MRI has proven to be a powerful imaging modality for non-invasive, whole body imaging, with meaningful image resolution for studying cellular dynamics. MRI contrast is generated by capitalizing on differences in water molecule microenvironment, including diffusion rate and direction, magnetic field differences, and water content. In order to use MRI to distinguish a unique population of cells from other cells in the body, such as a cell transplant, or the infiltration of immune cells to a disease, one of these properties needs to be altered, or a tracer needs to be introduced. This will generate contrast or signal from these cells.
Methods for Cell Tracking
1. Introduction
MRI has proven to be a powerful imaging modality for non-invasive, whole body imaging, with meaningful image resolution for studying cellular dynamics. MRI contrast is generated by capitalizing on differences in water molecule microenvironment, including diffusion rate and direction, magnetic field differences, and water content. In order to use MRI to distinguish a unique population of cells from other cells in the body, such as a cell transplant, or the infiltration of immune cells to a disease, one of these properties needs to be altered, or a tracer needs to be introduced. This will generate contrast or signal from these cells.
2.The early days...
The first reports of magnetic cell labeling for the purpose of specific cell tracking by MRI were published in 1992-3. Bulte, et al used two different versions of dextran coated magnetite to specifically label B- and T-lymphocytes by way of antibody mediated uptake 1 and various blood cells by viral envelope coated magnetoliposomes 2. Similarly, Yeh, et al used hydrophilic dextran coated magnetite nanoparticles to label T-lymphocytes, however without the use of antibodies 3. Two additional papers reported on magnetic cell labeling of neural stem cells with Hawrylak, et al using viral encapsulated magnetite 4 and Norman, et al using magnetite nanoparticles coated with wheat germ agglutinin 5. In 1995, ferumoxides was released as an FDA approved iron oxide nanoparticle. This dextran coated iron oxide nanoparticle was 100 – 150 nm hydrodynamic radius and contained a 5-10 nm iron oxide core 6. This standard, well characterized iron oxide nanoparticle allowed for numerous investigators to embrace magnetic cell labeling for MRI, however, low labeling amounts and efficiencies were often the case 7. In 2002, it was reported that combining simple transfection agents plus ferumoxides enabled robust labeling for a number of cell types 8. This discovery greatly accelerated the pace of MRI-based cell tracking as evidenced by a steep rise in number of publications per year investigating iron oxide labeled cells by MRI. The subsequent removal of ferumoxides from the market, forced investigators to refocus efforts around other commercially available agents or to fabricate their own nanoparticles.
3 Iron oxide based contrast agents
3.1 Ferumoxytol and other commercially available agents
The void left by ferumoxides has largely been filled by ferumoxytol, an 30 nm diameter iron oxide nanoparticle with polyglucose sorbitol carboxymethylether coating currently only FDA-approved for treating anemia. Though ferumoxytol harbors a black box warning – as do the gadolinium contrast agents – ferumoxytol generally has a good safety record for MRI 9-10. Cells can be labeled ex vivo with ferumoxytol via standard cell culture methods as described in Section 4. Ferucarbotran has also re-emerged as a robust cell labeling agent, initially introduced for magnetic particle imaging, but of course, finding use for MRI as well. Commercial versions of ferumoxides still exist though no longer marketed by the trade name ‘Feridex’.
3.2 Non-commercial particles
Iron oxide nanoparticles have been the workhorse for MRI-based cell tracking for nearly 30 years. Iron oxide is a general term for molecules containing iron and oxygen, with several molecules such as Fe3O4, Fe2O3, and FeO easily synthesized. In bulk, these materials are magnetic, but as nanomaterials ~ <30-40 nm, these materials become superparamagnetic. This term describes the property of a material to achieve magnetism when placed inside a magnetic field, but lose it when removed from the field, that is, there is no or very little magnetic hysteresis. Facile synthetic approaches can be accomplished in water 11 or organic solvents 12. Aqueous magnetite is usually formed by the base catalyzed precipitation of magnetite from Fe(II) and Fe(III) salts, followed by citrate or oleic acid stabilization. Hydrophobic magnetite is most often formed by thermal decomposition of Fe(II) salts with oleic acid capping. Nanocrystal sizes range in diameter from 5-20 nm, with lower polydispersity and higher saturation magnetization achieved by the thermal decomposition route. Magnetite formation and properties are extensively reviewed in 11.
