Distribution of Superparamagnetic Nanoparticles in Lymphatic Tissue for Sentinel Lymph Node Detection in Breast Cancer by Magnetic Particle Imaging

  • Dominique Finas
  • Kristin Baumann
  • Katja Heinrich
  • Britta Ruhland
  • Lotta Sydow
  • Ksenija Gräfe
  • Timo Sattel
  • Kerstin Lüdtke-Buzug
  • Thorsten Buzug
Part of the Springer Proceedings in Physics book series (SPPHY, volume 140)

Abstract

Breast cancer diagnostic and treatment consists of surgical tumor removal and axillary lymph node resection. Radical axillary lymph node removemend is associated with high morbidity and significant loss of quality of life. The concept of sentinel lymph node biopsy (SNLB) by the use of dye and radio nuclides strongly reduced those side effects. To further reduce the side effects when axillary lymph nodes are removed, super paramagnetic iron oxide nano particles (SPIOs) could replace these marker substances. The magnetic particle imaging (MPI)-procedure will be used to visualize these SPIOs. Intraoperative three-dimensional MPI imaging and distinct localization probably by the use of a MPI hand probe will facilitate the axillary SNL detection and moreover makes it more precise. A mouse model was applied to prove the mentioned principle of SNLB by MPI. We are presenting first results of this approach and, additionally the qualitative and semi-quantitative distribution of SPIOs in lymph-fat tissue is shown for the first time. SPIOs are moving from the injection site through the lymph-fat tissue to the axillary region and finally into the axillary lymph nodes. This was approved by histology and prussian blue iron staining of the slides, electron transmission microscopy and in vivo magnetic resonance imaging. The concept of SNLB by MPI can be applied in principle in all solid tumors.

Keywords

Sentinel Lymph Node Mammary Gland Sentinel Lymph Node Biopsy Axillary Lymph Node Prussian Blue 
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 GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Dominique Finas
    • 1
  • Kristin Baumann
    • 1
  • Katja Heinrich
    • 1
  • Britta Ruhland
    • 1
  • Lotta Sydow
    • 1
  • Ksenija Gräfe
    • 2
  • Timo Sattel
    • 2
  • Kerstin Lüdtke-Buzug
    • 2
  • Thorsten Buzug
    • 2
  1. 1.Department of Obstetrics and GynecologyUniversity of LübeckLübeckGermany
  2. 2.Institute of Medical EngineeringUniversity of LübeckLübeckGermany

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