This presentation will describe the methods and applications for fluorine-19 based cell tracking with MRI. 19F MRI has emerged as a promising tool for in vivo cell tracking because it addresses some of the shortcomings of, the more widely used, iron-based cell tracking. Specifically, direct quantification of cell number and issues related to low specificity. The main limitation of 19F cell tracking is sensitivity. Current detection limits on preclinical imaging systems is thousands of cells/voxel. 19F cell tracking has been applied to the detection and quantification of therapeutic immune cells in cancer patients. Strategies for improving cell detection by 19F MRI will be discussed.
Cellular MRI combines the ability to obtain high-resolution MRI data with the use of magnetic contrast agents for labeling specific cells, thereby enhancing their detectability. The most widely used cell labeling agents for cell tracking are magnetite (Fe3O4)-based SPIONs. The presence of SPIONs in cells causes a distortion in the magnetic field and leads to abnormal signal hypo-intensities in iron-sensitive images; T2- and T2*-weighted images are most often used (1). Areas containing SPION-labeled cells therefore appear as regions of low signal intensity (signal voids) on MRI images, creating negative contrast. A variety of cell types including mesenchymal stem cells,(2,3) progenitor cells,(4) T-lymphocytes,(5) dendritic cells,(6-10) pancreatic islets,(11,12) cancer cells,(13-16) and hepatocytes (17) have been pre-labeled with SPION and tracked with MRI. This technique is highly sensitive, permitting the imaging of single cells in vivo, under ideal conditions (18).
There are, however, some significant limitations of iron-based MRI cell tracking. The first is low specificity due to other low-signal regions in T2/T2* images; i.e. SPION-labeled cells (black) in the lung (also black) or in a region of hemorrhage (black) cannot be detected. Although ultra-short echo time imaging methods have been developed for producing positive contrast from iron-labeled cells these too have similar problems with specificity. Second, quantification of iron-induced signal loss is complicated. Our group and others have shown that the degree of signal loss produced by SPION-labeled cells is only linear at low iron concentrations. Typically the degree of contrast (how black is it) or the volume of signal loss (how big a void is there) is measured from these images.
Fluorine-19 (19F) MRI with perfluorocarbon (PFC) nanoemulsions to label cells has emerged as a promising method for in vivo cell tracking (19,20). 19F cell tracking addresses some of the limitations associated with iron-based cell tracking. First, the 19F signal is specific since endogenous 19F is so low that there is not any appreciable tissue background signal. 19F images look similar to PET tracer images. Second, in contrast to the indirect visualization of SPIONs by observed proton signal loss, the spins of 19F nuclei are directly detected and image contrast is proportional to the number of 19F nuclei per voxel. Cell number can be determined if a measurement of 19F nuclei/cell is obtained by NMR spectroscopy; the 19F signal intensity for the cells of interest is compared to the 19F signal intensity of a reference tube containing a known 19F concentration and the NMR calibration value (21). However, a limitation of 19F cell tracking is low sensitivity; thousands of labeled cells per voxel are required. Fluorine sensitivity improves with higher field strengths and preclinical studies have reported in vivo detection of as few as 5000 cells per voxel (22). The first human clinical trial at 3 Tesla (T) demonstrated a cellular detection limit between 1 and 10 million cells (23). Further improvements in MR hardware and pulse sequences should lead to increased sensitivity for cell detection (24).
This presentation will review the methodology for cell tracking with 19F MRI including cell labeling, image acquisition and quantification. 19F-based cell tracking will be compared with iron-based cell tracking. A variety of applications for 19F-based cell tracking will be discussed. Methods to address the shortcomings of 19F-based cell tracking will be described.
Canadian Institutes for Health Research
Robarts Cellular and Molecular Imaging Group @RobartsCMIGroup
Past Trainees: Drs. Ashley Makela, Jeff Gaudet, Matthew Fox and Emeline Ribot
1. Makela A, Murrell DH, Parkins K, Kara J, Gaudet J, Foster PJ. “Cellular Imaging with MRI.” Invited Paper. Topics in Magnetic Resonance Imaging, 25:177-186, October, 2016. PMID: 27748707
2. Gonzalez-Lara LE, Xu X, Hofstetrova K, Pniak A, Chen Y, McFadden CD, Martinez-Santiesteban FM, Rutt BK, Brown A, Foster PJ. The Use of Cellular Magnetic Resonance Imaging to Track the Fate of Iron-Labeled Multipotent Stromal Cells after Direct Transplantation in a Mouse Model of Spinal Cord Injury. Mol Imaging Biol. 2010 Aug 5.
3. Sykova E, Jendelova P. In vivo tracking of stem cells in brain and spinal cord injury. Prog Brain Res. 2007 161:367-83.
4. Hinds KA, Hill JM, Shapiro EM, Laukkanen MO, Silva AC, Combs CA, Varney TR, Balaban RS, Koretsky AP, Dunbar CE. Highly efficient endosomal labeling of progenitor and stem cells with large magnetic particles allows magnetic resonance imaging of single cells. Blood 2003 102: 867-872. 4.
5.Tremblay ML, Davis C, Bowen CV, Stanley O, Parsons C, Weir G, Karkada M, Stanford MM, Brewer KD. Usi ng MRI cell tracking to monitor immune cell recruitment in response to a peptide-based cancer vaccine. Magn Reson Med. 2018 Jul;80(1):304-316. doi: 10.1002/mrm.27018.
6. Zhang X, de Chickera SN, Willert C, Economopoulos V, Noad J, Rohani R, Wang AY, Levings MK, Scheid E, Foley R, Foster PJ, Dekaban GA. Cellular magnetic resonance imaging of monocyte-derived dendritic cell migration from healthy donors and cancer patients as assessed in a scid mouse model. Cytotherapy. 2011 13(10):1234-48.
7. de Chickera S, Willert C, Mallet C, Foley R, Foster P, Dekaban GA. Cellular MRI as a suitable, sensitive non-invasive modality for correlating in vivo migratory efficiencies of different dendritic cell populations with subsequent immunological outcomes. Int Immunol. 2012 24(1):29-41. 7.
8. Rohani R, de Chickera SN, Willert C, Chen Y, Dekaban GA and Foster PJ. In Vivo Cellular MRI of Dendritic Cell Migration using Micrometer-sized Iron Oxide (MPIO) Particles. Mol Imaging & Biol 13(4): 679-694, 2011.
9. Dekaban G, Hamilton A, Fink C, Au B, de Chickera D, Ribot E, Foster PJ. “Tracking and Evaluation of Dendritic Cell Migration by Cellular Magnetic Resonance Imaging.” WIREs Nanomedicine & Nanobiotechnology 5(5):469-8, September 2013. doi: 10.1002/wnan.1227
10. de Chickera SN, Snir J, Willert C, Rohani R, Foley R, Foster PJ, Dekaban GA. “Labelling Dendritic Cells with SPIO has Implications for their Subsequent in Vivo Migration as Assessed with Cellular MRI.” Contrast Media and Molecular Imaging 6(4): 314-327, August 2011.
11. Jirak D, Kriz J, Strzelecki M, Yang J, Hasilo C, White DJ, Foster PJ. Monitoring the survival of islet transplants by MRI using a novel technique for their automated detection and quantification. MAGMA. 2009 22(4):257-65.
12. Ping Wang, Christian Schuetz, Prashanth Vallabhajosyula, Zdravka Medarova, Aseda Tena, Lingling Wei, Kazuhiko Yamada, Shaoping Deng, James F. Markmann, David H. Sachs, Anna Moore. Monitoring of allogeneic islet grafts in nonhuman primates using magnetic resonance imaging. Transplantation. 2015 Aug; 99(8): 1574–1581.
13. Heyn C, Ronald JA, Ramadan SS, Snir JA, Barry AM, MacKenzie LT, Mikulis DJ, Palmieri D, Bronder JL, Steeg PS, et al. In vivo MRI of cancer cell fate at the single-cell level in a mouse model of breast cancer metastasis to the brain. Magn Reson Med. 2006 56: 1001-1010.
14. Murrell DH, Zarghami N, Jensen MD, Dickson F, Chambers AF, Wong E, Foster PJ. “MRI surveillance of cancer cell fate in a brain metastasis model after early radiotherapy.”Magn Reson Med 78(4):1506-1512, October 2017.
15. Townson JL, Ramadan SS, Simedrea C, Rutt BK, MacDonald IC, Foster PJ, Chambers AF. Three-dimensional imaging and quantification of both solitary cells and metastases in whole mouse liver by magnetic resonance imaging. Cancer Res. 2009 69(21):8326-31.
16. Economopoulos V, Chen Y, McFadden C, Foster PJ. “MRI Detection of Nonproliferative Tumor Cells in Lymph Node Metastases Using Iron Oxide Particles in a Mouse Model of Breast Cancer.” Translational Oncology 6(3):347-54, June 2017 16.
17. Roach DR, Garrett WM, Welch G, Caperna TJ, Talbot NC,Shapiro EM. Magnetic cell labeling of primary and stem cell-derived pig hepatocytes for MRI-based cell tracking of hepatocyte transplantation. PLoS One. 2015 Apr 9;10(4):e0123282. doi: 10.1371/journal.pone.0123282.
18. Heyn C, Ronald JA, Mackenzie LT, MacDonald IC, Chambers AF, Rutt BK, and Foster PJ. In vivo magnetic resonance imaging of single cells in mouse brain with optical validation. Magn Reson Med. 2006; 55: 23-29.
19. Fox, MS, Gaudet, JM, Foster PJ. “Fluorine-19: Versatile MRI Contrast Agents for Imaging Micro and Macro-biological Environments.” Magnetic Resonance Insights. 22:8 (Suppl 1):53-67, March 2016.
20. Mangala Srinivas, Arend Heerschap, Eric T. Ahrens, Carl G. Figdor, I. Jolanda M. de Vries. 19F MRI for quantitative in vivo cell tracking. Trends Biotechnol. 2010 Jul; 28(7): 363–370.
21. Ahrens ET, Flores R, Xu H, Morel PA. In vivo imaging platform for tracking immunotherapeutic cells. Nat Biotechnol 2005;23(8):983–987.
22. Bulte JW, Walczak P, Janowski M, et al. Quantitative “hot spot” imaging of transplanted stem cells using superparamagnetic tracers and magnetic particle imaging (MPI). Tomography 2015;1(2):91–97.
23. Ahrens ET, Helfer BM, O’Hanlon CF, Schirda C. Clinical cell therapy imaging using a perfluorocarbon tracer and fluorine-19 MRI. Magn Reson Med 2014;72(6):1696–1701.
24. Fink C, Gaudet JM, Fox MS, Bhatt S, Viswanathan S, Smith M, Chin J, Foster PJ, Dekaban GA. “19F- perfluorocarbon-labeled Human Peripheral Blood Mononuclear Cells Can be Detected In Vivo Using Clinical MRI Parameters in a Therapeutic Cell Setting.” Scientific Reports 8(1):590, January 2018. PMID: 29330541.