ArticleEuropean radiology2017
Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase
Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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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
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic Accuracy of Amino Acid and FDG-PET in Differentiating Brain Metastasis Recurrence from Radionecrosis after Radiotherapy: A Systematic Review and Meta-Analysis.AJNR. American journal of neuroradiology · 2018Pooled it
- Prediction of TERTp-mutation status in IDH-wildtype high-grade gliomas using pre-treatment dynamic [European journal of nuclear medicine and molecular imaging · 2021Trial
- 11C-methionine-PET for differentiating recurrent brain tumor from radiation necrosis: radiomics approach with random forest classifier.Scientific reports · 2019Trial
- AI differentiates radionecrosis from true progression in brain metastasis upon stereotactic radiosurgery: Analysis of 124 histologically assessed lesions.Neuro-oncology · 2025Article
- Reducing acquisition time in O-(2-Quantitative imaging in medicine and surgery · 2025Article
- Auxiliary Value of [Cancers · 2025Article
- Long-Term Neuroprotective Effects of Hydrogen-Rich Water and Memantine in Chronic Radiation-Induced Brain Injury: Behavioral, Histological, and Molecular Insights.Antioxidants (Basel, Switzerland) · 2025Article
- A Combined Approach Using T2*-Weighted Dynamic Susceptibility Contrast MRI Perfusion Parameters and Radiomics to Differentiate Between Radionecrosis and Glioma Progression: A Proof-of-Concept Study.Life (Basel, Switzerland) · 2025Article
- The current research status of the mechanisms and treatment of radioactive brain injury.American journal of cancer research · 2024Review
- Article
- Review
- Article
- Using domain knowledge for robust and generalizable deep learning-based CT-free PET attenuation and scatter correction.Nature communications · 2022Article
- Can Radiomics Provide Additional Information in [Cancers · 2022Article
- Static FET PET radiomics for the differentiation of treatment-related changes from glioma progression.Journal of neuro-oncology · 2022Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET.European journal of nuclear medicine and molecular imaging · 2022Article
- Review
- A novel semiautomated method for background activity and biological tumour volume definition to improve standardisation ofEJNMMI physics · 2022Article
- Machine Learning-Based Radiomics in Neuro-Oncology.Acta neurochirurgica. Supplement · 2022Review
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWe investigated the potential of textural feature analysis of O-(2-[
methodsForty-seven patients with contrast-enhancing brain lesions (n = 54) on MRI after radiotherapy of brain metastases underwent dynamic
resultsDiagnostic accuracy increased from 81 % for TBR
conclusionsTextural feature analysis in combination with TBRs may have the potential to increase diagnostic accuracy for discrimination between brain metastasis recurrence and radiation injury, without the need for dynamic KEY POINTS: • Textural feature analysis provides quantitative information about tumour heterogeneity • Textural features help improve discrimination between brain metastasis recurrence and radiation injury • Textural features might be helpful to further understand tumour heterogeneity • Analysis does not require a more time consuming dynamic PET acquisition.
Indexed as
Identifiers
27853813What OpenQuestion holds
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.