ReviewFrontiers in neurology2022
Neuroplasticity of Glioma Patients: Brain Structure and Topological Network.
Review in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 31 citations in OpenAlex.
- Functional gradient analysis reveals potential therapeutic mechanisms of nrTMS for postoperative motor deficits in glioma patients: A randomized controlled trial.NeuroImage. Clinical · 2026Trial
- Humoral immunity in cancer.Signal transduction and targeted therapy · 2026Review
- The prefrontal cortex across scales: laminar architecture, white-matter constraints, and distributed control in cognition.Brain structure & function · 2026Review
- Unveiling the whole-brain impact of diffuse midline glioma: cortical morphological remodeling and network alterations driven by H3 K27 mutation.Neuroradiology · 2026Article
- Beyond binary classification: a pilot study of imaging-derived glioma severity modeling using T1-weighted and diffusion MRI radiomics.Magma (New York, N.Y.) · 2026Article
- The onco-functional reorganization of language network underlying metaplasticity induced by gliomas.Frontiers in oncology · 2026Article
- Neurocognitive outcomes following glioma diagnosis and treatment: A systematic review.Brain & spine · 2026Review
- Structural-functional fingerprinting for abnormalities investigation in glioma patients.Scientific reports · 2025Article
- Noninvasive assessment of glymphatic dysfunction and IDH mutation in glioma with DTI-ALPS and DTI metrics.Quantitative imaging in medicine and surgery · 2025Article
- High-Density Electroencephalography Detects Spatiotemporal Abnormalities in Brain Networks in Patients With Glioma-Related Epilepsy.CNS neuroscience & therapeutics · 2025Article
- Review
- Accurate low and high grade glioma classification using free water eliminated diffusion tensor metrics and ensemble machine learning.Scientific reports · 2024Article
- Predicting Cognitive Functioning for Patients with a High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space.Neuroinformatics · 2024Article
- Altered whole-brain functional network in patients with frontal low-grade gliomas: a resting-state functional MRI study.Neuroradiology · 2024Article
- Optimal approaches to analyzing functional MRI data in glioma patients.Journal of neuroscience methods · 2024Article
- CSF3R as a potential prognostic biomarker and immunotherapy target in glioma.Central-European journal of immunology · 2024Article
- Evaluating circulating tumour cell enrichment techniques to establish an appropriate method for clinical application in glioblastomas.Frontiers in neurology · 2024Article
- Diagnostic and Therapeutic Issues in Glioma Using Imaging Data: The Challenge of Numerical Twinning.Journal of clinical medicine · 2023Review
- A Novel Intraoperative Mapping Device Detects the Thermodynamic Response Function.Brain sciences · 2023Article
- Assessment of brain cancer atlas maps with multimodal imaging features.Journal of translational medicine · 2023Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients.
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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.