Radiogenomic Analysis of Oncological Data: A Technical Survey

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 phenoty...

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Published in	International journal of molecular sciences Vol. 18; no. 4; p. 805
Main Authors	Incoronato, Mariarosaria, Aiello, Marco, Infante, Teresa, Cavaliere, Carlo, Grimaldi, Anna, Mirabelli, Peppino, Monti, Serena, Salvatore, Marco
Format	Journal Article
Language	English
Published	Switzerland MDPI AG 12.04.2017 MDPI
Subjects	Algorithms Cancer Computational Biology - methods Data Mining - methods Diagnostic Imaging Gene expression Genomics - methods Genotype & phenotype High-Throughput Nucleotide Sequencing Humans Image Interpretation, Computer-Assisted - methods Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging Medical diagnosis Neoplasms - diagnostic imaging Neoplasms - genetics Positron-Emission Tomography Radiomics Review Tomography, X-Ray Computed microarray MR data mining cancer correlation matrix radiogenomics molecular imaging NGS technologies texture analysis
Online Access	Get full text
ISSN	1422-0067 1661-6596 1422-0067
DOI	10.3390/ijms18040805

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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.
AbstractList	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. 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.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.
Author	Infante, Teresa Monti, Serena Aiello, Marco Cavaliere, Carlo Grimaldi, Anna Salvatore, Marco Mirabelli, Peppino Incoronato, Mariarosaria
AuthorAffiliation	IRCCS SDN, Via E. Gianturco, 113, 80143 Naples, Italy; maiello@sdn-napoli.it (M.A.); tinfante@sdn-napoli.it (T.I.); ccavaliere@sdn-napoli.it (C.C.); agrimaldi@sdn-napoli.it (A.M.G.); pmirabelli@sdn-napoli.it (P.M.); smonti@sdn-napoli.it (S.M.); direzionescientifica@sdn-napoli.it (M.S.)
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Snippet	In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data....
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SubjectTerms	Algorithms Cancer Computational Biology - methods Data Mining - methods Diagnostic Imaging Gene expression Genomics - methods Genotype & phenotype High-Throughput Nucleotide Sequencing Humans Image Interpretation, Computer-Assisted - methods Image Processing, Computer-Assisted - methods Magnetic Resonance Imaging Medical diagnosis Neoplasms - diagnostic imaging Neoplasms - genetics Positron-Emission Tomography Radiomics Review Tomography, X-Ray Computed
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Title	Radiogenomic Analysis of Oncological Data: A Technical Survey
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