Magnetic Nanoparticle Imaging: Insight on the Effects of Magnetic Interactions and Hysteresis of Tracers
Source abstract
Abstract
The dynamic properties of magnetite nanoparticles are investigated by rate equations with the aim of clarifying the factors affecting their performance as tracers in magnetic particle imaging (MPI). It is shown that size-dependent effects such as magnetic hysteresis and dipole–dipole interaction may have a great impact on the behavior of MPI tracers. Usually, magnetic imaging exploits the higher-order harmonics of the magnetization waveform without considering either intraparticle hysteresis or interparticle interactions. These assumptions may result in an incorrect estimate (either by excess or by defect) of the nanoparticle concentration, which is the ultimate aim of MPI. The mismatch between real and estimated values is apparent for concentrations typical of some therapeutic applications of magnetic nanoparticles or reached by effect of particle accumulation in organs because of slow clearance processes. We show that this difficulty can be removed by measuring not only the magnitude of the third harmonic of the signal but also the phase shift with respect to the driving field. The proposed technique of signal adjustment makes use of the settings of present-day MPI operating devices. The validity of the adjustment procedure is checked by a proof of concept using nonuniform nanoparticle concentrations.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Characterization and Applications of Magnetic Nanoparticles · Nanoparticle-Based Drug Delivery · Microfluidic and Bio-sensing Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Advanced Materials Metrology and Life Sciences, Istituto Nazionale di Ricerca Metrologica (INRiM), Torino I-10135, Italy
References (81)
Show source-provided references
1. Gleich B. · 201410.1007/978-3-658-01961-7 ↗
2. Bakenecker, A.; Ahlborg, M.; Debbeler, C.; Kaethner, C.; Lüdtke-Buzug, K. In Precision Medicine: Tools and Quantitative Approaches; Deigner, H.P., Kohl, M., Eds. Academic Press, 2018; Chapter 9, pp 183–228.10.1016/B978-0-12-805364-5.00009-3 ↗
3. Enpuku, K.; Yoshida, T. In Bioimaging; Ueno, S., Ed. CRC Press: Boca Raton, FL, 2020; Chapter 7, pp 155–183.
4. 10.1021/acsanm.1c0076810.1021/acsanm.1c00768 ↗
5. 10.1002/jmri.2687510.1002/jmri.26875 ↗
6. 10.3390/diagnostics1010080010.3390/diagnostics10100800 ↗
7. https://www.magneticinsight.com/applications/.
8. 10.1021/acsnano.0c0322910.1021/acsnano.0c03229 ↗
9. 10.18383/j.tom.2020.0004310.18383/j.tom.2020.00043 ↗
10. 10.1021/acsnano.9b0866010.1021/acsnano.9b08660 ↗
11. 10.1039/D0NR07983A10.1039/D0NR07983A ↗
12. 10.3390/cancers1321528510.3390/cancers13215285 ↗
13. 10.1021/acsnano.0c0632610.1021/acsnano.0c06326 ↗
14. 10.1021/acsnano.8b0089310.1021/acsnano.8b00893 ↗
15. 10.1080/02656736.2020.185325210.1080/02656736.2020.1853252 ↗
16. 10.1039/D0NR00604A10.1039/D0NR00604A ↗
17. 10.7150/thno.4085810.7150/thno.40858 ↗
18. 10.1007/s11095-016-1958-510.1007/s11095-016-1958-5 ↗
19. 10.1088/1361-6560/aa6c9910.1088/1361-6560/aa6c99 ↗
20. 10.1021/acsanm.0c0077910.1021/acsanm.0c00779 ↗
21. 10.1016/j.cbpa.2018.04.01410.1016/j.cbpa.2018.04.014 ↗
22. 10.1021/acsanm.0c0089010.1021/acsanm.0c00890 ↗
