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Neurol Res. 2008 Nov;30(9):952-9. doi: 10.1179/174313208X322761. Epub 2008 Jul 25.

The temporal correlation of dynamic contrast-enhanced magnetic resonance imaging with tumor angiogenesis in a murine glioblastoma model.

Author information

1
Department of Neurosurgery, Stanford University School of Medicine, 1201 Welch Road, Stanford, CA 94305, USA.

Abstract

OBJECTIVE:

Glioblastoma multiforme (GBM) is a WHO grade IV malignant brain tumor with poor prognosis, despite advances in surgical and adjuvant therapy. GBM is characterized by areas of central necrosis and high levels of angiogenesis, during which increased vascular permeability allows for the extravasation of endothelial progenitor cells to support blood vessel and tumor growth. The purpose of this study was to characterize changes in tumor vascular permeability, vascular density and vessel morphology in vivo during angiogenesis.

METHODS:

An orthotropic murine (GL26) glioblastoma model was used in this study. in vivo serial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in combination with histologic and molecular genetic analyses was performed to correlate in vivo imaging of vascular development.

RESULTS:

DCE-MRI revealed a significant change in tumor vessel permeability dependent upon tumor progression and size. Time to max signal intensity displayed a stepwise increase between days 21 and 24 (p<0.05), a critical period before exponential tumor growth during which a significant increase in tumor vascular density and vessel caliber is observed on histology. Furthermore, quantitative real-time PCR revealed a corollary increase in angiogenic signaling molecules before the observed changes on DCE-MRI.

DISCUSSION:

In vivo changes of orthotopic glioma blood vessel permeability as shown by DCE-MRI correlates with histologic quantification of vascular density and vessel caliber as well as with the molecular expression of angiogenic factors. DCE-MRI is a useful tool for non-invasive in vivo monitoring of angiogenesis in pre-clinical tumor models.

PMID:
18662497
DOI:
10.1179/174313208X322761
[Indexed for MEDLINE]

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