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Quantitative 19F MRI of perfluoro-15-crown-5-ether using uniformity correction of the spin excitation and signal reception

  • Ina Vernikouskaya
  • Alexander Pochert
  • Mika Lindén
  • Volker Rasche
Research Article
  • 28 Downloads

Abstract

Objectives

A common limitation of all 1H contrast agents is that they only allow indirect visualization through modification of the intrinsic properties of the tissue, making quantification of this effect challenging. 19F compounds, on the contrary, are measured directly, without any background signal. There is a linear relationship between the amount of 19F spins and the intensity of the signal. However, non-uniformity of the radiofrequency field may lead to errors in the quantified 19F signal and should be carefully addressed for any quantitative imaging.

Materials and methods

Adaptation of the previously introduced \(B_{1}^{ + }\) mapping technique to the problem of quantifying the 19F signal from perfluoro-15-crown-5-ether (PFCE) is proposed in this work. Initial evaluation of the proposed technique simultaneously accounting for transmit \(B_{1}^{ + }\) and receive \(B_{1}^{ - }\) field inhomogeneities is performed in a PFCE phantom. As a proof of concept, in vivo quantification of the 19F signal is performed in a murine model after application of custom-designed hollow mesoporous silica spheres (HMSS) loaded with PFCE.

Results

A phantom experiment clearly shows that only compensation for both transmit and receive characteristics outperforms inaccurate quantification based on the non- or partly-corrected signal intensities. Furthermore, an optimized protocol is proposed for in vivo application.

Conclusion

The proposed \(B_{1}^{ + }\)/\(B_{1}^{ - }\) mapping technique represents a simple to implement and easy-to-use solution for quantification of the 19F signal from PFCE in the presence of B1-field inhomogeneities.

Keywords

19F MRI Quantification B1 inhomogeneity Perfluoro-15-crown-5-ether Hollow mesoporous silica spheres 

Abbreviations

CA

Contrast agent

FA

Flip angle

HMSS

Hollow mesoporous silica sphere

HMSS-PFCE

HMSS nanoparticles loaded with PFCE

MSE

Multiple spin echo

MSN

Mesoporous amorphous silica nanoparticle

PFC

Perfluorocarbon

PFCE

Perfluoro-15-crown-5-ether

RR-VFA

Reference region variable flip angle

SE-IR

Spin echo inversion-recovery

SPGR

Spoiled gradient echo

RES

Reticuloendothelial system

Notes

Acknowledgements

The authors would like to thank the Ulm University Center for Translational Imaging MoMAN for its support.

Author contributions

All authors were involved in the conception and design of the study and contributed to the interpretation of the data. IV performed optimization of the MR imaging protocols, acquisition of the data, and data processing. AP performed preparation of the PFCE phantom and the synthesis and characterization of the nanoparticles. IV and AP drafted the manuscript; ML and VR revised it critically for important intellectual content. All authors read and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there are no relationships that could be construed as a conflict of interest.

Ethical approval

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. All procedures performed in study involving animals were in accordance with the ethical standards of the institution at which the study was conducted.

Supplementary material

10334_2018_696_MOESM1_ESM.docx (4.6 mb)
Supplementary material 1 (DOCX 4722 kb)

