Why the study?
Can magnetic particle imaging (MPI) accurately quantify vascular stenoses in vessel phantoms?
Can magnetic particle imaging (MPI) accurately quantify vascular stenoses in vessel phantoms?
Magnetic particle imaging demonstrates high accuracy and reproducibility for quantifying vascular stenoses in a phantom model, highlighting its potential as a fast, radiation-free imaging modality.
Supports MPI stenosis quantification in phantoms; leaves open in vivo validation and clinical translation.
Magnetic particle imaging (MPI) is a promising new tomographic imaging method to detect the spatial distribution of superparamagnetic iron-oxide nanoparticles (SPIOs). The aim of this paper was to investigate the potential of MPI to quantify artificial stenoses in vessel phantoms. Custom-made stenosis phantoms (length 40 mm; inner diameter 8 mm) with different degrees of stenosis (0%, 25%, 50%, 75%, and 100%) were scanned in a custom-built MPI scanner (in-plane resolution: ~1-1.5 mm and field of view: 65 × 29 × 29 mm3). Phantoms were filled with diluted Feru-carbotran [SPIO agent, 5 mmol (Fe)/l]. Each measurement (overall acquisition time: 20 ms per image, 400 averages) was repeated ten times to assess reproducibility. The MPI signal was used for semi-automatic stenosis quantification. Two stenosis evaluation approaches were compared based on the signal intensity profile alongside the stenosis phantoms. Using a novel multi-step image evaluation approach, MPI allowed for accurate quantification of different stenosis grades. While low grade stenoses were slightly over-estimated, high grade stenoses were slightly underestimated. In particular, the 0%, 25%, and 50% stenosis phantoms revealed a 6.2% ± 0.8, 25.7% ± 1.0, and 48.0% ± 1.5 stenosis, respectively. The higher grade 75% stenosis phantom revealed a 73.3% ± 2.8 and the 100% stenosis phantom a 95.8% ± 1.9 stenosis. MPI accurately visualized and quantified different stenosis grades in vessel phantoms with high reproducibility demonstrating its great potential for fast and radiation-free preclinical cardiovascular imaging.
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Herz et al. (2017) studied this question.
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