Literature DB >> 20303995

Three-dimensional analysis of tumour vascular corrosion casts using stereoimaging and micro-computed tomography.

A A Folarin1, M A Konerding, J Timonen, S Nagl, R B Pedley.   

Abstract

OBJECTIVE: In order to perform effective translational research for cancer therapy, we need to employ pre-clinical models which reflect the clinical situation. The purpose of this study was to quantitatively compare the vascular architecture of human colorectal cancer and experimental tumour models to determine the suitability of animal models for vascular studies and antivascular therapy.
METHODS: In this study we investigated the three-dimensional properties of colonic tumour vasculature in both human clinical tissues (normal mucosa control [n=20], carcinoma [n=20] and adenoma [n=6]) and murine colorectal xenografts (LS147T [n=6] and SW1222 [n=6]). Scanning Electron Microscope Stereoimaging (SEM) and X-ray Micro-Computed Tomography (Micro-CT) methods were employed for 3D analyses of the vascular corrosion casts from these tissues.
RESULTS: Morphological measurements showed that there were significant differences in the underlying morphology in the different tissues. Of the studied xenografts, LS147T is more consistently similar to the vascular architecture of the human carcinoma than SW1222. The only reversal of this is for the inter-vessel distance.
CONCLUSION: While SEM stereoimaging provided better surface detailed resolution of the corrosion casts, it was complimented by the fully 3D micro-CT method. Comparison made between the xenografts and clinical tumours showed that the LS147T xenografts shared many similarities with the clinical tumour vasculature. This study provides insight into how to select the most suitable pre-clinical models for translational studies of clinical cancer therapy. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20303995      PMCID: PMC4398341          DOI: 10.1016/j.mvr.2010.03.007

Source DB:  PubMed          Journal:  Microvasc Res        ISSN: 0026-2862            Impact factor:   3.514


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