REFERENCES

  1. 1.
    Sinharay S, Pagel MD (2016) Advances in magnetic resonance imaging contrast agents for biomarker detection. Annu Rev Anal Chem (Palo Alto Calif) 9(1):95–115CrossRefGoogle Scholar
  2. 2.
    Hingorani DV, Bernstein AS, Pagel MD (2015) A review of responsive MRI contrast agents: 2005–2014. Contrast Media Mol Imaging 10(4):245–265CrossRefPubMedGoogle Scholar
  3. 3.
    Zuo Z, Syrovets T, Wu Y, Hafner S, Vernikouskaya I, Liu W et al (2017) The CAM cancer xenograft as a model for initial evaluation of MR labelled compounds. Sci Rep 7:46690CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Vernikouskaya I, Fekete N, Bannwarth M, Erle A, Rojewski M, Landfester K et al (2014) Iron-loaded PLLA nanoparticles as highly efficient intracellular markers for visualization of mesenchymal stromal cells by MRI. Contrast Media Mol Imaging 9(2):109–121CrossRefPubMedGoogle Scholar
  5. 5.
    Pan D, Schmieder AH, Wickline SA, Lanza GM (2011) Manganese-based MRI contrast agents: past, present and future. Tetrahedron 67(44):8431–8444CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    de Rochefort L, Nguyen T, Brown R, Spincemaille P, Choi G, Weinsaft J et al (2008) In vivo quantification of contrast agent concentration using the induced magnetic field for time-resolved arterial input function measurement with MRI. Med Phys 35(12):5328–5339CrossRefPubMedGoogle Scholar
  7. 7.
    Chen J, Lanza GM, Wickline SA (2010) Quantitative magnetic resonance fluorine imaging: today and tomorrow. Wiley Interdiscip Rev Nanomed Nanobiotechnol 2(4):431–440CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Morawski AM, Winter PM, Yu X, Fuhrhop RW, Scott MJ, Hockett F et al (2004) Quantitative “magnetic resonance immunohistochemistry” with ligand-targeted (19)F nanoparticles. Magn Reson Med 52(6):1255–1262CrossRefPubMedGoogle Scholar
  9. 9.
    Shukla HP, Mason RP, Bansal N, Antich PP (1996) Regional myocardial oxygen tension: 19F MRI of sequestered perfluorocarbon. Magn Reson Med 35(6):827–833CrossRefPubMedGoogle Scholar
  10. 10.
    Zhao D, Constantinescu A, Jiang L, Hahn EW, Mason RP (2001) Prognostic radiology: quantitative assessment of tumor oxygen dynamics by MRI. Am J Clin Oncol 24(5):462–466CrossRefPubMedGoogle Scholar
  11. 11.
    Schlemmer HP, Becker M, Bachert P, Dietz A, Rudat V, Vanselow B et al (1999) Alterations of intratumoral pharmacokinetics of 5-fluorouracil in head and neck carcinoma during simultaneous radiochemotherapy. Cancer Res 59(10):2363–2369PubMedGoogle Scholar
  12. 12.
    Balducci A, Wen Y, Zhang Y, Helfer BM, Hitchens TK, Meng WS et al (2013) A novel probe for the non-invasive detection of tumor-associated inflammation. Oncoimmunology 2(2):e23034CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Huang MQ, Ye Q, Williams DS, Ho C (2002) MRI of lungs using partial liquid ventilation with water-in-perfluorocarbon emulsions. Magn Reson Med 48(3):487–492CrossRefPubMedGoogle Scholar
  14. 14.
    Ruiz-Cabello J, Barnett BP, Bottomley PA, Bulte JW (2011) Fluorine 19F MRS and MRI in biomedicine. NMR Biomed 24(2):114–129CrossRefPubMedGoogle Scholar
  15. 15.
    Waiczies S, Millward JM, Starke L, Delgado PR, Huelnhagen T, Prinz C et al (2017) Enhanced fluorine-19 MRI sensitivity using a cryogenic radiofrequency probe: technical developments and ex vivo demonstration in a mouse model of neuroinflammation. Sci Rep 7(1):9808CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Srinivas M, Cruz LJ, Bonetto F, Heerschap A, Figdor CG, de Vries IJM (2010) Customizable, multi-functional fluorocarbon nanoparticles for quantitative in vivo imaging using 19F MRI and optical imaging. Biomaterials 31(27):7070–7077CrossRefPubMedGoogle Scholar
