Skip to main content

Small Animal Imaging in Oncology Drug Development

  • Chapter
  • First Online:

Abstract

Major advances in small animal imaging have been made during the last two decades encompassing a full array of platforms that image along the electromagnetic spectrum from MRI (100–101 m), optical (10−6 m), X-ray (10−9 m), to nuclear (10−11–10−12 m). This in part has been facilitated by the National Cancer Institute (NCI), National Institutes of Health (NIH) through the support of Small Animal Imaging Research Programs (SAIRP), and other initiatives to increase the availability of small animal imaging platforms and develop the expertise in the use of these methods. While the primary application of these new techniques has been research tools to answer scientific questions especially related to the understanding of in vivo systems, another area of interest has been the introduction of imaging-based in vivo assay systems for drug development in oncology. In fact, a major effort has been undertaken to integrate in vivo imaging biomarker development with in vitro biomarker development in contrast to the historical scenario of applying imaging only late in the development plan, leading to the conundrum of validation of imaging while trying to employ imaging as a biomarker.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: new estimates of R&D costs. J Health Econ. 2016;47:20–33. https://doi.org/10.1016/j.jhealeco.2016.01.012.

    Article  PubMed  Google Scholar 

  2. Thomas DW, Burns J, Audette J, Carroll A, et al. Clinical development success rates 2006–2015, BioIndustry analysis. http://www.amplion.com/clinical-development-success-rates?hsCtaTracking=7e38cfe3-248d-440b-a7e4-c038acfa6eb2%7Ca6180579-5624-4deb-ac76-35b512407bd1

  3. Vanhove C, Bankstahl JP, Krämer SD, Visser E, Belcari N, Vandenberghe S. Accurate molecular imaging of small animals taking into account animal models, handling, anesthesia, quality control and imaging system performance. EJNMMI Phys. 2015;2:31. https://doi.org/10.1186/s40658-015-0135-y.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kinahan P, Fletcher JW. PET/CT standardized uptake values (SUVs) in clinical practice and assessing response to therapy. Semin Ultrasound CT MR. 2010;31(6):496–505. https://doi.org/10.1053/j.sult.2010.10.001.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sha W, Ye H, Iwamoto KS, Wong K-P, Wilks MQ, Stout D, McBride W, Huang S-C. Factors affecting tumor 18F-FDG uptake in longitudinal mouse PET studies. EJNMMI Res. 2013;3:51. https://doi.org/10.1186/2191-219X-3-51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Adiseshaiah PP, Patel NL, Ileva LV, Kalen JD, Haines DC, McNeil SE. Longitudinal imaging of cancer cell metastasis in two preclinical models: a correlation of noninvasive imaging to histopathology. Int J Molecul Imaging. 2014;2014:102702. https://doi.org/10.1155/2014/102702.

    Article  CAS  Google Scholar 

  7. Fuchs K, Kukuk D, Mahling M, Quintanilla-Martinez L, Reischl G, Reutershan J, Lang F, Rocken M, Pichler BJ, Kneilling M. Impact of anesthetics on 3′-[18F]fluoro-3′-deoxythymidine ([18F]FLT) uptake in animal models of cancer and inflammation. Mol Imaging. 2013:1–11. https://doi.org/10.2310/7290.2012.00042.

    Article  Google Scholar 

  8. Maier FC, Kneilling M, Reischl G, Cay F, Bukala D, Schmid A, Judenhofer MS, Röcken M, Machulla H-J, Pichler BJ. Significant impact of different oxygen breathing conditions on noninvasive in vivo tumor-hypoxia imaging using [18F]-fluoro-azomycinarabino- furanoside ([18F]FAZA). Radiat Oncol. 2011;6:165. https://doi.org/10.1186/1748-717X-6-165.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Fueger BJ, Czernin J, Hildebrandt I, Tran C, Halpern BS, Stout D, Phelps ME, Weber WA. Impact of animal handling on the results of 18F-FDG PET studies in mice. J Nucl Med. 2006;47(6):999–1006.

    CAS  PubMed  Google Scholar 

  10. Fuchs K, Kukuk D, Reischl G, Foller M, Eichner M, Reutershan J, Lang F, Rocken M, Pichler BJ, Kneilling M. Oxygen breathing affects 3′-deoxy-3’-18F-fluorothymidine uptake in mouse models of arthritis and cancer. J Nucl Med. 2012;53:823–30. https://doi.org/10.2967/jnumed.111.101808.

    Article  CAS  PubMed  Google Scholar 

  11. Hildebrandt IJ, Helen S, Weber WA. Anesthesia and other considerations for in vivo imaging of small animals. ILAR. 2008;49(1):17–26. https://doi.org/10.1093/ilar.49.1.17.

    Article  CAS  Google Scholar 

  12. Ileva LV, Bernardo M, Patel NL, Riffle LA, Graff-Cherry C, Robinson C, Difilippantonio S, Kalen JD. Challenges in performing preclinical imaging in a large cohort therapeutic efficacy study of murine cancer models. 64th AALAS National Meeting, Baltimore, MD, October 29, 2013.