Iron oxide is potentially harmful to cells 13, so polymer coating strategies are employed to protect the cores from biology – and biology from the cores. An enormous array of natural and synthetic polymers has been used to coat particles, with varying degradation kinetics and functionalities. These have been reviewed extensively numerous times with an excellent recent review here 14. In general, particles are encased within polymers as either single or few cores within polymer shells in a core:shell fashion, or are encapsulated en mass throughout larger polymer particles via emulsion methodologies, such as PLGA or cellulose 15-16. Larger polymer particles are reviewed here 17.
The superparamagnetic nature of these nanomaterials enables their detection via T2 and T2* weighted sequences. The diffusion of water through inhomogeneous magnetic field gradients caused by the nanoparticles enables T2 contrast while the static magnetic field caused by ensembles of nanoparticles or by microparticles or MPIOs allows T2* weighted contrast 18. Experimental MRI sequences have been developed to specifically detect iron oxide labeled cells by providing bright contrast. These include IRON (inversion-recovery with ON-resonant water suppression) 19, Offâresonance saturation as a means of generating contrast with superparamagnetic nanoparticles 20, and GRASP (GRadient echo Acquisition for Superparamagnetic particles with positive contrast) 21.
3.3 Genetics Biological mechanisms for forming iron oxide nanocrystals include the protein ferritin, the magnetosomes found in magnetotactic bacteria and melanin. In general, ferritin contains a rather weak iron oxide nanocrystal, mainly due to the non-uniform crystal properties of the iron oxide. Interesting approaches have been reported to modify the ferritin macromolecule to improve its relaxivity, reviewed in 22, with the most recent report achieving 50% improvement in relaxivity by enhancing the biomineralization of iron 23. Various aspects of magnetosome formation have been parsed out and recapitulated in mammalian cells, including the iron transporter MagA 24. While contrast enhancement from iron accumulation is possible, fully reconstituting iron oxide nanocrystals themselves via magnetosome machinery remains elusive still. Lastly, melanin is synthesized by tyrosine hydroxylase from tyrosine containing monomers. Importantly, melanin acts like a metal sponge, and so an abundance of melanin will accumulate metals and yield MRI contrast, especially if those metals are iron. Thus, overexpression of tyrosine hydroxylase could be used via melanin synthesis to recruit iron locally 25. An excellent review is 26.
4 Fluorine based contrast agents (tracers)
Fluorine based contrast agents have emerged as a viable cell labeling strategy. Fluorine has no abundance in the body, and so cells can be labeled with fluorine based agents can be detected unambiguously following transplant, making fluorine based agent more like tracers. The most promising agents are perfluorocarbon based agents which are readily taken up by cells by simple incubation. This class of agents is extensively reviewed in 27.
5 Cell labeling
5.1 In vitro
Cells are plated in culture vessels and incubated with particles. Some particles, such as MPIOs 28 and PLGA encapsulated iron oxide particles 15, sink onto adherent cells and can be endocytosed within hours. Other particles which remain in suspension require assistance for efficient labeling. Chemical tools that were originally developed for transfecting genes into cells have been adapted for cell labeling, and have the ability to increase the efficiency of particle uptake into cells in vivo or in vitro. These include the use of poly-L-lysine (PLL) 8 or protamine sulfate 29 which are co-incubated with particles and cells for in vitro labeling and co-injected with particles for in vivo labeling. A recent report on the complexation of heparin, protamine sulfate and feromoxytol has shown good uptake properties 30. Most papers simply use protamine sulfate. For cells which grow in suspension, transfection agents are entirely necessary, or other affinity based tagging such as antibodies 31.
5.2 In vivo
In vivo cell labeling has been demonstrated in a number of systems. In the brain, endogenous neural progenitor cells can be labeled by directly injecting magnetic particles either into the lateral ventricles 32 or into the rostral migratory stream 33. These cells endocytose the particles in situ and carry them as they migrate. In vivo labeling of dendritic cells has been performed in the context of vaccine development 34. In vivo labeling of immune cells, macrophages in particular, has been demonstrated in a wide variety of models across the biomedical spectrum 35-38. Whether cells are labeled as circulating monocytes or as homed macrophages remains to be fully discerned.
6. MRI methods & Data analysis
6.1 Iron quantification
Quantification of MRI-based cell tracking experiments is perhaps the least developed aspect of the experiment. In general, the data analysis remains phenomenological, that is, results are reported in vague terms of “cells are detected”. But in order to realize the true power of this technique, methodologies are required to quantify cell numbers, migration rates and other quantitative parameters. One approach to deriving quantitative metrics from this data is iron quantification. The position here, is that if we know how much iron cells contain, and we can quantify the iron, then we can quantify the number of cells. Two methods for iron quantification have emerged. The first is relaxometry. Reports detailing the use of T2 measurements to quantify iron content allow the measurement of cell numbers 39-40. A second technique is based on SWIFT imaging 41. The challenge with these techniques is that the iron oxide nanoparticles can degrade over time, which affects their magnetic properties, and hence their relaxation properties. So, over time, these methods would be dependent on these changes. Further, relaxation times depend on clustering of particles, so as cells migrate, this clustering is reduced.