  17. 17.
    Jacoby C, Temme S, Mayenfels F, Benoit N, Krafft MP, Schubert R et al (2014) Probing different perfluorocarbons for in vivo inflammation imaging by 19F MRI: image reconstruction, biological half-lives and sensitivity. NMR Biomed 27(3):261–271CrossRefPubMedGoogle Scholar
  18. 18.
    Krafft MP (2001) Fluorocarbons and fluorinated amphiphiles in drug delivery and biomedical research. Adv Drug Deliv Rev 47(2–3):209–228CrossRefPubMedGoogle Scholar
  19. 19.
    Barnett BP, Ruiz-Cabello J, Hota P, Ouwerkerk R, Shamblott MJ, Lauzon C et al (2011) Use of perfluorocarbon nanoparticles for non-invasive multimodal cell tracking of human pancreatic islets. Contrast Media Mol Imaging 6(4):251–259CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Ahrens ET, Zhong J (2013) In vivo MRI cell tracking using perfluorocarbon probes and fluorine-19 detection. NMR Biomed 26(7):860–871CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Janjic JM, Ahrens ET (2009) Fluorine-containing nanoemulsions for MRI cell tracking. Wiley Interdiscip Rev Nanomed Nanobiotechnol 1(5):492–501CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Keipert PE, Otto S, Flaim SF, Weers JG, Schutt EA, Pelura TJ et al (1994) Influence of perflubron emulsion particle size on blood half-life and febrile response in rats. Artif Cells Blood Substit Immobil Biotechnol 22(4):1169–1174CrossRefPubMedGoogle Scholar
  23. 23.
    Li Z, Barnes JC, Bosoy A, Stoddart JF, Zink JI (2012) Mesoporous silica nanoparticles in biomedical applications. Chem Soc Rev 41(7):2590–2605CrossRefPubMedGoogle Scholar
  24. 24.
    Nakamura T, Sugihara F, Matsushita H, Yoshioka Y, Mizukami S, Kikuchi K (2015) Mesoporous silica nanoparticles for 19F magnetic resonance imaging, fluorescence imaging, and drug delivery. Chem Sci 6:1986–1990CrossRefPubMedGoogle Scholar
  25. 25.
    Ye F, Laurent S, Fornara A, Astolfi L, Qin J, Roch A et al (2008) Uniform mesoporous silica coated iron oxide nanoparticles as a highly efficient, nontoxic MRI T(2) contrast agent with tunable proton relaxivities. Contrast Media Mol Imaging 7(5):460–468CrossRefGoogle Scholar
  26. 26.
    Hsiao J-K, Tsai C-P, Chung T-H, Hung Y, Yao M, Liu H-M et al (2008) Mesoporous silica nanoparticles as a delivery system of gadolinium for effective human stem cell tracking. Small 4(9):1445–1452CrossRefPubMedGoogle Scholar
  27. 27.
    Vernikouskaya I, Pochert A, Linden M, Rasche V (2015) Perfluoro-15-crown-5-ether-loaded hollow mesoporous silica spheres for 19F in vivo MRI. In: Proceedings of the 23th scientific meeting, International Society for Magnetic Resonance in medicine, Toronto, 1902Google Scholar
  28. 28.
    Pochert A, Vernikouskaya I, Pascher F, Rasche V, Lindén M (2017) Cargo-influences on the biodistribution of hollow mesoporous silica nanoparticles as studied by quantitative 19F-magnetic resonance imaging. J Colloid Interface Sci 488:1–9CrossRefPubMedGoogle Scholar
  29. 29.
    Jiru F, Klose U (2006) Fast 3D radiofrequency field mapping using echo-planar imaging. Magn Reson Med 56(6):1375–1379CrossRefPubMedGoogle Scholar
  30. 30.
    Insko EK, Bolinger L (1993) Mapping of the radiofrequency field. J Magn Reson Ser A 103(1):82–85CrossRefGoogle Scholar
  31. 31.
