ReviewJournal of magnetic resonance imaging : JMRI2020
Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma.
Review in Journal of magnetic resonance imaging : JMRI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review and Meta-analysis of Survival Prediction in Glioblastoma Patients using Advanced MRI Techniques.Current medical imaging · 2026Pooled it
- FET-PETTranslational cancer research · 2026Article
- Article
- The brain imaging feature-related gene NRP2 drives the malignant progression of glioblastoma through the FAK pathway: a Mendelian randomization study.Translational oncology · 2026Article
- Multimodal phototherapy for Glioblastoma: from mechanistic action to synergistic delivery and therapeutic strategies.Journal of nanobiotechnology · 2026Review
- Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning-Based Prediction Models to Distinguish Glioblastomas from Single Brain Metastases.Diagnostics (Basel, Switzerland) · 2024Article
- Clinicopathological Parameters and Immunohistochemical Profiles in Correlation with MRI Characteristics in Glioblastomas.International journal of molecular sciences · 2024Article
- Inferring the genetic relationships between unsupervised deep learning-derived imaging phenotypes and glioblastoma through multi-omics approaches.Briefings in bioinformatics · 2024Article
- Radiogenomics as an Integrated Approach to Glioblastoma Precision Medicine.Current oncology reports · 2024Review
- The peritumoral brain zone in glioblastoma: a review of the pretreatment approach.Polish journal of radiology · 2024Review
- MRI radiomics model for predicting TERT promoter mutation status in glioblastoma.Brain and behavior · 2023Article
- Amine-weighted chemical exchange saturation transfer magnetic resonance imaging in brain tumors.NMR in biomedicine · 2023Article
- Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma.NMR in biomedicine · 2022Review
- Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism.Frontiers in neurology · 2022Review
- Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine.Cancers · 2021Article
- Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics-A Systematic Review.Cancers · 2020Review
- A Review of Newly Diagnosed Glioblastoma.Frontiers in oncology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Glioblastoma is the most common and most malignant primary brain tumor. Despite aggressive multimodal treatment, its prognosis remains poor. Even with continuous developments in MRI, which has provided us with newer insights into the diagnosis and understanding of tumor biology, response assessment in the posttherapy setting remains challenging. We believe that the integration of additional information from advanced neuroimaging techniques can further improve the diagnostic accuracy of conventional MRI. In this article, we review the utility of advanced neuroimaging techniques such as diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, proton magnetic resonance spectroscopy, and chemical exchange saturation transfer in characterizing and evaluating treatment response in patients with glioblastoma. We will also discuss the existing challenges and limitations of using these techniques in clinical settings and possible solutions to avoiding pitfalls in study design, data acquisition, and analysis for future studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:978-997.
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Identifiers
What OpenQuestion holds
Registered trials
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.