ArticleCancers2022
Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 18 citations in OpenAlex.
- Systematic review and meta-analysis of AI in lung cancer metastasis imaging for diagnosis and prognosis.NPJ digital medicine · 2026Article
- Low interstitial fluid in patients with spontaneous intracranial hypotension.Fluids and barriers of the CNS · 2026Article
- The Freiburg framework for multimodalFrontiers in synaptic neuroscience · 2026Article
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- Advanced diffusion MRI provides evidence for altered axonal microstructure and gradual peritumoral infiltration in GBM in comparison to brain metastases.Clinical neuroradiology · 2024Article
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- Diagnosing Progression in Glioblastoma-Tackling a Neuro-Oncology Problem Using Artificial-Intelligence-Derived Volumetric Change over Time on Magnetic Resonance Imaging to Examine Progression-Free Survival in Glioblastoma.Diagnostics (Basel, Switzerland) · 2024Article
- Mesoscopic Assessment of Microstructure in Glioblastomas and Metastases by Merging Advanced Diffusion Imaging with Immunohistopathology.AJNR. American journal of neuroradiology · 2023Article
- Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.Journal of digital imaging · 2023Article
- Application of diffusion microstructure imaging in musculoskeletal radiology - translation from head to shoulders.European radiology · 2023Article
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- FLAIRectomy: Resecting beyond the Contrast Margin for Glioblastoma.Brain sciences · 2022Article
- Microstructural differentiation of cerebral metastases, glioblastoma, meningioma, and primary CNS lymphoma using advanced diffusion imaging techniques.Neuro-oncology advancesArticle
- Advanced diffusion imaging reveals microstructural characteristics of primary CNS lymphoma, allowing differentiation from glioblastoma.Neuro-oncology advancesArticle
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Glioblastomas (GBM) and brain metastases are often difficult to differentiate in conventional MRI. Diffusion microstructure imaging (DMI) is a novel MR technique that allows the approximation of the distribution of the intra-axonal compartment, the extra-axonal cellular, and the compartment of interstitial/free water within the white matter. We hypothesize that alterations in the T2 hyperintense areas surrounding contrast-enhancing tumor components may be used to differentiate GBM from metastases. Methods: DMI was performed in 19 patients with glioblastomas and 17 with metastatic lesions. DMI metrics were obtained from the T2 hyperintense areas surrounding contrast-enhancing tumor components. Resected brain tissue was assessed in six patients in each group for features of an edema pattern and tumor infiltration in the perilesional interstitium. Results: Within the perimetastatic T2 hyperintensities, we observed a significant increase in free water (p < 0.001) and a decrease in both the intra-axonal (p = 0.006) and extra-axonal compartments (p = 0.024) compared to GBM. Perilesional free water fraction was discriminative regarding the presence of GBM vs. metastasis with a ROC AUC of 0.824. Histologically, features of perilesional edema were present in all assessed metastases and absent or marginal in GBM. Conclusion: Perilesional T2 hyperintensities in brain metastases and GBM differ significantly in DMI-values. The increased free water fraction in brain metastases suits the histopathologically based hypothesis of perimetastatic vasogenic edema, whereas in glioblastomas there is additional tumor infiltration.
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