6.2 Cell counting
An alternative method for quantifying cell numbers is to use MRI-based single cell detection to enumerate cells. If cell can be labeled with enough iron oxide >10 pg/cell, and with high enough resolution, ~100 micron, individual cells can be detected in vivo. Spot detection paradigms can then be used to identify these cells and enumerate them. This has been nicely demonstrated by 42 and by 43. The challenge, of course, is to provide this high resolution in scans of animals larger than rodents. This methodology also provides a nice mechanism for monitoring migration rates of cells.
1. Bulte, J. W.; Hoekstra, Y.; Kamman, R. L.; Magin, R. L.; Webb, A. G.; Briggs, R. W.; Go, K. G.; Hulstaert, C. E.; Miltenyi, S.; The, T. H.; . Specific MR imaging of human lymphocytes by monoclonal antibody-guided dextran-magnetite particles. Magn Reson. Med 1992, 25 (1), 148-157.
2. Bulte, J. W.; Ma, L. D.; Magin, R. L.; Kamman, R. L.; Hulstaert, C. E.; Go, K. G.; The, T. H.; de Leij, L., Selective MR imaging of labeled human peripheral blood mononuclear cells by liposome mediated incorporation of dextran-magnetite particles. Magn Reson. Med 1993, 29 (1), 32-37.
3. Yeh, T. C.; Zhang, W.; Ildstad, S. T.; Ho, C., Intracellular labeling of T-cells with superparamagnetic contrast agents. Magn Reson. Med 1993, 30 (5), 617-625.
4. Hawrylak, N.; Ghosh, P.; Broadus, J.; Schlueter, C.; Greenough, W. T.; Lauterbur, P. C., Nuclear magnetic resonance (NMR) imaging of iron oxide-labeled neural transplants. Exp. Neurol 1993, 121 (2), 181-192.
5. Norman, A. B.; Thomas, S. R.; Pratt, R. G.; Lu, S. Y.; Norgren, R. B., Magnetic-Resonance-Imaging of Neural Transplants in Rat-Brain Using A Superparamagnetic Contrast Agent. Brain Research 1992, 594 (2), 279-283.
6. Bulte, J. W.; Kraitchman, D. L., Iron oxide MR contrast agents for molecular and cellular imaging. NMR Biomed 2004, 17 (7), 484-499.
7. Arbab, A. S.; Bashaw, L. A.; Miller, B. R.; Jordan, E. K.; Bulte, J. W.; Frank, J. A., Intracytoplasmic tagging of cells with ferumoxides and transfection agent for cellular magnetic resonance imaging after cell transplantation: methods and techniques. Transplantation 2003, 76 (7), 1123-1130.
8. Frank, J. A.; Zywicke, H.; Jordan, E. K.; Mitchell, J.; Lewis, B. K.; Miller, B.; Bryant, L. H., Jr.; Bulte, J. W., Magnetic intracellular labeling of mammalian cells by combining (FDA-approved) superparamagnetic iron oxide MR contrast agents and commonly used transfection agents. Acad. Radiol 2002, 9 Suppl 2, S484-S487.
9. Muehe, A. M.; Feng, D.; von Eyben, R.; Luna-Fineman, S.; Link, M. P.; Muthig, T.; Huddleston, A. E.; Neuwelt, E. A.; Daldrup-Link, H. E., Safety Report of Ferumoxytol for Magnetic Resonance Imaging in Children and Young Adults. Invest Radiol 2016, 51 (4), 221-227.
10. Nguyen, K. L.; Yoshida, T.; Han, F.; Ayad, I.; Reemtsen, B. L.; Salusky, I. B.; Satou, G. M.; Hu, P.; Finn, J. P., MRI with ferumoxytol: A single center experience of safety across the age spectrum. J Magn Reson Imaging 2017, 45 (3), 804-812.
11. Laurent, S.; Forge, D.; Port, M.; Roch, A.; Robic, C.; Elst, L. V.; Muller, R. N., Magnetic iron oxide nanoparticles: Synthesis, stabilization, vectorization, physicochemical characterizations, and biological applications. Chemical Reviews 2008, 108 (6), 2064-2110.
12. Park, J.; An, K.; Hwang, Y.; Park, J. G.; Noh, H. J.; Kim, J. Y.; Park, J. H.; Hwang, N. M.; Hyeon, T., Ultra-large-scale syntheses of monodisperse nanocrystals. Nat. Mater 2004, 3 (12), 891-895.
