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Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in Rats

Abstract

Purpose

Rats are important preclinical models for studying breast cancer metastasis and bone pathologies. In these research areas, fluorescence molecular tomography (FMT) is commonly applied for quantitative three-dimensional (3D) imaging in mice. However, uncertainties due to strong depth dependency of FMT signal and spatial resolution require a validation study in rats.

Procedure

FMT performance in rats was assessed based on co-registered FMT/micro-computed tomography (micro-CT) reconstructed volumes obtained from optical phantoms and from models relevant for tumor imaging, bone remodeling and biodistribution analysis of nanoparticles.

Results

FMT reconstructions within 20-mm-thick optical phantoms were accurate (95 ± 11 % recovery), precise (CV ≤ 8 %) and linear (R 2 > 0.9788) over a range of 78–2,500 nM of the near infrared fluorescent agent VivoTag 750 (VT750). In vivo, implanted defined fluorescent targets yielded a recovery of 105 ± 5 % and successfully co-registered with micro-CT delineated structures. Additionally, using the bone-targeting imaging agent Osteosense 750, regions of neo bone formation identified by FMT could be mapped to the region of epiphyseal growth plates observed in micro-CT images. Finally, as a proof of concept, to monitor nanoparticulate drug pharmacokinetics in rat subjects the accumulation/clearance of VT750–albumin conjugate in/from the liver was followed at 11 different time points over a period of 2 weeks by FMT/micro-CT.

Conclusions

FMT imaging has been validated in optical phantoms as well as in 160 g rats, and sequential FMT/micro-CT imaging can be considered as a useful tool for preclinical research in rats.

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References

  1. 1.

    Nahrendorf M, Waterman P, Thurber G et al (2009) Hybrid in vivo FMT-CT imaging of protease activity in atherosclerosis with customized nanosensors. Arterioscl Thromb Vasc 29:1444–1451

    CAS  Article  Google Scholar 

  2. 2.

    Leblond F, Tichauer KM, Holt RW et al (2011) Toward whole-body optical imaging of rats using single-photon counting fluorescence tomography. Opt Lett 36:3723–3725

    PubMed Central  PubMed  Article  Google Scholar 

  3. 3.

    Jöbsis F (1977) Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science 198:1264–1267

    PubMed  Article  Google Scholar 

  4. 4.

    Graves EE, Ripoll J, Weissleder R, Ntziachristos V (2003) A submillimeter resolution fluorescence molecular imaging system for small animal imaging. Med Phys 30:901–911

    CAS  PubMed  Article  Google Scholar 

  5. 5.

    Zhang G, Liu F, Zhang B et al (2013) Imaging of pharmacokinetic rates of indocyanine green in mouse liver with a hybrid fluorescence molecular tomography/X-ray computed tomography system. J Biomed Opt 18:040505. doi:10.1117/1.JBO.18.4.040505

    PubMed  Article  Google Scholar 

  6. 6.

    Zilberman Y, Kallai I, Gafni Y et al (2008) Fluorescence molecular tomography enables in vivo visualization and quantification of nonunion fracture repair induced by genetically engineered mesenchymal stem cells. J Orthop Res 26:522–530

    CAS  PubMed  Article  Google Scholar 

  7. 7.

    Kozloff KM, Quinti L, Patntirapong S et al (2009) Non-invasive optical detection of cathepsin K-mediated fluorescence reveals osteoclast activity in vitro and in vivo. Bone 44:190–198

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  8. 8.

    Zaheer A, Lenkinski RE, Mahmood A et al (2001) In vivo near-infrared fluorescence imaging of osteoblastic activity. Nat Biotechnol 19:1148–1154

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Haller J, Hyde D, Deliolanis N et al (2008) Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging. J Appl Physiol 104:795–802

    CAS  PubMed  Article  Google Scholar 

  10. 10.

    Kossodo S, Zhang J, Groves K et al (2011) Noninvasive in vivo quantification of neutrophil elastase activity in acute experimental mouse lung injury. Int J Mol Imaging 2011:581406

    PubMed Central  PubMed  Article  Google Scholar 

  11. 11.

    Weissleder R, Tung CH, Mahmood U, Bodanov AJ (1999) In-vivo imaging of tumors with protease activated near-infrared fluorescent probes. Nat Biotechnol 17:375–378

    CAS  PubMed  Article  Google Scholar 

  12. 12.

    Kossodo S, Pickarski M, Lin S-A et al (2010) Dual in vivo quantification of integrin-targeted and protease-activated agents in cancer using fluorescence molecular tomography (FMT). Mol Imaging Biol 12:488–499

    PubMed  Article  Google Scholar 

  13. 13.

    Ackermann M, Carvajal IM, Morse BA et al (2011) Adnectin CT-322 inhibits tumor growth and affects microvascular architecture and function in Colo205 tumor xenografts. Int J Oncol 38:71–80

    CAS  PubMed  Google Scholar 

  14. 14.

