ArticleHeliyon2024
Predicting glioblastoma recurrence using multiparametric MR imaging of non-enhancing peritumoral regions at baseline.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Beyond morphology: imaging the glioblastoma microenvironment in the era of quantitative neuro-oncology.Frontiers in medicine · 2026Review
- Three-Dimensional quantitative analysis of the Peri-Enhancing zone reveals ADC and CBV signatures of glioblastoma recurrence.NeuroImage. Clinical · 2026Article
- Implication of tumor morphology and MRI characteristics on the accuracy of automated versus human segmentation of GBM areas.Scientific reports · 2025Article
- Investigating the potential of diffusion tensor atlases to generate anisotropic clinical tumor volumes in glioblastoma patients.Physics and imaging in radiation oncology · 2025Article
- Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: To assess the feasibility of multiparametric magnetic resonance imaging in predicting tumor recurrence in nonenhancing peritumoral regions in patients with glioblastoma at baseline. Methods: Fifty-eight patients with recurrent glioblastoma underwent multiparametric magnetic resonance imaging, including T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging. Nonenhancing peritumoral regions with glioblastoma recurrence were identified by coregistering preoperative and post-recurrent magnetic resonance images. Regions of interest were placed in nonenhancing peritumoral regions with and without tumor recurrence to calculate the apparent diffusion coefficient value, and relative ratios of T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and cerebral blood volume values. Results: Significant lower relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative apparent diffusion coefficient but higher relative cerebral blood volume values were found in the nonenhancing peritumoral regions with tumor recurrence than without recurrence (all Conclusion: The combined use of T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging can effectively estimate the risk of future tumor recurrence at baseline.
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Registered trials
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