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Molecular Imaging: Reporter Gene Imaging

  • Inna Serganova
  • Phillipp Mayer-Kukuck
  • Ruimin Huang
  • Ronald BlasbergEmail author
Part of the Handbook of Experimental Pharmacology book series (HEP, volume 185/2)

Abstract

Non-invasive in-vivo molecular genetic imaging developed over the past decade and predominantly utilises radiotracer (PET, gamma camera, autoradiography), magnetic resonance and optical imaging technology. Molecular genetic imaging has its roots in both molecular biology and cell biology. The convergence of these disciplines and imaging modalities has provided the opportunity to address new research questions, including oncogenesis, tumour maintenance and progression, as well as responses to molecular-targeted therapy. Three different imaging strategies are described: (1) “bio-marker” or “surrogate” imaging; (2) “direct” imaging of specific molecules and pathway activity; (3) “indirect” reporter gene imaging. Examples of each imaging strategy are presented and discussed. Several applications of PET- and optical-based reporter imaging are demonstrated, including signal transduction pathway monitoring, oncogenesis in genetic mouse models, endogenous molecular genetic/biological processes and the response to therapy in animal models of human disease. Molecular imaging studies will compliment established ex-vivo molecular-biological assays that require tissue sampling by providing a spatial and a temporal dimension to our understanding of disease development and progression, as well as response to treatment. Although molecular imaging studies are currently being performed primarily in experimental animals, we optimistically expect they will be translated to human subjects with cancer and other diseases in the near future.

Keywords

Positron Emission Tomography Imaging Reporter Gene Expression Bioluminescence Imaging Single Photon Emission Compute Tomogra Magnetic Reso Imaging 
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-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Inna Serganova
    • 1
  • Phillipp Mayer-Kukuck
    • 1
  • Ruimin Huang
    • 1
  • Ronald Blasberg
    • 1
    Email author
  1. 1.Departments of Neurology and RadiologyMemorial Sloan-Kettering Cancer CenterNew YorkUSA

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