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USPIO enhanced lymph node MRI using 3D multi-echo GRE in a rabbit model.

Sung Hun Kim1, Soon Nam Oh1, Hyun Seok Choi1

  • 1Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.

Contrast Media & Molecular Imaging
|December 16, 2016
PubMed
Summary

Ultrasmall superparamagnetic iron oxide (USPIO) MRI shows promise for detecting metastatic lymph nodes. R2* mapping effectively differentiates metastatic from reactive lymph nodes, outperforming other USPIO quantification methods.

Keywords:
ferumoxtran-10lymph nodeslymphatic metastasismagnetite nanoparticlesrabbits

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Biomedical Engineering
  • Oncology

Background:

  • Ultrasmall superparamagnetic iron oxide (USPIO) is a negative MR contrast agent investigated for detecting metastatic lymph nodes.
  • Previous studies primarily relied on signal intensity for USPIO-enhanced MRI analysis.
  • Accurate quantification of USPIO particles is crucial for reliable lymph node metastasis detection.

Purpose of the Study:

  • To evaluate the diagnostic performance of three parametric approaches for quantifying USPIO particles in lymph nodes.
  • To compare normalized signal intensity, R2*, and susceptibility mapping using 3D multi-echo gradient echo (GRE) for USPIO detection.
  • To assess the utility of these parametric approaches in differentiating metastatic from reactive lymph nodes.

Main Methods:

  • USPIO-enhanced MRI was performed on nine rabbits with VX2 tumor implants before and after USPIO injection.
  • 3D multi-echo GRE sequences were used to acquire magnitude and phase data.
  • Multi-echo combined T2*-weighted images, R2* maps, and quantitative susceptibility maps were generated to analyze 18 lymph nodes (9 reactive, 9 metastatic).

Main Results:

  • All evaluated lymph nodes showed significant signal drops post-USPIO injection, indicating USPIO accumulation.
  • R2* difference before and after USPIO injection was significantly different (p < 0.05) between reactive and metastatic lymph nodes.
  • Normalized signal intensity and susceptibility did not show significant differences between reactive and metastatic lymph nodes.

Conclusions:

  • R2* mapping derived from 3D multi-echo GRE is a potentially valuable tool for detecting lymph node metastasis using USPIO-enhanced MRI.
  • Parametric analysis using R2* mapping offers improved differentiation of lymph node status compared to normalized signal intensity and susceptibility.
  • This quantitative MRI approach shows promise for improved lymph node staging in preclinical models.