ArticleAJNR. American journal of neuroradiology2021
MRI Features May Predict Molecular Features of Glioblastoma in
Article in AJNR. American journal of neuroradiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.
- Radiomics and Machine Learning in Diagnostics of Glial Brain Tumors: a Systematic Review and Meta-Analysis.Sovremennye tekhnologii v meditsine · 2025Pooled it
- Prediction of TERTp-mutation status in IDH-wildtype high-grade gliomas using pre-treatment dynamic [European journal of nuclear medicine and molecular imaging · 2021Trial
- Multiparametric static hybrid ¹⁸F-FET PET/MR for preoperative prediction of TERT promoter mutation in glioblastoma.Neuroradiology · 2026Article
- A misdiagnosed case of tumefactive demyelinating lesion mimicking glioma: Imaging pitfalls and diagnostic lessons.Radiology case reports · 2026Article
- AOSNP-ADAPTR resource level-based recommendations on practical diagnostic strategies for WHO CNS5 adult-type diffuse gliomas.Brain pathology (Zurich, Switzerland) · 2026Review
- Radiomics-Driven Hybrid Deep Learning for MRI-Based Prediction of Glioma Grade and 1p/19q Codeletion.Tomography (Ann Arbor, Mich.) · 2026Article
- Opportunities and challenges in application of VASARI features in neuro-oncology.Neuro-oncology practice · 2025Review
- A Radiologist's Guide to IDH-Wildtype Glioblastoma for Efficient Communication With Clinicians: Part I-Essential Information on Preoperative and Immediate Postoperative Imaging.Korean journal of radiology · 2025Review
- Molecular GBM versus Histopathological GBM: Radiology-Pathology-Genetic Correlation and the New WHO 2021 Definition of Glioblastoma.AJNR. American journal of neuroradiology · 2024Review
- Diffusion- and Perfusion-Weighted MRI Radiomics for Survival Prediction in Patients with Lower-Grade Gliomas.Yonsei medical journal · 2024Article
- A radiomics-based nomogram may be useful for predicting telomerase reverse transcriptase promoter mutation status in adult glioblastoma.Brain and behavior · 2024Article
- Article
- Multiparametric MRI-based fusion radiomics for predicting telomerase reverse transcriptase (TERT) promoter mutations and progression-free survival in glioblastoma: a multicentre study.Neuroradiology · 2024Article
- MRI radiomics model for predicting TERT promoter mutation status in glioblastoma.Brain and behavior · 2023Article
- Article
- Vasari Scoring System in Discerning between Different Degrees of Glioma and IDH Status Prediction: A Possible Machine Learning Application?Journal of imaging · 2023Article
- Forecasting Molecular Features in IDH-Wildtype Gliomas: The State of the Art of Radiomics Applied to Neurosurgery.Cancers · 2023Review
- Qualitative and Quantitative Magnetic Resonance Imaging Phenotypes May Predict CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytomas: A Multicenter Study.Korean journal of radiology · 2023Article
- Multi-parameter MRI based radiomics nomogram for predicting telomerase reverse transcriptase promoter mutation and prognosis in glioblastoma.Frontiers in neurology · 2023Article
- A review of radiomics and genomics applications in cancers: the way towards precision medicine.Radiation oncology (London, England) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeMATERIALS AND
methodsIn this multi-institutional retrospective study, pathologically confirmed
resultsIn the test set, a model using both Visually AcceSAble Rembrandt Images and radiomic features showed superior predictive performance (area under the curve = 0.854) than that with only clinical features or Visually AcceSAble Rembrandt Images (areas under the curve = 0.514 and 0.648, respectively;
conclusionsMR imaging features integrated with machine learning classifiers may predict a subset of
Indexed as
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.