    Yarnykh VL (2007) Actual flip-angle imaging in the pulsed steady state: a method for rapid three-dimensional mapping of the transmitted radiofrequency field. Magn Reson Med 57(1):192–200CrossRefPubMedGoogle Scholar
  32. 32.
    Dowell NG, Tofts PS (2007) Fast, accurate, and precise mapping of the RF field in vivo using the 180 degrees signal null. Magn Reson Med 58(3):622–630CrossRefPubMedGoogle Scholar
  33. 33.
    Sacolick LI, Wiesinger F, Hancu I, Vogel MW (2010) B1 mapping by Bloch-Siegert shift. Magn Reson Med 63(5):1315–1322CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Sung K, Saranathan M, Daniel BL, Hargreaves BA (2013) Simultaneous T(1) and B(1) (+) mapping using reference region variable flip angle imaging. Magn Reson Med 70(4):954–961CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Brookes JA, Redpath TW, Gilbert FJ, Murray AD, Staff RT (1999) Accuracy of T1 measurement in dynamic contrast-enhanced breast MRI using two- and three-dimensional variable flip angle fast low-angle shot. J Magn Reson Imaging 9(2):163–171CrossRefPubMedGoogle Scholar
  36. 36.
    Gupta S, Schmidt E, Mulkern R, Fedorov A, Hancu I, Zhu Y, et al (2012) A method for correcting T1 maps of prostate at 3T obtained by variable flip angle imaging. In: Proceedings of the 20th scientific meeting, International Society for Magnetic Resonance in medicine, Melbourne, 1962Google Scholar
  37. 37.
    Ma J (2004) Breath-hold water and fat imaging using a dual-echo two-point Dixon technique with an efficient and robust phase-correction algorithm. Magn Reson Med 52(2):415–419CrossRefPubMedGoogle Scholar
  38. 38.
    Kuhl CK, Kooijman H, Gieseke J, Schild HH (2007) Effect of B1 inhomogeneity on breast MR imaging at 3.0 T. Radiology 244(3):929–930CrossRefPubMedGoogle Scholar
  39. 39.
    Sung K, Daniel BL, Hargreaves BA (2013) Transmit B1 + field inhomogeneity and T1 estimation errors in breast DCE-MRI at 3 tesla. J Magn Reson Imaging 38(2):454–459CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Collins CM, Yang QX, Wang JH, Zhang X, Liu H, Michaeli S et al (2002) Different excitation and reception distributions with a single-loop transmit-receive surface coil near a head-sized spherical phantom at 300 MHz. Magn Reson Med 47(5):1026–1028CrossRefPubMedGoogle Scholar
  41. 41.
    Hoult DI (2000) The principle of reciprocity in signal strength calculations—a mathematical guide. Concepts Magn Reson 12(4):173–187CrossRefGoogle Scholar
  42. 42.
    Glover GH, Hayes CE, Pelc NJ, Edelstein WA, Mueller OM, Hart HR et al (1985) Comparison of linear and circular polarization for magnetic resonance imaging. J Magn Reson 64(2):255–270Google Scholar
  43. 43.
    Kellman P, Hansen MS (2014) T1-mapping in the heart: accuracy and precision. J Cardiovasc Magn Reson 16(1):2.  https://doi.org/10.1186/1532-429X-16-2 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Vernikouskaya I (2015) Qualitative and quantitative assessment of the local contrast agent aggregations using MRI, Dissertation, Ulm University. https://oparu.uni-ulm.de/xmlui/handle/123456789/3718. Accessed 10 July 2018
  45. 45.
    Kadayakkara DK, Damodaran K, Hitchens TK, Bulte JW, Ahrens ET (2014) (19)F spin-lattice relaxation of perfluoropolyethers: dependence on temperature and magnetic field strength (7.0-14.1T. J Magn Reson 242:18–22CrossRefPubMedGoogle Scholar
  46. 46.
    Ji Y, Waiczies H, Winter L, Neumanova P, Hofmann D, Rieger J et al (2015) Eight-channel transceiver RF coil array tailored for 1H/19F MR of the human knee and fluorinated drugs at 7.0 T. NMR Biomed 28(6):726–737CrossRefPubMedGoogle Scholar
