ReviewComputational and mathematical methods in medicine2012
In silico modelling of tumour margin diffusion and infiltration: review of current status.
Review in Computational and mathematical methods in medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Treating the invisible target: treatment planning targeting the microscopic tumor spread in gliomas.Frontiers in oncology · 2026Article
- Evaluation of current clinical target volume definitions for glioblastoma using cell-based dosimetry stochastic methods.The British journal of radiology · 2015Article
- A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET.Journal of the Royal Society, Interface · 2015Article
- TrAp: a tree approach for fingerprinting subclonal tumor composition.Nucleic acids research · 2013Article
- Quantifying the roles of cell motility and cell proliferation in a circular barrier assay.Journal of the Royal Society, Interface · 2013Article
- Radiobiological framework for the evaluation of stereotactic radiosurgery plans for invasive brain tumours.ISRN oncology · 2013Article
- The Ever-Changing Role of Medical Physicists in the Era of Personalized Medicine.Journal of medical physicsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a result of advanced treatment techniques, requiring precise target definitions, a need for more accurate delineation of the Clinical Target Volume (CTV) has arisen. Mathematical modelling is found to be a powerful tool to provide fairly accurate predictions for the Microscopic Extension (ME) of a tumour to be incorporated in a CTV. In general terms, biomathematical models based on a sequence of observations or development of a hypothesis assume some links between biological mechanisms involved in cancer development and progression to provide quantitative or qualitative measures of tumour behaviour as well as tumour response to treatment. Generally, two approaches are taken: deterministic and stochastic modelling. In this paper, recent mathematical models, including deterministic and stochastic methods, are reviewed and critically compared. It is concluded that stochastic models are more promising to provide a realistic description of cancer tumour behaviour due to being intrinsically probabilistic as well as discrete, which enables incorporation of patient-specific biomedical data such as tumour heterogeneity and anatomical boundaries.
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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.