ArticleCell proliferation2009
Virtual glioblastoma: growth, migration and treatment in a three-dimensional mathematical model.
Article in Cell proliferation, 2009. 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 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
27 citing papers in PubMed, 80 citations in OpenAlex.
- Feasibility of convection-enhanced delivery of unlabeledMedical physics · 2026Article
- Biopsy location and tumor-associated macrophages in predicting malignant glioma recurrence using an in-silico model.NPJ systems biology and applications · 2025Article
- The self-organized structure of glioma oncostreams and the disruptive role of passive cells.Scientific reports · 2024Article
- Spatial computational modelling illuminates the role of the tumour microenvironment for treating glioblastoma with immunotherapies.NPJ systems biology and applications · 2024Article
- Understanding glioblastoma invasion using physically-guided neural networks with internal variables.PLoS computational biology · 2022Article
- Multiscale modeling of glioma pseudopalisades: contributions from the tumor microenvironment.Journal of mathematical biology · 2021Article
- Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study.Neuro-oncology · 2020Article
- Radiation protraction schedules for low-grade gliomas: a comparison between different mathematical models.Journal of the Royal Society, Interface · 2019Article
- Patient-specific parameter estimates of glioblastoma multiforme growth dynamics from a model with explicit birth and death rates.Mathematical biosciences and engineering : MBE · 2019Article
- A Brownian dynamics tumor progression simulator with application to glioblastoma.Convergent science physical oncology · 2018Article
- Advances in Glioblastoma Multiforme Treatment: New Models for Nanoparticle Therapy.Frontiers in physiology · 2018Review
- Mathematical Analysis of Glioma Growth in a Murine Model.Scientific reports · 2017Article
- Article
- A Numerical Handling of the Boundary Conditions Imposed by the Skull on an Inhomogeneous Diffusion-Reaction Model of Glioblastoma Invasion Into the Brain: Clinical Validation Aspects.Cancer informatics · 2017Article
- Non-standard radiotherapy fractionations delay the time to malignant transformation of low-grade gliomas.PloS one · 2017Article
- Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights.Scientific reports · 2016Article
- A mathematical approach to virus therapy of glioblastomas.Biology direct · 2016Article
- Fast and high temperature hyperthermia coupled with radiotherapy as a possible new treatment for glioblastoma.Journal of therapeutic ultrasound · 2016Article
- Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme.PloS one · 2016Article
- Evaluation of current clinical target volume definitions for glioblastoma using cell-based dosimetry stochastic methods.The British journal of radiology · 2015Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesGlioblastomas are aggressive primary brain cancers that are characterized by extensive infiltration into the brain and are highly resistant to treatment. Through mathematical modelling, we model the process of invasion and predict the relative importance of mechanisms contributing to malignant invasion. Clinically, we predict patterns of tumour recurrence following various modes of therapeutic intervention. MATERIALS AND
methodsOur mathematical model uses a realistic three-dimensional brain geometry and considers migrating and proliferating cells as separate classes. Several mechanisms for infiltrative migration are considered. Methods are developed for simulating surgical resection, radiotherapy and chemotherapy.
resultsThe model provides clinically realistic predictions of tumour growth and recurrence following therapeutic intervention. Specific results include (i) invasiveness is governed largely by the ability of glioblastoma cells to degrade and migrate through the extracellular matrix and the ability of single migrating cells to form colonies; (ii) tumours originating deeper in the brain generally grow more quickly than those of superficial origin; (iii) upon surgery, the margins and geometry of resection significantly determine the extent and pattern of postoperative recurrence; (iv) radiotherapy works synergistically with greater resection margins to reduce recurrence; (v) simulations in both two- and three-dimensional geometries give qualitatively similar results; and (vi) in an actual clinical case comprising several surgical interventions, the model provides good qualitative agreement between the simulated and observed course of the disease.
conclusionsThe model provides a useful initial framework by which biological mechanisms of invasion and efficacy of potential treatment regimens may be assessed.
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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.