ArticleEuropean radiology2017
Quantification of antiangiogenic treatment effects on tissue heterogeneity in glioma tumour xenograft model using a combination of DCE-MRI and 3D-ultramicroscopy.
Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 5 citations in OpenAlex.
- Role of dynamic contrast-enhanced and dynamic susceptibility contrast imaging in evaluating the biological features of glioma.Quantitative imaging in medicine and surgery · 2025Article
- DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study.Clinical neuroradiology · 2021Article
- Prognostication of anaplastic astrocytoma patients: application of contrast leakage information of dynamic susceptibility contrast-enhanced MRI and dynamic contrast-enhanced MRI.European radiology · 2020Article
- Spatiotemporal heterogeneity of tumor vasculature during tumor growth and antiangiogenic treatment: MRI assessment using permeability and blood volume parameters.Cancer medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study aimed at assessing the effects of an anti-angiogenic treatment, which neutralises vascular endothelial growth factor (VEGF), on tumour heterogeneity.
methodsMurine glioma cells have been inoculated into the right brain frontal lobe of 16 mice. Anti-VEGF antibody was administered to a first group (n = 8), while a second group (n = 8) received a placebo. Magnetic resonance acquisitions, performed at days 10, 12, 15 and 23 following the implantation, allowed the derivation of a three-dimensional features dataset characterising tumour heterogeneity. Three-dimensional ultramicroscopy and standard histochemistry analysis have been performed to verify in vivo results.
resultsPlacebo-treated mice displayed a highly-vascularised area at the tumour periphery, a monolithic necrotic core and a chaotic dense vasculature across the entire tumour. In contrast, the B20-treated group did not show any highly vascularised regions and presents a fragmented necrotic core. A significant reduction of the number of vessel segments smaller than 17 μm has been observed. There was no difference in overall tumour volume and growth rate between the two groups.
conclusionsRegion-specific analysis revealed that VEGF inhibition affects only: (1) highly angiogenic compartments expressing high levels of VEGF and characterised by small capillaries, and also (2) the formation and structure of necrotic regions. These effects appear to be transient and limited in time. KEY POINTS: • VEGF inhibition affects only the highly angiogenic region and small capillaries network • VEGF inhibition is transient in time • Tumour volume is not affected by anti-angiogenic treatment • VEGF inhibition also influences the architecture of necrotic regions.
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.