ArticlePloS one2015
Towards the Personalized Treatment of Glioblastoma: Integrating Patient-Specific Clinical Data in a Continuous Mechanical Model.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 23 papers.
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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.
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Who cites it
23 citing papers in PubMed.
- Go-or-grow models in biology: a monster on a leash.Journal of mathematical biology · 2025Review
- Non-Invasive Measurement of Elasticity in Glioblastoma Multiforme Validates Decreased TMZ Sensitivity in Astrocyte Co-Culture.IEEE open journal of engineering in medicine and biology · 2025Article
- Association between the Anatomical Location of Glioblastoma and Its Evaluation with Clinical Considerations: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2024Review
- Elastocapillary effects determine early matrix deformation by glioblastoma cell spheroids.APL bioengineering · 2024Article
- Modelling microtube driven invasion of glioma.Journal of mathematical biology · 2023Article
- An Integrated Monte Carlo Model for Heterogeneous Glioblastoma Treated with Boron Neutron Capture Therapy.Cancers · 2023Article
- Coupling solid and fluid stresses with brain tumour growth and white matter tract deformations in a neuroimaging-informed model.Biomechanics and modeling in mechanobiology · 2022Article
- Article
- Treatment-induced shrinking of tumour aggregates: a nonlinear volume-filling chemotactic approach.Journal of mathematical biology · 2021Article
- Personalised, image-guided, noninvasive brain stimulation in gliomas: Rationale, challenges and opportunities.EBioMedicine · 2021Review
- In Silico Mathematical Modelling for Glioblastoma: A Critical Review and a Patient-Specific Case.Journal of clinical medicine · 2021Review
- Transferrin-Decorated Niosomes with Integrated InP/ZnS Quantum Dots and Magnetic Iron Oxide Nanoparticles: Dual Targeting and Imaging of Glioma.International journal of molecular sciences · 2021Article
- Biomechanical modelling of spinal tumour anisotropic growth.Proceedings. Mathematical, physical, and engineering sciences · 2020Article
- Connective tissue growth factor as an unfavorable prognostic marker promotes the proliferation, migration, and invasion of gliomas.Chinese medical journal · 2020Article
- Investigating the Physical Effects in Bacterial Therapies for Avascular Tumors.Frontiers in microbiology · 2020Article
- Article
- Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI.NeuroImage. Clinical · 2018Article
- Advances in Glioblastoma Multiforme Treatment: New Models for Nanoparticle Therapy.Frontiers in physiology · 2018Review
- Clinical implications of in silico mathematical modeling for glioblastoma: a critical review.Journal of neuro-oncology · 2018Review
- Glioma and microenvironment dual targeted nanocarrier for improved antiglioblastoma efficacy.Drug delivery · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma multiforme (GBM) is the most aggressive and malignant among brain tumors. In addition to uncontrolled proliferation and genetic instability, GBM is characterized by a diffuse infiltration, developing long protrusions that penetrate deeply along the fibers of the white matter. These features, combined with the underestimation of the invading GBM area by available imaging techniques, make a definitive treatment of GBM particularly difficult. A multidisciplinary approach combining mathematical, clinical and radiological data has the potential to foster our understanding of GBM evolution in every single patient throughout his/her oncological history, in order to target therapeutic weapons in a patient-specific manner. In this work, we propose a continuous mechanical model and we perform numerical simulations of GBM invasion combining the main mechano-biological characteristics of GBM with the micro-structural information extracted from radiological images, i.e. by elaborating patient-specific Diffusion Tensor Imaging (DTI) data. The numerical simulations highlight the influence of the different biological parameters on tumor progression and they demonstrate the fundamental importance of including anisotropic and heterogeneous patient-specific DTI data in order to obtain a more accurate prediction of GBM evolution. The results of the proposed mathematical model have the potential to provide a relevant benefit for clinicians involved in the treatment of this particularly aggressive disease and, more importantly, they might drive progress towards improving tumor control and patient's prognosis.
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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.