ArticleMetabolites2022
Differentiation of Glioblastoma and Brain Metastases by MRI-Based Oxygen Metabolomic Radiomics and Deep Learning.
Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence algorithms for differentiating pseudoprogression from true progression in high-grade gliomas: A systematic review and meta-analysis.Neurosurgical review · 2025Pooled it
- Physio-metabolic MRI of oxygen metabolism and neovascularization for differentiating glioblastomas from solitary NSCLC brain metastases.La Radiologia medica · 2026Observational
- Brain metastases converge on shared geometric architecture and transcriptomic landscape yet remain distinct from gliomas.iScience · 2026Article
- Decoding the Glioblastoma Microenvironment: AI-Driven Analysis of Cellular MRI Signatures for Targeted Therapy.Cellular and molecular neurobiology · 2026Review
- Diagnostic imaging and emerging image-guided neurointervention in brain tumors: a narrative review.Frontiers in radiology · 2026Review
- Artificial Intelligence in the Diagnosis and Treatment of Brain Gliomas.Biomedicines · 2025Review
- AI-Driven Innovations in Neuroradiology and Neurosurgery: Scoping Review of Current Evidence and Future Directions.Cancers · 2025Review
- Diagnostic, Therapeutic, and Prognostic Applications of Artificial Intelligence (AI) in the Clinical Management of Brain Metastases (BMs).Brain sciences · 2025Review
- A Review of Artificial Intelligence-Based Systems for Non-Invasive Glioblastoma Diagnosis.Life (Basel, Switzerland) · 2025Review
- Assessment of blood-brain barrier leakage and brain oxygenation in Connexin-32 knockout mice with systemic neuroinflammation using pulse electron paramagnetic resonance imaging techniques.Magnetic resonance in medicine · 2024Article
- Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors.Cancers · 2024Review
- An Explainable MRI-Radiomic Quantum Neural Network to Differentiate Between Large Brain Metastases and High-Grade Glioma Using Quantum Annealing for Feature Selection.Journal of digital imaging · 2023Article
- Can Perfusion-Based Brain Tissue Oxygenation MRI Support the Understanding of Cerebral Abscesses In Vivo?Diagnostics (Basel, Switzerland) · 2023Article
- One Step Forward-The Current Role of Artificial Intelligence in Glioblastoma Imaging.Life (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Glioblastoma (GB) and brain metastasis (BM) are the most frequent types of brain tumors in adults. Their therapeutic management is quite different and a quick and reliable initial characterization has a significant impact on clinical outcomes. However, the differentiation of GB and BM remains a major challenge in today's clinical neurooncology due to their very similar appearance in conventional magnetic resonance imaging (MRI). Novel metabolic neuroimaging has proven useful for improving diagnostic performance but requires artificial intelligence for implementation in clinical routines. Here; we investigated whether the combination of radiomic features from MR-based oxygen metabolism ("oxygen metabolic radiomics") and deep convolutional neural networks (CNNs) can support reliably pre-therapeutic differentiation of GB and BM in a clinical setting. A self-developed one-dimensional CNN combined with radiomic features from the cerebral metabolic rate of oxygen (CMRO
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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.