23. 10.1021/acsanm.9b0097710.1021/acsanm.9b00977 ↗
24. 10.1038/natrevmats.2016.1410.1038/natrevmats.2016.14 ↗
25. 10.1080/03639045.2017.142196110.1080/03639045.2017.1421961 ↗
26. 10.2217/nnm-2018-004010.2217/nnm-2018-0040 ↗
27. 10.1016/j.jiec.2017.06.01910.1016/j.jiec.2017.06.019 ↗
28. 10.1016/j.jmmm.2018.10.08210.1016/j.jmmm.2018.10.082 ↗
29. 10.1002/wnan.157110.1002/wnan.1571 ↗
30. 10.1007/s10854-021-06865-810.1007/s10854-021-06865-8 ↗
31. 10.1039/D0NR07397K10.1039/D0NR07397K ↗
32. 10.1038/s41573-020-0090-810.1038/s41573-020-0090-8 ↗
33. 10.1039/c3nr00544e10.1039/c3nr00544e ↗
34. 10.1063/1.500639110.1063/1.5006391 ↗
35. 10.1038/s41598-020-58853-310.1038/s41598-020-58853-3 ↗
36. 10.1039/B922628C10.1039/B922628C ↗
37. 10.4236/ojapps.2018.8501410.4236/ojapps.2018.85014 ↗
38. 10.1021/acsnano.7b0484410.1021/acsnano.7b04844 ↗
39. 10.3174/ajnr.A589610.3174/ajnr.A5896 ↗
40. Cullity B. D. · 2009
41. 10.1016/j.jmmm.2019.16592710.1016/j.jmmm.2019.165927 ↗
42. 10.1039/D0CS00260G10.1039/D0CS00260G ↗
43. 10.1016/j.jmmm.2010.11.05410.1016/j.jmmm.2010.11.054 ↗
44. 10.1038/s41551-019-0506-010.1038/s41551-019-0506-0 ↗
45. 10.1088/1361-6560/aa70ca10.1088/1361-6560/aa70ca ↗
46. 10.1039/C9NR01395D10.1039/C9NR01395D ↗
47. 10.1002/adtp.20200006110.1002/adtp.202000061 ↗
48. 10.1016/j.lfs.2019.01.05610.1016/j.lfs.2019.01.056 ↗
49. 10.2147/IJN.S22314210.2147/IJN.S223142 ↗
50. 10.1080/17435390.2020.184293410.1080/17435390.2020.1842934 ↗
51. 10.3762/bjnano.1.2210.3762/bjnano.1.22 ↗
52. 10.1088/1361-6463/ab258010.1088/1361-6463/ab2580 ↗
53. 10.1007/978-3-540-69882-1_1510.1007/978-3-540-69882-1_15 ↗
54. 10.1088/1361-6463/ac000b10.1088/1361-6463/ac000b ↗
55. 10.1021/nn503888j10.1021/nn503888j ↗
56. 10.1016/j.jmmm.2016.10.09610.1016/j.jmmm.2016.10.096 ↗
57. 10.1088/1361-6463/aa590b10.1088/1361-6463/aa590b ↗
58. 10.1016/j.biomaterials.2014.04.03610.1016/j.biomaterials.2014.04.036 ↗
59. 10.1063/1.353663210.1063/1.3536632 ↗
60. 10.1103/PhysRevB.71.05440110.1103/PhysRevB.71.054401 ↗
61. 10.1103/PhysRevApplied.12.03404110.1103/PhysRevApplied.12.034041 ↗
62. 10.1039/C9NR09503A10.1039/C9NR09503A ↗
63. 10.1118/1.342629410.1118/1.3426294 ↗
64. 10.1021/acs.jpcc.8b1076310.1021/acs.jpcc.8b10763 ↗
65. 10.1103/PhysRevB.98.13442310.1103/PhysRevB.98.134423 ↗
66. 10.1039/D0NA00358A10.1039/D0NA00358A ↗
67. 10.1515/bmt-2012-005710.1515/bmt-2012-0057 ↗
68. 10.1063/1.367605310.1063/1.3676053 ↗
69. 10.1016/j.jmmm.2003.09.00110.1016/j.jmmm.2003.09.001 ↗
70. 10.1063/1.358677610.1063/1.3586776 ↗
71. 10.1209/0295-5075/28/9/01010.1209/0295-5075/28/9/010 ↗
72. 10.1063/1.480258310.1063/1.4802583 ↗
73. 10.1063/1.344587910.1063/1.3445879 ↗
74. Beola, L.; Gutiérrez, L.; Grazú, V.; Asín, L. In Nanomaterials for Magnetic and Optical Hyperthermia Applications; Fratila, R., De La Fuente, J. M., Eds. Elsevier, 2019; pp 317–337.10.1016/B978-0-12-813928-8.00012-0 ↗
75. 10.1007/s11060-010-0389-010.1007/s11060-010-0389-0 ↗
76. 10.1016/j.jmmm.2019.16620610.1016/j.jmmm.2019.166206 ↗
77. 10.3390/diagnostics1105077310.3390/diagnostics11050773 ↗
78. 10.1016/j.bspc.2021.10317110.1016/j.bspc.2021.103171 ↗
79. 10.1039/C4NR05061D10.1039/C4NR05061D ↗
80. 10.1016/j.cocis.2017.12.00310.1016/j.cocis.2017.12.003 ↗
81. 10.1002/aic.1714710.1002/aic.17147 ↗