ArticleMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine2020
Prediction of Hypoxia in Brain Tumors Using a Multivariate Model Built from MR Imaging and
Article in Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Diagnostic and Prognostic Value of Hypoxia PET in Glioma: A Systematic Review and Meta-Analysis.Cancers · 2026Review
- Magnetic resonance imaging to detect tumor hypoxia in brain malignant disease: A systematic review of validation studies.Clinical and translational radiation oncology · 2025Review
- A novel approach for dose painting radiotherapy of brain metastases guided by mr perfusion images.Frontiers in oncology · 2022Article
- Quantitative and qualitative evaluation of sequential PET/MRI using a newly developed mobile PET system for brain imaging.Japanese journal of radiology · 2021Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
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Abstract
purposeThe aim of this study was to generate a multivariate model using various MRI markers of blood flow and vascular permeability and accumulation of
methodsFifteen patients aged 27-74 years with brain tumors (glioma, n = 13; lymphoma, n = 1; germinoma, n = 1) were included. MRI scans were performed using a 3T scanner, and dynamic contrast-enhanced (DCE) perfusion and arterial spin labeling images were obtained. K
resultsThe area under the curve (AUC) was highest for the multivariate prediction model with FDG (0.892) followed by the multivariate model without FDG and univariate analysis with FDG and K
conclusionA multivariate prediction model created using blood flow, vascular permeability, and glycometabolism parameters can predict the extent of hypoxia in FMISO-positive areas in patients with brain tumors.
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