ArticleAJNR. American journal of neuroradiology2013
Potential role of preoperative conventional MRI including diffusion measurements in assessing epidermal growth factor receptor gene amplification status in patients with glioblastoma.
Article in AJNR. American journal of neuroradiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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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.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Congress of neurological surgeons systematic review and evidence-based guidelines update on the role of emerging developments in the management of newly diagnosed glioblastoma.Journal of neuro-oncology · 2020Pooled it
- The role of imaging for the management of newly diagnosed glioblastoma in adults: a systematic review and evidence-based clinical practice guideline update.Journal of neuro-oncology · 2020Pooled it
- Quantitative magnetic resonance imaging and radiogenomic biomarkers for glioma characterisation: a systematic review.The British journal of radiology · 2018Pooled it
- Exploring the Role of Advanced MRI in Understanding Glioblastoma Biology: A Scoping Review.Cancers · 2026Review
- Advanced MRI, Radiomics and Radiogenomics in Unravelling Incidental Glioma Grading and Genetic Status: Where Are We?Medicina (Kaunas, Lithuania) · 2025Review
- Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype.Journal of neuro-oncology · 2023Article
- Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives.Biomedicines · 2023Review
- Tumor Progression and Treatment-Related Changes: Radiological Diagnosis Challenges for the Evaluation of Post Treated Glioma.Cancers · 2022Review
- Diagnostic and Prognostic Value of pH- and Oxygen-Sensitive Magnetic Resonance Imaging in Glioma: A Retrospective Study.Cancers · 2022Article
- Determining the optimum tumor control probability model in radiotherapy of glioblastoma multiforme using magnetic resonance imaging data pre- and post- radiation therapy.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2022Article
- Identification of magnetic resonance imaging features for the prediction of molecular profiles of newly diagnosed glioblastoma.Journal of neuro-oncology · 2021Article
- Phosphorous Magnetic Resonance Spectroscopy and Molecular Markers in IDH1 Wild Type Glioblastoma.Cancers · 2021Article
- Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors.Cancers · 2021Review
- Diffusion and perfusion MRI may predict EGFR amplification and the TERT promoter mutation status of IDH-wildtype lower-grade gliomas.European radiology · 2020Article
- A Comparison of the Efficiency of Using a Deep CNN Approach with Other Common Regression Methods for the Prediction of EGFR Expression in Glioblastoma Patients.Journal of digital imaging · 2020Article
- Clinical Imaging for Diagnostic Challenges in the Management of Gliomas: A Review.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2020Review
- Multiparametric and multiregional diffusion features help predict molecule information, grade and survival in lower-grade gliomas: a feasibility study.The British journal of radiology · 2019Article
- Article
- Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis.Oncotarget · 2018Review
- Advances in Neuro-Oncology Imaging Techniques.Ochsner journal · 2018Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
background and purposeEpidermal growth factor receptor amplification is a common molecular event in glioblastomas. The purpose of this study was to examine the potential usefulness of morphologic and diffusion MR imaging signs in the prediction of epidermal growth factor receptor gene amplification status in patients with glioblastoma. MATERIALS AND
methodsWe analyzed pretreatment MR imaging scans from 147 consecutive patients with newly diagnosed glioblastoma and correlated MR imaging features with tumor epidermal growth factor receptor amplification status. The following morphologic tumor MR imaging features were qualitatively assessed: 1) border sharpness, 2) cystic/necrotic change, 3) hemorrhage, 4) T2-isointense signal, 5) restricted water diffusion, 6) nodular enhancement, 7) subependymal enhancement, and 8) multifocal discontinuous enhancement. A total of 142 patients had DWI available for quantitative analysis. ADC maps were calculated, and the ADCmean, ADCmin, ADCmax, ADCROI, and ADCratio were measured.
resultsEpidermal growth factor receptor amplification was present in 60 patients (40.8%) and absent in 87 patients (59.2%). Restricted water diffusion correlated with epidermal growth factor receptor amplification (P = .04), whereas the other 7 morphologic MR imaging signs did not (P > .12). Quantitative DWI analysis found that all ADC measurements correlated with epidermal growth factor receptor amplification, with the highest correlations found with ADCROI (P = .0003) and ADCmean (P = .0007).
conclusionsOur results suggest a role for diffusion MR imaging in the determination of epidermal growth factor receptor amplification status in glioblastoma. Additional work is necessary to confirm these results and isolate new imaging biomarkers capable of noninvasively characterizing the molecular status of these tumors.
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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.