Evidence map›Paper›PMID 37492687›Full record

ReviewFrontiers in radiology2022

Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions.

Dania G Malik, Tanya J Rath, Javier C Urcuyo Acevedo, Peter D Canoll, Kristin R Swanson, Jerrold L Boxerman, C Chad Quarles, Kathleen M Schmainda, Terry C Burns, Leland S Hu

Abstract readReview
In one paragraph

Review in Frontiers in radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. FET-PETTranslational cancer research · 2026
    Article
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  4. Article
  5. Review
  6. Article
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Dania G MalikDepartment of Radiology, Mayo Clinic, Phoenix, AZ, United States.
Tanya J RathDepartment of Radiology, Mayo Clinic, Phoenix, AZ, United States.
Javier C Urcuyo AcevedoMathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States.
Peter D CanollDepartments of Pathology and Cell Biology, Columbia University, New York, NY, United States.
Kristin R SwansonMathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States.
Jerrold L BoxermanDepartment of Diagnostic Imaging, Brown University, Providence, RI, United States.
C Chad QuarlesDepartment of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States.
Kathleen M SchmaindaDepartment of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States.
Terry C BurnsDepartments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States.
Leland S HuDepartment of Radiology, Mayo Clinic, Phoenix, AZ, United States.

Funding

Langworthy Diversity Supplement: Image-based models of tumor-immune dynamics in glioblastomaU01CA250481 · NCI · MAYO CLINIC ARIZONA · PI CANOLL, PETER, HU, LELAND · 2021 to 2025
$3.8M
Targeting Go and Grow in GlioblastomaR01NS118513 · NINDS · MAYO CLINIC JACKSONVILLE · PI CANOLL, PETER, KENCHAPPA, RAJAPPA · 2020 to 2024
$2.8M
NCI NIH HHS U01 CA250481NINDS NIH HHS R01 NS118513
6 · The paper itself

Abstract

In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.

Indexed as

advancedglioblastomametabolicMRIperfusionpost-treatmentresponse assessment

Identifiers

PMID37492687
PMCPMC10365126

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.