Literature DB >> 28418819

Cancer Genomics and Important Oncologic Mutations: A Contemporary Guide for Body Imagers.

Veronica L Cox1, Priya Bhosale1, Gauri R Varadhachary1, Nicolaus Wagner-Bartak1, Isabella C Glitza1, Kathryn A Gold1, Johnique T Atkins1, Pamela T Soliman1, David S Hong1, Aliya Qayyum1.   

Abstract

The field of cancer genomics is rapidly evolving and has led to the development of new therapies. Knowledge of commonly involved cellular pathways and genetic mutations is now essential for radiologists reading oncology cases. Radiogenomics is an emerging area of research that seeks to correlate imaging features with cancer genotypes. Such knowledge may extend the utility of multiparametric imaging to yield information regarding cancer prognosis and likelihood of therapeutic response. To date, only a handful of radiogenomics studies have been performed to evaluate solid tumors of the body, and there is much to explore. Before doing so, however, it behooves us to have adequate background knowledge of clinical cancer genomics to design meaningful radiogenomics projects and explore imaging phenotypes. Herein, an up-to-date, detailed overview is provided of well-known and common mutations of solid body tumors (such as human epithelial growth factor receptor 2, breast cancer susceptibility protein), newer genomic alterations with potential for clinical relevance, and a discussion of known related imaging findings, including existing radiogenomics data and other radiologic patterns of disease. © RSNA, 2017 Online supplemental material is available for this article.

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Year:  2017        PMID: 28418819     DOI: 10.1148/radiol.2017152224

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  4 in total

Review 1.  Patterns of enhancement in the hepatobiliary phase of gadoxetic acid-enhanced MRI.

Authors:  Cathryn L Hui; Marcela Mautone
Journal:  Br J Radiol       Date:  2020-06-01       Impact factor: 3.039

Review 2.  The application of radiomics in predicting gene mutations in cancer.

Authors:  Yana Qi; Tingting Zhao; Mingyong Han
Journal:  Eur Radiol       Date:  2022-01-20       Impact factor: 5.315

3.  Multimodal 3D DenseNet for IDH Genotype Prediction in Gliomas.

Authors:  Sen Liang; Rongguo Zhang; Dayang Liang; Tianci Song; Tao Ai; Chen Xia; Liming Xia; Yan Wang
Journal:  Genes (Basel)       Date:  2018-07-30       Impact factor: 4.096

Review 4.  Cancer genome landscape: a radiologist's guide to cancer genome medicine with imaging correlates.

Authors:  Francesco Alessandrino; Daniel A Smith; Sree Harsha Tirumani; Nikhil H Ramaiya
Journal:  Insights Imaging       Date:  2019-11-28
  4 in total

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