    Google Scholar 

  13. Honndorf VS, Schmidt H, Wehrl HF, Wiehr S, Ehrlichmann W, Quintanilla-Martinez L, Barjat H, Ricketts S-A, Pichler BJ. Quantitative correlation at the molecular level of tumor response to docetaxel by multimodal diffusion-weighted magnetic resonance imaging and [18F]FDG/[18F]FLT positron emission tomography. Mol Imaging. 2014;(1) https://doi.org/10.2310/7290.2014.00045.

    Article  Google Scholar 

  14. Yang H, Wang H, Shivalila CS, Cheng AW, Shi L, Jaenisch R. One-step generation of mice carrying reporter and conditional alleles by CRISPR/cas-mediated genome engineering. Cell. 2013;154(6):1370–9. https://doi.org/10.1016/2013.08.022.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. The Jackson Laboratory, Bar Harbor, ME USA, https://www.jax.org/.

  16. Tentler JJ, Tan AC, Weekes CD, Jimeno A, Leong S, Pitts TM, Arcaroli JJ, Messersmith WA, Gail Eckhardt S. Patient-derived tumor xenografts as models for oncology drug development. Nat Rev Clin Oncol. 2012;9:338–50. https://doi.org/10.1038/nrclinonc.2012.61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Elmore S. Apoptosis: a review of programmed cell death. Toxicol Pathol. 2007;35(4):495–516.

    Article  CAS  Google Scholar 

  18. Biological Testing Branch, Division of Cancer Diagnostics and Treatment, NCI, NIH: https://dtp.cancer.gov/organization/btb/default.htm

  19. Center for Advanced Preclinical Research, Center for Cancer Research, NCI, NIH: https://ccr.cancer.gov/capr

  20. van Marion DMS, et al. Studying cancer metastasis: Existing models, challenges and future perspectives. Crit Rev Oncol Hematol. 2015;97:107–17. https://doi.org/10.1016/j.critrevonc.2015.08.00.

    Article  PubMed  Google Scholar 

  21. Chaffer CL, Weinberg RA. A perspective on cancer cell metastasis. Science. 2011;331(6024):1559–64. https://doi.org/10.1126/science.1203543.

    Article  CAS  PubMed  Google Scholar 

  22. Troy T, Jekic-McMullen D, Sambucetti L, Rice B. Quantitative comparison of the sensitivity of detection of fluorescent and bioluminescence reporters in animal models. Mol Imaging. 2004;3(1):9–23.

    Article  CAS  Google Scholar 

  23. Siolas D, Honnon GJ. Patient-derived tumor xenografts: transforming clinical samples into mouse models. Cancer Res. 2013;73(17):5315–9. https://doi.org/10.1158/0008-5472.CAN-13-1069.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Cassidy JW, Caldas C, Bruna A. Maintaining tumor heterogeneity in patient-derived tumor xenografts. Cancer Res. 2015;75(15):2963–8. https://doi.org/10.1158/0008-5472.CAN-15-0727.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. American Cancer Society. Colorectal cancer. 2018.

    Google Scholar 

  26. Durkee BY, Weichert JP, Halberg RB. Small animal micro-CT colonography. Methods. 2010;50:36–41. https://doi.org/10.1016/j.ymeth.2009.07.008.

    Article  CAS  PubMed  Google Scholar 

  27. Boll H, Bag S, Nölte IS, Wilhelm T, Kramer M, Groden C, Böcker U, Brockmann MA. Double-contrast micro-CT colonoscopy in live mice. Int J Color Dis. 2011;26:721–7. https://doi.org/10.1007/s00384-011-1181-0.

    Article  Google Scholar 

  28. Larsson AE, et al. Magnetic resonance imaging of experimental mouse colitis and association with inflammatory activity. Inflamm Bowel Dis. 2006;12:478–85.

    Article  Google Scholar 

  29. Herborn CU, et al. Dark lumen magnetic resonance colonography in a rodent polyp model: initial experience and demonstration of feasibility. Investig Radiol. 2004;39:723–7.

    Article  Google Scholar 

  30. Ileva LV, Bernardo M, Young MR, Riffle LA, Tatum JL, Kalen JD, Choyke PL. In vivo MRI virtual colonography in a mouse model of colon cancer. Nat Protoc. 2014;9(11):2682–92. https://doi.org/10.1038/nprot.2014.178.

    Article  PubMed  Google Scholar 

  31. Young MR, Ileva LV, Bernardo M, Riffle LA, Jones YL, Kim YS, Colburn NH, Choyke PL. Monitoring of tumor promotion and progression in a mouse model of inflammation-induced colon cancer with magnetic resonance colonography. Neoplasia. 2009;11(3):237–46. https://doi.org/10.1593/neo.81326.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Wu M, Rivkin A, Pham T. Panitumumab: human monoclonal antibody against the epidermal growth factor receptors for the treatment of metastatic colorectal cancer. Clin Ther. 2008;30:14–30. https://doi.org/10.1016/j.clinthera.2008.01.014.

