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Int. J. Mol. Sci. 2017, 18(4), 805; doi:10.3390/ijms18040805

Radiogenomic Analysis of Oncological Data: A Technical Survey

IRCCS SDN, Via E. Gianturco, 113, 80143 Naples, Italy
These authors contributed equally to this work.
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Academic Editors: Jamal Zweit and Sundaresan Gobalakrishnan
Received: 30 December 2016 / Revised: 6 April 2017 / Accepted: 8 April 2017 / Published: 12 April 2017
(This article belongs to the Special Issue Cancer Molecular Imaging in the Era of Precision Medicine)
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Abstract

In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data. Such information has increased in complexity from basic (i.e., blood samples) to extensive sets encompassing many aspects of a subject phenotype, and now rapidly extending into genetic and, more recently, radiomic information. Radiogenomics integrates both aspects, investigating the relationship between imaging features and gene expression. From a methodological point of view, radiogenomics takes advantage of non-conventional data analysis techniques that reveal meaningful information for decision-support in cancer diagnosis and treatment. This survey is aimed to review the state-of-the-art techniques employed in radiomics and genomics with special focus on analysis methods based on molecular and multimodal probes. The impact of single and combined techniques will be discussed in light of their suitability in correlation and predictive studies of specific oncologic diseases. View Full-Text
Keywords: radiogenomics; cancer; MR; texture analysis; microarray; NGS technologies; correlation matrix; molecular imaging; data mining radiogenomics; cancer; MR; texture analysis; microarray; NGS technologies; correlation matrix; molecular imaging; data mining
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Incoronato, M.; Aiello, M.; Infante, T.; Cavaliere, C.; Grimaldi, A.M.; Mirabelli, P.; Monti, S.; Salvatore, M. Radiogenomic Analysis of Oncological Data: A Technical Survey. Int. J. Mol. Sci. 2017, 18, 805.

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