Magnetic Particle Imaging: In vitro Signal Analysis and Lumen Quantification of 21 Endovascular Stents

Int J Nanomedicine. 2021 Jan 11:16:213-221. doi: 10.2147/IJN.S284694. eCollection 2021.

Abstract

Purpose: Endovascular stents are medical devices, which are implanted in stenosed blood vessels to ensure sufficient blood flow. Due to a high rate of in-stent re-stenoses, there is the need of a noninvasive imaging method for the early detection of stent occlusion. The evaluation of the stent lumen with computed tomography (CT) and magnetic resonance imaging (MRI) is limited by material-induced artifacts. The purpose of this work is to investigate the potential of the tracer-based modality magnetic particle imaging (MPI) for stent lumen visualization and quantification.

Methods: In this in vitro study, 21 endovascular stents were investigated in a preclinical MPI scanner. Therefore, the stents were implanted in vessel phantoms. For the signal analysis, the phantoms were scanned without tracer material, and the signal-to-noise-ratio was analyzed. For the evaluation of potential artifacts and the lumen quantification, the phantoms were filled with diluted tracer agent. To calculate the stent lumen diameter a calibrated threshold value was applied.

Results: We can show that it is possible to visualize the lumen of a variety of endovascular stents without material induced artifacts, as the stents do not generate sufficient signals in MPI. The stent lumen quantification showed a direct correlation between the calculated and nominal diameter (r = 0.98).

Conclusion: In contrast to MRI and CT, MPI is able to visualize and quantify stent lumina very accurately.

Keywords: artifacts; endovascular stents; lumen quantification; magnetic particle imaging; superparamagnetic iron oxide nanoparticles.

MeSH terms

  • Artifacts
  • Endovascular Procedures*
  • Humans
  • Magnetic Phenomena*
  • Magnetic Resonance Imaging
  • Phantoms, Imaging
  • Signal Processing, Computer-Assisted*
  • Signal-To-Noise Ratio
  • Stents*
  • Tomography, X-Ray Computed

Grants and funding

This work was supported in part by Federal Ministry of Education and Research (BMBF) Grant Nos. 13GW0071D, 13GW0069A, 13GW0230B and 01DL17010A.