Radiogenomic Predictors of Recurrence in Glioblastoma - A Systematic Review
Glioblastoma, as the most aggressive brain tumor, is associated with a poor prognosis and outcome. To optimize prognosis and clinical therapy decisions, there is an urgent need to stratify patients with increased risk for recurrent tumors and low therapeutic success to optimize individual treatme...
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Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Philipps-Universität Marburg
2022
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Subjects: | |
Online Access: | PDF Full Text |
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Summary: | Glioblastoma, as the most aggressive brain tumor, is associated with a poor prognosis and
outcome. To optimize prognosis and clinical therapy decisions, there is an urgent need to stratify
patients with increased risk for recurrent tumors and low therapeutic success to optimize individual
treatment. Radiogenomics establishes a link between radiological and pathological information.
This review provides a state-of-the-art picture illustrating the latest developments in the use of
radiogenomic markers regarding prognosis and their potential for monitoring recurrence. Databases
PubMed, Google Scholar, and Cochrane Library were searched. Inclusion criteria were defined as
diagnosis of glioblastoma with histopathological and radiological follow-up. Out of 321 reviewed
articles, 43 articles met these inclusion criteria. Included studies were analyzed for the frequency
of radiological and molecular tumor markers whereby radiogenomic associations were analyzed.
Six main associations were described: radiogenomic prognosis, MGMT status, IDH, EGFR status,
molecular subgroups, and tumor location. Prospective studies analyzing prognostic features of
glioblastoma together with radiological features are lacking. By reviewing the progress in the
development of radiogenomic markers, we provide insights into the potential efficacy of such an
approach for clinical routine use eventually enabling early identification of glioblastoma recurrence
and therefore supporting a further personalized monitoring and treatment strategy. |
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Item Description: | Gefördert durch den Open-Access-Publikationsfonds der UB Marburg. |
Physical Description: | 23 Pages |
DOI: | 10.3390/jpm12030402 |