ReviewBrain pathology (Zurich, Switzerland)2022
Use of advanced neuroimaging and artificial intelligence in meningiomas.
Review in Brain pathology (Zurich, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Machine learning-based models and radiomics: can they be reliable predictors for meningioma recurrence? A systematic review and meta-analysis.Neurosurgical review · 2025Pooled it
- Biomimetic scaffolds based on stem cells for neural tissue engineering: a review.Stem cell research & therapy · 2026Review
- Differentiation of Intracranial Dural Metastases and Meningiomas Using DSC Perfusion MRI and Machine Learning.Diagnostics (Basel, Switzerland) · 2026Article
- A scoping review of artificial intelligence applications in meningioma from image analysis to prognostic prediction.Discover oncology · 2026Review
- Artificial intelligence in neuroimaging: Opportunities and ethical challenges.Brain & spine · 2024Article
- Artificial Intelligence, Radiomics, and Computational Modeling in Skull Base Surgery.Advances in experimental medicine and biology · 2024Review
- Radiomics-Based Prediction of TERT Promotor Mutations in Intracranial High-Grade Meningiomas.Cancers · 2023Article
- Are there reliable multiparametric MRI criteria for differential diagnosis between intracranial meningiomas and solitary intracranial dural metastases?Oncology letters · 2023Article
- A magnetic resonance imaging based radiomics model to predict mitosis cycles in intracranial meningioma.Scientific reports · 2023Article
- Radiomic and clinical nomogram for cognitive impairment prediction in Wilson's disease.Frontiers in neurology · 2023Article
- Use of advanced neuroimaging and artificial intelligence in meningiomas.Brain pathology (Zurich, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anatomical cross-sectional imaging methods such as contrast-enhanced MRI and CT are the standard for the delineation, treatment planning, and follow-up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non-invasively provide detailed insights into the molecular and metabolic features of meningiomas. These techniques are usually based on MRI, e.g., perfusion-weighted imaging, diffusion-weighted imaging, MR spectroscopy, and positron emission tomography. Furthermore, artificial intelligence methods such as radiomics offer the potential to extract quantitative imaging features from routinely acquired anatomical MRI and CT scans and advanced imaging techniques. This allows the linking of imaging phenotypes to meningioma characteristics, e.g., the molecular-genetic profile. Here, we review several diagnostic applications and future directions of these advanced neuroimaging techniques, including radiomics in preclinical models and patients with meningioma.
Indexed as
Identifiers
What 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.