ArticlePLoS computational biology2016
Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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
30 citing papers in PubMed.
- Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review.Health science reports · 2026Article
- Exploring the relationship between vascular remodelling and tumour growth using agent-based modelling.PLoS computational biology · 2026Article
- Article
- Cell-cell fusion in cancer: The next cancer hallmark?The international journal of biochemistry & cell biology · 2024Review
- Diverse mutant selection windows shape spatial heterogeneity in evolving populations.PLoS computational biology · 2024Article
- Simulating tumor volume dynamics in response to radiotherapy: Implications of model selection.Journal of theoretical biology · 2024Article
- Digitize your Biology! Modeling multicellular systems through interpretable cell behavior.bioRxiv : the preprint server for biology · 2023Article
- Diverse mutant selection windows shape spatial heterogeneity in evolving populations.bioRxiv : the preprint server for biology · 2023Article
- Radio-immune response modelling for spatially fractionated radiotherapy.Physics in medicine and biology · 2023Article
- Quantification of spatial and phenotypic heterogeneity in an agent-based model of tumour-macrophage interactions.PLoS computational biology · 2023Article
- Article
- HtrA3: a promising prognostic biomarker and therapeutic target for head and neck squamous cell carcinoma.PeerJ · 2023Article
- Multiscale modeling of drug resistance in glioblastoma with gene mutations and angiogenesis.Computational and structural biotechnology journal · 2023Article
- Translation of Precision Medicine Research Into Biomarker-Informed Care in Radiation Oncology.Seminars in radiation oncology · 2022Review
- Theoretical modeling of collaterally sensitive drug cycles: shaping heterogeneity to allow adaptive therapy.Journal of mathematical biology · 2021Article
- Revisiting a Null Hypothesis: Exploring the Parameters of Oligometastasis Treatment.International journal of radiation oncology, biology, physics · 2021Article
- Personalizing Radiotherapy Prescription Dose Using Genomic Markers of Radiosensitivity and Normal Tissue Toxicity in NSCLC.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2021Article
- Abnormal morphology biases hematocrit distribution in tumor vasculature and contributes to heterogeneity in tissue oxygenation.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Evidence for hypoxia increasing the tempo of evolution in glioblastoma.British journal of cancer · 2020Article
- Inferring Tumor Proliferative Organization from Phylogenetic Tree Measures in a Computational Model.Systematic biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripley's L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis.
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.