    Weissleder R, Ntziachristos V (2003) Shedding light onto live molecular targets. Nat Med 9:123–128

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Hainfeld JF, Slatkin DN, Focella TM, Smilowitz HM (2006) Gold nanoparticles: a new X-ray contrast agent. Br J Radiol 79:248–253

    CAS  PubMed  Article  Google Scholar 

  16. 16.

    Almajdub M, Nejjari M, Poncet G et al (2007) In-vivo high-resolution X-ray microtomography for liver and spleen tumor assessment in mice. Contrast Media Mol I 2:88–93

    CAS  Article  Google Scholar 

  17. 17.

    Boll H, Nittka S, Doyon F et al (2011) Micro-CT based experimental liver imaging using a nanoparticulate contrast agent: a longitudinal study in mice. PloS One 6:e25692. doi:10.1371/journal.pone.0025692

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  18. 18.

    Histing T, Garcia P, Holstein JH et al (2011) Small animal bone healing models: standards, tips, and pitfalls results of a consensus meeting. Bone 49:591–599

    CAS  PubMed  Article  Google Scholar 

  19. 19.

    Blouin S, Baslé MF, Chappard D (2005) Rat models of bone metastases. Clin Exp Metastasis 22:605–614

    PubMed  Article  Google Scholar 

  20. 20.

    Sharma V, McNeill JH (2009) To scale or not to scale: the principles of dose extrapolation. Br J Pharmacol 157:907–921

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  21. 21.

    Iannaccone PM, Jacob HJ (2009) Rats! Dis Model Mech 2:206–210

    PubMed Central  PubMed  Article  Google Scholar 

  22. 22.

    Cubeddu R, Pifferi A, Taroni P et al (1997) A Solid Phantom for Photon Migration Studies. Phys Med Biol 42:1971–1979

    CAS  PubMed  Article  Google Scholar 

  23. 23.

    Tiwari G, Tiwari R (2010) Bioanalytical method validation: An updated review. Pharm Meth 1:25–38

    Article  Google Scholar 

  24. 24.

    Vasquez KO, Casavant C, Peterson JD (2011) Quantitative whole body biodistribution of fluorescent-labeled agents by non-invasive tomographic imaging. PloS One 6:e20594. doi:10.1371/journal.pone.0020594

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  25. 25.

    Loening AM, Gambhir SS (2003) AMIDE: a free software tool for multimodality medical image analysis. Mol Imaging 2:131–137

    PubMed  Article  Google Scholar 

  26. 26.

    Stricker D (2008) BrightStat.com: free statistics online. Comput Meth Prog Bio 92:135–143

    Article  Google Scholar 

  27. 27.

    Ale A, Ermolayev V, Herzog E et al (2012) FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography. Nat Methods 9:615–620

    CAS  PubMed  Article  Google Scholar 

  28. 28.

    Martin EA, Ritman EL, Turner RT (2003) Time course of epiphyseal growth plate fusion in rat tibiae. Bone 32:261–267

    CAS  PubMed  Article  Google Scholar 

  29. 29.

    Barbour RL, Graber HL, Chang JCJ et al (1995) MRI-guided optical tomography: prospects and computation for a new imaging method. IEEE Comput Sci Eng 2:63–77

    Article  Google Scholar 

  30. 30.

    Kunjachan S, Gremse F, Theek B et al (2013) Noninvasive Optical Imaging of Nanomedicine Biodistribution. ACS Nano 7:252–262

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  31. 31.

    Swirski FK, Berger CR, Figueiredo J-L et al (2007) A near-infrared cell tracker reagent for multiscopic in vivo imaging and quantification of leukocyte immune responses. PloS One 2:e1075. doi:10.1371/journal.pone.0001075

    PubMed Central  PubMed  Article  Google Scholar 

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Acknowledgments

The authors would like to thank Dr. Sasha Belenkov and Dr. Wael Yared from Perkin-Elmer (ViSen) for providing valuable suggestions with respect to FMT operations and software. The assistance of Harald Bartolomae and Alex Rossel in the setup of the imaging equipment is appreciated. The authors also wish to thank Markus Heneka from MicroAnalytics, Germany for assistance with micro-CT related issues. This work was supported by the Excellence Initiative of the German Federal and State Governments Grant EXC 294 and in part by the 5th INTERREG Upper Rhine Program (project A21: Nano@MATRIX).

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Correspondence to V. Prasad Shastri.

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Vonwil, D., Christensen, J., Fischer, S. et al. Validation of Fluorescence Molecular Tomography/Micro-CT Multimodal Imaging In Vivo in Rats. Mol Imaging Biol 16, 350–361 (2014). https://doi.org/10.1007/s11307-013-0698-8

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Key words

  • Image co-registration
  • Nanomaterials
  • Nanomedicine
  • Bone remodeling
  • Biodistribution