  47. 47.
    Zhong J, Sakaki M, Okada H, Ahrens ET (2013) In vivo intracellular oxygen dynamics in murine brain glioma and immunotherapeutic response of cytotoxic T cells observed by fluorine-19 magnetic resonance imaging. PLoS One 8(5):e59479CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Colotti R, Bastiaansen JAM, Wilson A, Flögel U, Gonzales C, Schwitter J et al (2017) Characterization of perfluorocarbon relaxation times and their influence on the optimization of fluorine-19 MRI at 3 tesla. Magn Reson Med 77(6):2263–2271CrossRefPubMedGoogle Scholar
  49. 49.
    Fox MS, Gaudet JM, Foster PJ (2016) Fluorine-19 MRI contrast agents for cell tracking and lung imaging. Magn Reson Insights 8(Suppl 1):53–67PubMedPubMedCentralGoogle Scholar
  50. 50.
    Partlow KC, Chen J, Brant JA, Neubauer AM, Meyerrose TE, Creer MH et al (2007) 19F magnetic resonance imaging for stem/progenitor cell tracking with multiple unique perfluorocarbon nanobeacons. FASEB J 21(8):1647–1654CrossRefPubMedGoogle Scholar
  51. 51.
    Ruiz-Cabello J, Walczak P, Kedziorek DA, Chacko VP, Schmieder AH, Wickline SA et al (2008) In vivo “hot spot” MR imaging of neural stem cells using fluorinated nanoparticles. Magn Reson Med 60(6):1506–1511CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Yu T, Hubbard D, Ray A, Ghandehari H (2012) In vivo biodistribution and pharmacokinetics of silica nanoparticles as a function of geometry, porosity and surface characteristics. J Control Release 163(1):46–54CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Xie G, Sun J, Zhong G, Shi L, Zhang D (2010) Biodistribution and toxicity of intravenously administered silica nanoparticles in mice. Arch Toxicol 84(3):183–190CrossRefPubMedGoogle Scholar
  54. 54.
    Huang X, Li L, Liu T, Hao N, Liu H, Chen D et al (2011) The shape effect of mesoporous silica nanoparticles on biodistribution, clearance, and biocompatibility in vivo. ACS Nano 5(7):5390–5399CrossRefPubMedGoogle Scholar
  55. 55.
    Miller L, Winter G, Baur B, Witulla B, Solbach C, Reske S et al (2014) Synthesis, characterization, and biodistribution of multiple 89Zr-labeled pore-expanded mesoporous silica nanoparticles for PET. Nanoscale 6(9):4928–4935CrossRefPubMedGoogle Scholar
  56. 56.
    Matsushita H, Mizukami S, Sugihara F, Nakanishi Y, Yoshioka Y, Kikuchi K (2014) Multifunctional core-shell silica nanoparticles for highly sensitive 19F magnetic resonance imaging. Angew Chem Int Ed 53(4):1008–1011CrossRefGoogle Scholar
  57. 57.
    von Eckardstein A, Nofer JR, Assmann G (2001) High density lipoproteins and arteriosclerosis. Role of cholesterol efflux and reverse cholesterol transport. Arterioscler Thromb Vasc Biol 21(1):13–27CrossRefGoogle Scholar
  58. 58.
    Rosenholm J, Meinander A, Peuhu E, Niemi R, Eriksson J, Sahlgren C et al (2009) Targeting of porous hybrid silica nanoparticles to cancer cells. ACS Nano 3(1):197–206CrossRefPubMedGoogle Scholar
  59. 59.
    Pochert A, Stiller D, Rasche V, Linden M (2013) Hollow mesoporous silica spheres as 19F-MRI imaging agents. In: Proceedings of the 6th World Molecular Imaging Congress, Savannah, LBAP 012Google Scholar

Copyright information

© European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) 2018

Authors and Affiliations

  1. 1.Department of Internal Medicine IIUlm University Medical CenterUlmGermany
  2. 2.Small Animal MRIUlm UniversityUlmGermany
  3. 3.Inorganic Chemistry IIUlm UniversityUlmGermany

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