Research progress of MRI in glioma grading and molecular genetic biomarkers

<p>The pathological and imaging diagnosis of glioma has significantly evolved in recent years. Glioma grading, together with a number of molecular genetic biomarkers, has been recognized as an important prognostic and predictive factor, which can also guide the treatment strategy of glioma....

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Main Authors: Shan-shan ZHANG, Lin YU
Format: Article
Language:English
Published: Tianjin Huanhu Hospital 2017-01-01
Series:Chinese Journal of Contemporary Neurology and Neurosurgery
Subjects:
Online Access:http://www.cjcnn.org/index.php/cjcnn/article/view/1539
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spelling doaj-adaa860da3b64332a33c800ece5b71952020-11-25T01:29:38ZengTianjin Huanhu HospitalChinese Journal of Contemporary Neurology and Neurosurgery1672-67312017-01-0117169731508Research progress of MRI in glioma grading and molecular genetic biomarkersShan-shan ZHANG0Lin YU1Department of Medical Image, Tianjin Medical University General Hospital, Tianjin 300052, ChinaDepartment of Biochemistry and Molecular Biology, School of Basic Medical Science, Tianjin Medical University, Tianjin 300070, China<p>The pathological and imaging diagnosis of glioma has significantly evolved in recent years. Glioma grading, together with a number of molecular genetic biomarkers, has been recognized as an important prognostic and predictive factor, which can also guide the treatment strategy of glioma. This article highlights the research progress of MRI for noninvasively grading and molecular characterization of gliomas, including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), dynamic contrast-enhanced MRI (DCE-MRI), perfusion-weighted imaging (PWI) and magnetic resonance spectroscopy (MRS). The multiparametric imaging data analysis could improve imaging diagnosis, introduce the potential to noninvasively detect underlying molecular features of glioma, finally improve the accuracy of prognosis prediction and guide the individual-based treatment for glioma patients.</p><p> </p><p><strong>DOI: </strong>10.3969/j.issn.1672-6731.2017.01.013</p>http://www.cjcnn.org/index.php/cjcnn/article/view/1539GliomaBiological markersMagnetic resonance imagingReview
collection DOAJ
language English
format Article
sources DOAJ
author Shan-shan ZHANG
Lin YU
spellingShingle Shan-shan ZHANG
Lin YU
Research progress of MRI in glioma grading and molecular genetic biomarkers
Chinese Journal of Contemporary Neurology and Neurosurgery
Glioma
Biological markers
Magnetic resonance imaging
Review
author_facet Shan-shan ZHANG
Lin YU
author_sort Shan-shan ZHANG
title Research progress of MRI in glioma grading and molecular genetic biomarkers
title_short Research progress of MRI in glioma grading and molecular genetic biomarkers
title_full Research progress of MRI in glioma grading and molecular genetic biomarkers
title_fullStr Research progress of MRI in glioma grading and molecular genetic biomarkers
title_full_unstemmed Research progress of MRI in glioma grading and molecular genetic biomarkers
title_sort research progress of mri in glioma grading and molecular genetic biomarkers
publisher Tianjin Huanhu Hospital
series Chinese Journal of Contemporary Neurology and Neurosurgery
issn 1672-6731
publishDate 2017-01-01
description <p>The pathological and imaging diagnosis of glioma has significantly evolved in recent years. Glioma grading, together with a number of molecular genetic biomarkers, has been recognized as an important prognostic and predictive factor, which can also guide the treatment strategy of glioma. This article highlights the research progress of MRI for noninvasively grading and molecular characterization of gliomas, including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), dynamic contrast-enhanced MRI (DCE-MRI), perfusion-weighted imaging (PWI) and magnetic resonance spectroscopy (MRS). The multiparametric imaging data analysis could improve imaging diagnosis, introduce the potential to noninvasively detect underlying molecular features of glioma, finally improve the accuracy of prognosis prediction and guide the individual-based treatment for glioma patients.</p><p> </p><p><strong>DOI: </strong>10.3969/j.issn.1672-6731.2017.01.013</p>
topic Glioma
Biological markers
Magnetic resonance imaging
Review
url http://www.cjcnn.org/index.php/cjcnn/article/view/1539
work_keys_str_mv AT shanshanzhang researchprogressofmriingliomagradingandmoleculargeneticbiomarkers
AT linyu researchprogressofmriingliomagradingandmoleculargeneticbiomarkers
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