Assessment of Angiogenesis by MRI

  • Michal Neeman
Chapter
Part of the NATO ASI Series book series (NSSA, volume 298)

Abstract

Analysis of vascular remodeling in vivo is a major challenge both for the study of the regulatory mechanisms of its initiation and inhibition, and for clinical evaluation of pathological processes. Magnetic resonance imaging provides an attractive approach for non invasive analysis of angiogenesis. The aim of this review will be to introduce a number of specific MRI experiments that can provide information on angiogenesis, and these will be demonstrated through a few examples. The scope of this manuscript does not allow a thorough introduction of the principles of magnetic resonance imaging. Discussion will be further limited to the MRI signal that arises from the nuclear spin of the water hydrogens, as used in conventional clinical MRI. It is important to mention that while the MRI images are two dimensional, MRI is inherently a volumetric technique, and three dimensional data sets can be reconstructed either from a set of two dimensional slices or from a true isotropic 3D measurement. The non invasive nature of MRI allows for time course kinetic studies. The spatial resolution of MRI is limited primarily by the inherent insensitivity of nuclear magnetic resonance, and in vivo also by motion. Resolution of 1 mm is easily achieved in the clinic and 0.1 mm in research systems, in small laboratory animals. This resolution is not sufficient for resolving individual capillaries. However, the presence and characteristics of the vasculature can be inferred from the signal intensity (image contrast) in specific types of MRI experiments. The chapter will be divided into two major parts. Section 2 will review the use of exogenous MRI contrast agents that are injected systemically, usually intra venously.

Keywords

Contrast Agent Arterial Spin Label Water Hydrogen Multicellular Spheroid Small Laboratory Animal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Michal Neeman
    • 1
  1. 1.Department of Biological RegulationThe Weizmann Institute of ScienceRehovotIsrael

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