radiogenomics and Radiomics in Liver Cancers

Division of Vascular and Interventional Radiology, Minimally Invasive Therapeutics Laboratory, Mayo Clinic, Phoenix, AZ 85054, USA
Department of Interventional Radiology, MD Anderson Cancer Center, Houston, TX 77030, USA
Author to whom correspondence should be addressed.
Received: 1 December 2018 / Revised: 20 December 2018 / Accepted: 23 December 2018 / Published: 27 December 2018
(This article belongs to the Special Issue Imaging-Based Diagnostics in Interventional Medicine)
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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. View Full-Text
Keywords: radiogenomics; radiomics; hepatocellular carcinoma; intrahepatic cholangiocarcinoma; liver metastasis radiogenomics; radiomics; hepatocellular carcinoma; intrahepatic cholangiocarcinoma; liver metastasis

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Saini, A.; Breen, I.; Pershad, Y.; Naidu, S.; Knuttinen, M.G.; Alzubaidi, S.; Sheth, R.; Albadawi, H.; Kuo, M.; Oklu, R. Radiogenomics and Radiomics in Liver Cancers. Diagnostics 2019, 9, 4.

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