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Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review

OBJECTIVE: : The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assem...

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Autores principales: Seow, Pohchoo, Wong, Jeannie Hsiu Ding, Ahmad-Annuar, Azlina, Mahajan, Abhishek, Abdullah, Nor Aniza, Ramli, Norlisah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The British Institute of Radiology. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319852/
https://www.ncbi.nlm.nih.gov/pubmed/29902076
http://dx.doi.org/10.1259/bjr.20170930
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author Seow, Pohchoo
Wong, Jeannie Hsiu Ding
Ahmad-Annuar, Azlina
Mahajan, Abhishek
Abdullah, Nor Aniza
Ramli, Norlisah
author_facet Seow, Pohchoo
Wong, Jeannie Hsiu Ding
Ahmad-Annuar, Azlina
Mahajan, Abhishek
Abdullah, Nor Aniza
Ramli, Norlisah
author_sort Seow, Pohchoo
collection PubMed
description OBJECTIVE: : The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assembles recent evidence highlighting the value of using radiogenomic biomarkers to infer the underlying biology of gliomas and its correlation with imaging features.  METHODS: : A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging.  RESULTS: : Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented.  CONCLUSION: The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine. ADVANCES IN KNOWLEDGE: : Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma.
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spelling pubmed-63198522019-12-01 Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review Seow, Pohchoo Wong, Jeannie Hsiu Ding Ahmad-Annuar, Azlina Mahajan, Abhishek Abdullah, Nor Aniza Ramli, Norlisah Br J Radiol Systematic Review OBJECTIVE: : The diversity of tumour characteristics among glioma patients, even within same tumour grade, is a big challenge for disease outcome prediction. A possible approach for improved radiological imaging could come from combining information obtained at the molecular level. This review assembles recent evidence highlighting the value of using radiogenomic biomarkers to infer the underlying biology of gliomas and its correlation with imaging features.  METHODS: : A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging.  RESULTS: : Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented.  CONCLUSION: The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine. ADVANCES IN KNOWLEDGE: : Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma. The British Institute of Radiology. 2018-12 2018-06-27 /pmc/articles/PMC6319852/ /pubmed/29902076 http://dx.doi.org/10.1259/bjr.20170930 Text en © 2018 The Authors. Published by the British Institute of Radiology This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License http://creativecommons.org/licenses/by-nc/4.0/, which permits unrestricted non-commercial reuse, provided the original author and source are credited.
spellingShingle Systematic Review
Seow, Pohchoo
Wong, Jeannie Hsiu Ding
Ahmad-Annuar, Azlina
Mahajan, Abhishek
Abdullah, Nor Aniza
Ramli, Norlisah
Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
title Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
title_full Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
title_fullStr Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
title_full_unstemmed Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
title_short Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
title_sort quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319852/
https://www.ncbi.nlm.nih.gov/pubmed/29902076
http://dx.doi.org/10.1259/bjr.20170930
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