ReviewNeuro-oncology advances2020
Feature-based PET/MRI radiomics in patients with brain tumors.
Review in Neuro-oncology advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic Accuracy of PET for Differentiating True Glioma Progression From Post Treatment-Related Changes: A Systematic Review and Meta-Analysis.Frontiers in neurology · 2021Pooled 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
- PET|MR Open Source Radiomics Models for Treatment Outcome Prediction in Recurrent GBM.Cancers · 2026Article
- Advanced Neuroimaging and Emerging Systemic Therapies in Glioblastoma: Current Evidence and Future Directions.Biomedicines · 2025Review
- A Narrative Review of Theranostics in Neuro-Oncology: Advancing Brain Tumor Diagnosis and Treatment Through Nuclear Medicine and Artificial Intelligence.International journal of molecular sciences · 2025Review
- Prognostic and predictive determinants in high-grade gliomas: integrating tumor-intrinsic biology with patient and system-level factors.Frontiers in neurology · 2025Review
- Hybrid Positron Emission Tomography and Magnetic Resonance Imaging Guided Microsurgical Management of Glial Tumors: Case Series and Review of the Literature.Diagnostics (Basel, Switzerland) · 2024Article
- Comparison of PET/CT and PET/MRI in central nervous system tumors, a narrative review.International journal of physiology, pathophysiology and pharmacology · 2024Review
- Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives.Biomarker research · 2023Review
- Amino Acid Tracer PET MRI in Glioma Management: What a Neuroradiologist Needs to Know.AJNR. American journal of neuroradiology · 2023Review
- Feasibility of radiomic feature harmonization for pooling of [Zeitschrift fur medizinische Physik · 2023Article
- Can Radiomics Provide Additional Information in [Cancers · 2022Article
- Article
- Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.International journal of molecular sciences · 2021Review
- Surface values, volumetric measurements and radiomics of structural MRI for the diagnosis and subtyping of attention-deficit/hyperactivity disorder.The European journal of neuroscience · 2021Article
- TERT-Promoter Mutational Status in Glioblastoma - Is There an Association With Amino Acid Uptake on DynamicFrontiers in oncology · 2021Article
- Artificial Intelligence, Radiomics, and Deep Learning in Neuro-Oncology.Neuro-oncology advances · 2020Article
- Evolution and implementation of radiographic response criteria in neuro-oncology.Neuro-oncology advancesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET, thereby providing additional, potentially relevant diagnostic information for clinical decision-making. Because the computation of these features is performed highly automated on medical images acquired during routine follow-up, radiomics offers this information at low cost. Further, the radiomics features can be used alone or combined with other clinical or histomolecular parameters to generate predictive or prognostic mathematical models. These models can then be applied for various important diagnostic indications in neuro-oncology, for example, to noninvasively predict relevant biomarkers in glioma patients, to differentiate between treatment-related changes and local brain tumor relapse, or to predict treatment response. In recent years, amino acid PET has become an important diagnostic tool in patients with brain tumors. Therefore, the number of studies in patients with brain tumors investigating the potential of PET radiomics or combined PET/MRI radiomics is steadily increasing. This review summarizes current research regarding feature-based PET as well as combined PET/MRI radiomics in neuro-oncology.
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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.