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Imaging Signatures of Glioblastoma Molecular Characteristics: A Radiogenomics Review Publisher Pubmed



Fathi Kazerooni A1, 2 ; Bakas S1, 2, 3 ; Saligheh Rad H4 ; Davatzikos C1, 2
Authors
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Authors Affiliations
  1. 1. Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, United States
  2. 2. Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
  3. 3. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
  4. 4. Quantitative MR Imaging and Spectroscopy Group (QMISG), Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran

Source: Journal of Magnetic Resonance Imaging Published:2020


Abstract

Over the past few decades, the advent and development of genomic assessment methods and computational approaches have raised the hopes for identifying therapeutic targets that may aid in the treatment of glioblastoma. However, the targeted therapies have barely been successful in their effort to cure glioblastoma patients, leaving them with a grim prognosis. Glioblastoma exhibits high heterogeneity, both spatially and temporally. The existence of different genetic subpopulations in glioblastoma allows this tumor to adapt itself to environmental forces. Therefore, patients with glioblastoma respond poorly to the prescribed therapies, as treatments are directed towards the whole tumor and not to the specific genetic subregions. Genomic alterations within the tumor develop distinct radiographic phenotypes. In this regard, MRI plays a key role in characterizing molecular signatures of glioblastoma, based on regional variations and phenotypic presentation of the tumor. Radiogenomics has emerged as a (relatively) new field of research to explore the connections between genetic alterations and imaging features. Radiogenomics offers numerous advantages, including noninvasive and global assessment of the tumor and its response to therapies. In this review, we summarize the potential role of radiogenomic techniques to stratify patients according to their specific tumor characteristics with the goal of designing patient-specific therapies. Level of Evidence: 5. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2020;52:54–69. © 2019 International Society for Magnetic Resonance in Medicine
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