13. Laffon, B.; Fernandez-Bertolez, N.; Costa, C.; Brandao, F.; Teixeira, J. P.; Pasaro, E.; Valdiglesias, V., Cellular and Molecular Toxicity of Iron Oxide Nanoparticles. Adv Exp Med Biol 2018, 1048, 199-213.
14. Javed, Y.; Akhtar, K.; Anwar, H.; Jamil, Y., MRI based on iron oxide nanoparticles contrast agents: effect of oxidation state and architecture. Journal of Nanoparticle Research 2017, 19 (11).
15. Granot, D.; Nkansah, M. K.; Bennewitz, M. F.; Tang, K. S.; Markakis, E. A.; Shapiro, E. M., Clinically viable magnetic poly(lactide-co-glycolide) particles for MRI-based cell tracking. Magn Reson. Med 2014, 71 (3), 1238-1250.
16. Nkansah, M. K.; Thakral, D.; Shapiro, E. M., Magnetic poly(lactide-co-glycolide) and cellulose particles for MRI-based cell tracking. Magn Reson Med 2011, 65 (6), 1776-1785.
17. Shapiro, E. M., Biodegradable, polymer encapsulated, metal oxide particles for MRI-based cell tracking. Magn. Reson. Med 2014.
18. Bowen, C. V.; Zhang, X. W.; Saab, G.; Gareau, P. J.; Rutt, B. K., Application of the static dephasing regime theory to superparamagnetic iron-oxide loaded cells. Magnetic Resonance in Medicine 2002, 48 (1), 52-61.
19. Stuber, M.; Gilson, W. D.; Schar, M.; Kedziorek, D. A.; Hofmann, L. V.; Shah, S.; Vonken, E. J.; Bulte, J. W.; Kraitchman, D. L., Positive contrast visualization of iron oxide-labeled stem cells using inversion-recovery with ON-resonant water suppression (IRON). Magn Reson. Med 2007, 58 (5), 1072-1077.
20. Zurkiya, O.; Hu, X., Off-resonance saturation as a means of generating contrast with superparamagnetic nanoparticles. Magn Reson. Med 2006, 56 (4), 726-732.
21. Mani, V.; Briley-Saebo, K. C.; Itskovich, V. V.; Samber, D. D.; Fayad, Z. A., GRadient echo Acquisition for Superparamagnetic particles with positive contrast (GRASP): Sequence characterization in membrane and glass superparamagnetic iron oxide phantoms at 1.5T and 3T. Magnetic Resonance in Medicine 2006, 55 (1), 126-135.
22. Matsumoto, Y.; Jasanoff, A., Metalloprotein-based MRI probes. FEBS Lett 2013, 587 (8), 1021-1029.
23. Matsumoto, Y.; Chen, R.; Anikeeva, P.; Jasanoff, A., Engineering intracellular biomineralization and biosensing by a magnetic protein. Nat. Commun 2015, 6, 8721.
24. Zurkiya, O.; Chan, A. W.; Hu, X., MagA is sufficient for producing magnetic nanoparticles in mammalian cells, making it an MRI reporter. Magn Reson. Med 2008, 59 (6), 1225-1231.
25. Enochs, W. S.; Petherick, P.; Bogdanova, A.; Mohr, U.; Weissleder, R., Paramagnetic metal scavenging by melanin: MR imaging. Radiology 1997, 204 (2), 417-423.
26. Naumova, A. V.; Vande Velde, G., Genetically encoded iron-associated proteins as MRI reporters for molecular and cellular imaging. Wiley Interdiscip Rev Nanomed Nanobiotechnol 2018, 10 (2).
27. Jirak, D.; Galisova, A.; Kolouchova, K.; Babuka, D.; Hruby, M., Fluorine polymer probes for magnetic resonance imaging: quo vadis? MAGMA 2019, 32 (1), 173-185.
28. Shapiro, E. M.; Skrtic, S.; Koretsky, A. P., Sizing it up: cellular MRI using micron-sized iron oxide particles. Magn Reson. Med 2005, 53 (2), 329-338.
29. Janic, B.; Rad, A. M.; Jordan, E. K.; Iskander, A. S.; Ali, M. M.; Varma, N. R.; Frank, J. A.; Arbab, A. S., Optimization and validation of FePro cell labeling method. PLoS. One 2009, 4 (6), e5873.
