» Articles » PMID: 33477058

Near Real-time Magnetic Particle Imaging for Visual Assessment of Vascular Stenosis in a Phantom Model

Overview
Journal Phys Med
Date 2021 Jan 21
PMID 33477058
Citations 1
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: This study aimed to investigate the potential of magnetic particle imaging (MPI) to quantify artificial stenoses in vessel phantoms in near real-time.

Methods: Custom-made stenosis phantoms with different degrees of stenosis (0%, 25%, 50%, 75%, and 100%; length 40 mm, inner diameter 8 mm, Polyoxymethylene) were filled with diluted Ferucarbotran (superparamagnetic iron-oxide nanoparticle (SPION) tracer agent, 500 mmol (Fe)/l). A traveling wave MPI scanner (spatial resolution ~ 2 mm, gradient strength ~ 1.5 T/m, field of view: 65 mm length and 29 mm diameter, frequencies f = 1050 Hz and f = 12150 Hz) was used to acquire images of the phantoms (200 ms total acquisition time per image, 10 averages). Standardized grey scaling was used for comparability. All measured stenoses (n = 80) were graded manually using a dedicated software tool.

Results: MPI allowed for accurate visualization of stenoses at a frame rate of 5frames per second. Less severe stenoses were detected more precisely than higher-grade stenoses and came with smaller standard deviations. In particular, the 0%, 25%, 50%, 75%, and 100% stenosis phantom were measured as 3.7 ± 2.7% (mean ± standarddeviation), 18.6 ± 1.8%, 52.8 ± 3.7%, 77.8 ± 14.8% and 100 ± 0%. Geometrical distortions occurred around the center of the high-grade stenosis and led to higher standard deviations compared to lower grade stenoses. In the frame of this study the MPI signal depended linearly on the SPION concentration down to 0.05 mmol (Fe)/l.

Conclusion: Near real-time MPI accurately visualized and quantified different stenosis grades in vascular phantoms.

Citing Articles

Fusion Networks of CNN and Transformer with Channel Attention for Accurate Tumor Imaging in Magnetic Particle Imaging.

Shang Y, Liu J, Wang Y Biology (Basel). 2024; 13(1).

PMID: 38275723 PMC: 11154287. DOI: 10.3390/biology13010002.