Micro computed tomography for vascular exploration
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* Corresponding author: Thierry Couffinhal thierry.couffinhal@inserm.fr
1 Heart and Vascular Research Center, Dartmouth Medical School, Lebanon, NH, USA
2 Cardiology Section, Dartmouth Medical School, Lebanon, NH, USA
3 Radiology, Dartmouth Medical School, Lebanon, NH, USA
4 Clinical Sites Research Program, Philips Research North America, Briarcliff Manor, NY, USA
5 Inserm U828, Plateforme d'Innovation Biotechnologique de Xavier Arnozan, Université Victor Ségalen Bordeaux 2, Pessac, France
6 Pôle Cardiothoracique, CHU de Bordeaux, Université Victor Ségalen Bordeaux 2, France
7 Yale University School of Medicine, New Haven CT, USA
8 Departments of Surgery, Vascular Section, Dartmouth Medical School, Lebanon, NH, USA
Journal of Angiogenesis Research 2010, 2:7 doi:10.1186/2040-2384-2-7
Published: 5 March 2010Abstract
Vascular exploration of small animals requires imaging hardware with a very high spatial resolution, capable of differentiating large as well as small vessels, in both in vivo and ex vivo studies. Micro Computed Tomography (micro-CT) has emerged in recent years as the preferred modality for this purpose, providing high resolution 3D volumetric data suitable for analysis, quantification, validation, and visualization of results. The usefulness of micro-CT, however, can be adversely affected by a range of factors including physical animal preparation, numerical quantification, visualization of results, and quantification software with limited possibilities. Exacerbating these inherent difficulties is the lack of a unified standard for micro-CT imaging. Most micro-CT today is aimed at particular applications and the software tools needed for quantification, developed mainly by imaging hardware manufacturers, lack the level of detail needed to address more specific aims. This review highlights the capabilities of micro-CT for vascular exploration, describes the current state of imaging protocols, and offers guidelines and suggestions aimed at making micro-CT more accurate, replicable, and robust.