30. Thu, M. S.; Bryant, L. H.; Coppola, T.; Jordan, E. K.; Budde, M. D.; Lewis, B. K.; Chaudhry, A.; Ren, J.; Varma, N. R.; Arbab, A. S.; Frank, J. A., Self-assembling nanocomplexes by combining ferumoxytol, heparin and protamine for cell tracking by magnetic resonance imaging. Nat. Med 2012, 18 (3), 463-467.
31. Shapiro, E. M.; Medford-Davis, L. N.; Fahmy, T. M.; Dunbar, C. E.; Koretsky, A. P., Antibody-mediated cell labeling of peripheral T cells with micron-sized iron oxide particles (MPIOs) allows single cell detection by MRI. Contrast. Media Mol. Imaging 2007, 2 (3), 147-153.
32. Granot, D.; Scheinost, D.; Markakis, E. A.; Papademetris, X.; Shapiro, E. M., Serial monitoring of endogenous neuroblast migration by cellular MRI. Neuroimage 2011, 57 (3), 817-824.
33. Nieman, B. J.; Shyu, J. Y.; Rodriguez, J. J.; Garcia, A. D.; Joyner, A. L.; Turnbull, D. H., In vivo MRI of neural cell migration dynamics in the mouse brain. Neuroimage 2010, 50 (2), 456-464.
34. Long, C. M.; van Laarhoven, H. W.; Bulte, J. W.; Levitsky, H. I., Magnetovaccination as a novel method to assess and quantify dendritic cell tumor antigen capture and delivery to lymph nodes. Cancer Res 2009, 69 (7), 3180-3187.
35. Nejadnik, H.; Tseng, J.; Daldrup-Link, H., Magnetic resonance imaging of stem cell-macrophage interactions with ferumoxytol and ferumoxytol-derived nanoparticles. Wiley Interdiscip Rev Nanomed Nanobiotechnol 2019, e1552.
36. Aghighi, M.; Theruvath, A. J.; Pareek, A.; Pisani, L. L.; Alford, R.; Muehe, A. M.; Sethi, T. K.; Holdsworth, S. J.; Hazard, F. K.; Gratzinger, D.; Luna-Fineman, S.; Advani, R.; Spunt, S. L.; Daldrup-Link, H. E., Magnetic Resonance Imaging of Tumor-Associated Macrophages: Clinical Translation. Clin Cancer Res 2018, 24 (17), 4110-4118.
37. Nejadnik, H.; Lenkov, O.; Gassert, F.; Fretwell, D.; Lam, I.; Daldrup-Link, H. E., Macrophage phagocytosis alters the MRI signal of ferumoxytol-labeled mesenchymal stromal cells in cartilage defects. Sci Rep 2016, 6, 25897.
38. Khurana, A.; Chapelin, F.; Beck, G.; Lenkov, O. D.; Donig, J.; Nejadnik, H.; Messing, S.; Derugin, N.; Chan, R. C.; Gaur, A.; Sennino, B.; McDonald, D. M.; Kempen, P. J.; Tikhomirov, G. A.; Rao, J.; Daldrup-Link, H. E., Iron administration before stem cell harvest enables MR imaging tracking after transplantation. Radiology 2013, 269 (1), 186-97.
39. Liu, W.; Dahnke, H.; Rahmer, J.; Jordan, E. K.; Frank, J. A., Ultrashort T2* relaxometry for quantitation of highly concentrated superparamagnetic iron oxide (SPIO) nanoparticle labeled cells. Magn Reson. Med 2009, 61 (4), 761-766.
40. Liu, W.; Frank, J. A., Detection and quantification of magnetically labeled cells by cellular MRI. Eur. J. Radiol 2009, 70 (2), 258-264.
41. Zhang, J.; Chamberlain, R.; Etheridge, M.; Idiyatullin, D.; Corum, C.; Bischof, J.; Garwood, M., Quantifying iron-oxide nanoparticles at high concentration based on longitudinal relaxation using a three-dimensional SWIFT look-locker sequence. Magn. Reson. Med 2014, 71 (6), 1982-1988. 42. Mori, Y.; Chen, T.; Fujisawa, T.; Kobashi, S.; Ohno, K.; Yoshida, S.; Tago, Y.; Komai, Y.; Hata, Y.; Yoshioka, Y., From cartoon to real time MRI: in vivo monitoring of phagocyte migration in mouse brain. Sci. Rep 2014, 4, 6997.
43. Afridi, M. J.; Ross, A.; Liu, X. M.; Bennewitz, M. F.; Shuboni, D. D.; Shapiro, E. M., Intelligent and Automatic In Vivo Detection and Quantification of Transplanted Cells in MRI. Magnetic Resonance in Medicine 2017, 78 (5), 1991-2002.