Omics and Prognstic Markers

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doi:10.1093/neuonc/not183

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2019

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“…A number of prominent somatic mutations (namely TP53, RB1, NF1, EGFR, and PDGFRA) were found to be associated with volumetric parameters on T1 contrast and T2 FLAIR MR images [43]. The first purely quantitative analysis integrated GBM "multi-omics" data, containing multiple "-omes" such as the genome, transcriptome, and proteome, from the TCGA and their corresponding images from The Cancer Imaging Archive (TCIA) [44,45]. Zinn et al identified "radiomic profiles" that helped to discriminate the mutational landscape (i.e., TP53, PTEN, and EGFR) on a dataset of 29 TCGA patients [46].…”

Section: Brainmentioning

confidence: 99%

Radiogenomics: bridging imaging and genomics

et al. 2019

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From diagnostics to prognosis to response prediction, new applications for radiomics are rapidly being developed. One of the fastest evolving branches involves linking imaging phenotypes to the tumor genetic profile, a field commonly referred to as "radiogenomics." In this review, a general outline of radiogenomic literature concerning prominent mutations across different tumor sites will be provided. The field of radiogenomics originates from image processing techniques developed decades ago; however, many technical and clinical challenges still need to be addressed. Nevertheless, increasingly accurate and robust radiogenomic models are being presented and the future appears to be bright.

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