ArticleMagnetic resonance imaging2022
Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models.
Article in Magnetic resonance imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Improving the diagnostic efficacy of MR cytometry in prostate cancer imaging.Abdominal radiology (New York) · 2026Article
- The predictive value of MR cytometry in histological differentiation of rectal cancer: an exploratory study.European radiology · 2026Observational
- Liquid biopsy of plasma and urinary CfDNA differentiates glioma recurrence from radiation brain necrosis in preclinical models.Scientific reports · 2026Article
- Article
- CEST2022: Amide proton transfer-weighted MRI improves the diagnostic performance of multiparametric non-contrast-enhanced MRI techniques in patients with post-treatment high-grade gliomas.Magnetic resonance imaging · 2023Article
- Advances in the application of neuroinflammatory molecular imaging in brain malignancies.Frontiers in immunology · 2023Review
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundIt remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting.
methodsMulti-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T
resultsFor single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions.
conclusionA general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.
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