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Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging
Magnetic resonance imaging (MRI) and magnetic particle imaging (MPI) are powerful methods in the early diagnosis of diseases. Both imaging techniques utilize magnetic nanoparticles that have high magnetic susceptibility, strong saturation magnetization, and no coercivity. FeraSpin(TM) R and its frac...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6149994/ https://www.ncbi.nlm.nih.gov/pubmed/29231851 http://dx.doi.org/10.3390/molecules22122204 |
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author | Hirt, Ann M. Kumari, Monika Heinke, David Kraupner, Alexander |
author_facet | Hirt, Ann M. Kumari, Monika Heinke, David Kraupner, Alexander |
author_sort | Hirt, Ann M. |
collection | PubMed |
description | Magnetic resonance imaging (MRI) and magnetic particle imaging (MPI) are powerful methods in the early diagnosis of diseases. Both imaging techniques utilize magnetic nanoparticles that have high magnetic susceptibility, strong saturation magnetization, and no coercivity. FeraSpin(TM) R and its fractionated products have been studied for their imaging performances; however, a detailed magnetic characterization in their immobilized state is still lacking. This is particularly important for applications in MPI that require fixation of magnetic nanoparticles with the target cells or tissues. We examine the magnetic properties of immobilized FeraSpin(TM) R, its size fractions, and Resovist(®), and use the findings to demonstrate which magnetic properties best predict performance. All samples show some degree of oxidation to hematite, and magnetic interaction between the particles, which impact negatively on image performance of the materials. MRI and MPI performance show a linear dependency on the slope of the magnetization curve, i.e., initial susceptibility, and average blocking temperature. The best performance of particles in immobilized state for MPI is found for particle sizes close to the boundary between superparamagnetic (SP) and magnetically ordered, in which only Néel relaxation is important. Initial susceptibility and bifurcation temperature are the best indicators to predict MRI and MPI performance. |
format | Online Article Text |
id | pubmed-6149994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61499942018-11-13 Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging Hirt, Ann M. Kumari, Monika Heinke, David Kraupner, Alexander Molecules Article Magnetic resonance imaging (MRI) and magnetic particle imaging (MPI) are powerful methods in the early diagnosis of diseases. Both imaging techniques utilize magnetic nanoparticles that have high magnetic susceptibility, strong saturation magnetization, and no coercivity. FeraSpin(TM) R and its fractionated products have been studied for their imaging performances; however, a detailed magnetic characterization in their immobilized state is still lacking. This is particularly important for applications in MPI that require fixation of magnetic nanoparticles with the target cells or tissues. We examine the magnetic properties of immobilized FeraSpin(TM) R, its size fractions, and Resovist(®), and use the findings to demonstrate which magnetic properties best predict performance. All samples show some degree of oxidation to hematite, and magnetic interaction between the particles, which impact negatively on image performance of the materials. MRI and MPI performance show a linear dependency on the slope of the magnetization curve, i.e., initial susceptibility, and average blocking temperature. The best performance of particles in immobilized state for MPI is found for particle sizes close to the boundary between superparamagnetic (SP) and magnetically ordered, in which only Néel relaxation is important. Initial susceptibility and bifurcation temperature are the best indicators to predict MRI and MPI performance. MDPI 2017-12-12 /pmc/articles/PMC6149994/ /pubmed/29231851 http://dx.doi.org/10.3390/molecules22122204 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hirt, Ann M. Kumari, Monika Heinke, David Kraupner, Alexander Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging |
title | Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging |
title_full | Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging |
title_fullStr | Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging |
title_full_unstemmed | Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging |
title_short | Enhanced Methods to Estimate the Efficiency of Magnetic Nanoparticles in Imaging |
title_sort | enhanced methods to estimate the efficiency of magnetic nanoparticles in imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6149994/ https://www.ncbi.nlm.nih.gov/pubmed/29231851 http://dx.doi.org/10.3390/molecules22122204 |
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