Cited by 213Glioma Diagnosis and TreatmentAdvanced Neuroimaging Techniques and ApplicationsMRI in cancer diagnosis

Advanced magnetic resonance imaging in glioblastoma: a review

Open access
Shukla, Gaurav, Alexander, Gregory S., Bakas, Spyridon, Nikam, Rahul, Talekar, Kiran, Palmer, Joshua D., Shi, Wenyin·2017·Chinese Clinical Oncology

Abstract

Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

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  • The data considered in this study described patient populations with adult-type diffuse glioma, specifically displaying the radiological features of glioblastoma, scanned with multiparametric MRI.

    “The data considered in this study described patient populations with adult-type diffuse glioma30, and specifically displaying the radiological features of glioblastoma, scanned with mpMRI to characterize the anatomical tissue structure25.”

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Cited by 213

Authors
Shukla, G., Alexander, G. S., Bakas, S., Nikam, R., Talekar, K., Palmer, J. D., & Shi, W.
Affiliations
  • Thomas Jefferson University (US)
  • University of Pennsylvania (US)
  • The Ohio State University Wexner Medical Center (US)
Corresponding author
Shukla, Gaurav
Venue
Chinese Clinical Oncology
Published
2017-08
Volume
6
Issue
4
Pages
40-40
ISSN
  • 2304-3865 (ISSN-L)
  • 2304-3873
OpenAlex
W2743924567
Cited by
213
References
0
Citations by year
2026: 18 · 2025: 32 · 2024: 35 · 2023: 36 · 2022: 37 · 2021: 25 · 2020: 20 · 2019: 9 · 2018: 1
FWCI
4.71
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Chinese Clinical Oncology (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Genetics › Glioma Diagnosis and Treatment
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › MRI in cancer diagnosis
Keywords
glioblastoma, advanced MRI techniques, dynamic susceptibility contrast MRI, dynamic contrast enhancement, diffusion tensor imaging, MR spectroscopy, functional MRI, tractography, eloquent cortex, tumor characterization, central nervous system tumors
MeSH terms
Brain Neoplasms, Glioblastoma, Humans, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy, Prognosis, Sensitivity and Specificity, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging

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