    Article  CAS  PubMed  Google Scholar 

  33. Burgess AW. EGFR family: structure physiology signaling and therapeutic targets. Growth Factors. 2008;26:263–74. https://doi.org/10.1080/0897719080231284.

    Article  CAS  PubMed  Google Scholar 

  34. Ciardiello F, Tortora G. Anti-epidermal growth factor receptor drugs in cancer therapy. Expert Opin Investig Drugs. 2002;11:755–68. https://doi.org/10.1517/13543784.11.6.755.

    Article  CAS  PubMed  Google Scholar 

  35. Yang XD, Xia XC, Corvalan JR, Wang P, Davis CG. Development of ABX-EGF, a fully human anti-EGF receptor monoclonal antibody, for cancer therapy. Crit Rev Oncol Hematol. 2001;38:17–23. https://doi.org/10.1016/S1040-8428(00)00134-7.

    Article  CAS  PubMed  Google Scholar 

  36. Bhattacharyya S, Kurdziel K, Wei L, Riffle L, Kaur G, Hill GC, Jacobs PM, Tatum JL, Dorosho JH, Kalen JD. Zirconium-89 labeled panitumumab: a potential immuno-PET probe for HER1-expressing carcinomas. Nucl Med Biol. 2013;40:451–7. https://doi.org/10.1016/j.nucmedbio.2013.01.007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Bhattacharyya S, Patel NL, Wei L, Riffle LA, Kalen JD, Hill GC, Jacobs PM, Zinn KR, Rosenthal E. Synthesis and biological evaluation of panitumumab–IRDye800 conjugate as a fluorescence imaging probe for EGFR-expressing cancers. Med Chem Commum. 2014; https://doi.org/10.1039/c4md00116h.

    Article  CAS  Google Scholar 

  38. Faux SP, Houghton CE, Hubbard A, Pat- rick G. Increased expression of epidermal growth factor receptor in rat pleural mesothelial cells correlates with carcinogenicity of mineral fibres. Carcinogenesis. 2000;21(12):2275–80. https://doi.org/10.1093/carcin/21.12.2275.

    Article  CAS  PubMed  Google Scholar 

  39. Nayak TK, Bernardo M, Milenic DE, Choyke PL, Brechbiel MW. Orthotopic Pleural Mesothelioma in Mice: SPECT/CT and MRI Imaging with HER1-and HER2-targeted Radiolabeled Antibodies. Radiology. 2013;267:173–82. https://doi.org/10.1148/radiol.12121021.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Asselin M-C, O’Connor JPB, Boellaard R, Thacker NA, Jackson A. Quantifying heterogeneity in human tumours using MRI and PET. Eur J Cancer. 2012;48:447–55. https://doi.org/10.1016/j.ejca.2011.12.025.

    Article  PubMed  Google Scholar 

  41. Soares F, Janela F, Pereira M, Seabra J, Freire MM. 3D lacunarity in multifractal analysis of breast tumor lesions in dynamic contrast-enhanced magnetic resonance imaging. IEEE Trans Image Process. 2013;22(11):4422–35. https://doi.org/10.1109/TIP.2013.2273669.

    Article  PubMed  Google Scholar 

  42. Goh V, Sanghera B, Wellsted DM, Sundin J, Halligan S. Assessment of the spatial pattern of colorectal tumor perfusion estimated at perfusion CT using two-dimensional fractal analysis. Eur Radiol. 2009;19:1358–65. https://doi.org/10.1007/s00330-009-1304-y.

    Article  PubMed  Google Scholar 

  43. Dominietto M, Lehmann S, Keist R, Rudin M. Pattern analysis accounts for heterogeneity observed in MRI studies of tumor angiogenesis. Magn Reson Med. 2013;70:1481–90. https://doi.org/10.1002/mrm.24590.

    Article  CAS  PubMed  Google Scholar 

  44. Leijenaar RTH, Nalbantov G, Carvalho S, van Elmpt WJC, Troost EGC, Boellaard R, Aerts HJWL, Gillies RJ, Lambin P. The efect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis. Sci Rep. 2015;5:11075. https://doi.org/10.1038/srep11075.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Buvat I, Orlhac F, Soussan M. J Nucl Med. 2015;56(11):1642–4. https://doi.org/10.2967/jnumed.115.163469.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government Modified per federal agency (NIH).

Frederick National Laboratory for Cancer Research is accredited by AAALAC International and follows the Public Health Service Policy for the Care and Use of Laboratory Animals. Animal care was provided in accordance with the procedures outlined in the “Guide for Care and Use of Laboratory Animals” (National Research Council, 2011; National Academies Press, Washington, D.C.).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joseph D. Kalen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kalen, J.D., Tatum, J.L. (2019). Small Animal Imaging in Oncology Drug Development. In: Kuntner-Hannes, C., Haemisch, Y. (eds) Image Fusion in Preclinical Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-02973-9_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02973-9_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02972-2

  • Online ISBN: 978-3-030-02973-9

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics