ArticlePloS one2011
Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 155 papers, 5 of them syntheses that pooled it.
What it found
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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
155 citing papers in PubMed, 5 syntheses or guidelines pooled it, 267 citations in OpenAlex.
- Deep learning, radiomics and radiogenomics applications in the digital breast tomosynthesis: a systematic review.BMC bioinformatics · 2023Pooled it
- Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset.Medical physics · 2020Pooled it
- TCGA-TCIA Impact on Radiogenomics Cancer Research: A Systematic Review.International journal of molecular sciences · 2019Pooled it
- Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review.The British journal of radiology · 2018Pooled it
- Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas.AJNR. American journal of neuroradiology · 2015Pooled it
- Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.Scientific reports · 2016Trial
- Trial
- Spatial omics in high-grade glioma: study design, analytical pitfalls, and standards for reproducible neuro-oncology.Acta neuropathologica communications · 2026Review
- Radiogenomics and radiomics of skull base chordoma: Classification of novel radiomic subgroups and prediction of genetic signatures and clinical outcomes.Neuro-oncology · 2025Article
- Spectral Entropic Radiomics Feature Extraction (SERFE): an adaptive approach for glioblastoma disease classification.Frontiers in artificial intelligence · 2025Article
- A Bayesian deep segmentation framework for glioblastoma tumor segmentation using follow-up MRIs.Frontiers in neuroimaging · 2025Article
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Peritumoral Brain Zone in Astrocytoma: Morphology, Molecular Aspects, and Clinical Manifestations (Review).Sovremennye tekhnologii v meditsine · 2024Review
- Assessment of Glioblastoma Multiforme Tumor Heterogeneity via MRI-derived Shape and Intensity Features.Data science in science · 2024Article
- Machine learning with multimodal data for COVID-19.Heliyon · 2023Review
- Tumor Diagnosis against Other Brain Diseases Using T2 MRI Brain Images and CNN Binary Classifier and DWT.Brain sciences · 2023Article
- Current role of machine learning and radiogenomics in precision neuro-oncology.Exploration of targeted anti-tumor therapy · 2023Review
- Beyond Imaging and Genetic Signature in Glioblastoma: Radiogenomic Holistic Approach in Neuro-Oncology.Biomedicines · 2022Review
- Impact of Tumour Segmentation Accuracy on Efficacy of Quantitative MRI Biomarkers of Radiotherapy Outcome in Brain Metastasis.Cancers · 2022Article
- Pre-operative MRI radiomics model non-invasively predicts key genomic markers and survival in glioblastoma patients.Journal of neuro-oncology · 2022Article
95 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issuedMajadan, Bhanu [corrected to Mahajan, Bhanu]
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundDespite recent discoveries of new molecular targets and pathways, the search for an effective therapy for Glioblastoma Multiforme (GBM) continues. A newly emerged field, radiogenomics, links gene expression profiles with MRI phenotypes. MRI-FLAIR is a noninvasive diagnostic modality and was previously found to correlate with cellular invasion in GBM. Thus, our radiogenomic screen has the potential to reveal novel molecular determinants of invasion. Here, we present the first comprehensive radiogenomic analysis using quantitative MRI volumetrics and large-scale gene- and microRNA expression profiling in GBM.
methodsBased on The Cancer Genome Atlas (TCGA), discovery and validation sets with gene, microRNA, and quantitative MR-imaging data were created. Top concordant genes and microRNAs correlated with high FLAIR volumes from both sets were further characterized by Kaplan Meier survival statistics, microRNA-gene correlation analyses, and GBM molecular subtype-specific distribution.
resultsThe top upregulated gene in both the discovery (4 fold) and validation (11 fold) sets was PERIOSTIN (POSTN). The top downregulated microRNA in both sets was miR-219, which is predicted to bind to POSTN. Kaplan Meier analysis demonstrated that above median expression of POSTN resulted in significantly decreased survival and shorter time to disease progression (P<0.001). High POSTN and low miR-219 expression were significantly associated with the mesenchymal GBM subtype (P<0.0001).
conclusionHere, we propose a novel diagnostic method to screen for molecular cancer subtypes and genomic correlates of cellular invasion. Our findings also have potential therapeutic significance since successful molecular inhibition of invasion will improve therapy and patient survival in GBM.
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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.