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Multimodality Imaging in Small Animal Radiotherapy

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Image Fusion in Preclinical Applications

Abstract

For many decades, small animal radiation research was mostly performed using fairly crude experimental setups with radiation fields that did not conform to the desired target only. To enable more accurate irradiation in small animal research, recently, precision image-guided small animal radiation research platforms were developed. Similar to human planning systems, treatment planning on these micro-irradiators is based on computed tomography. However, in preclinical imaging, computed tomography is often hampered by low soft tissue contrast that makes it very challenging to localize targets in soft tissue regions. As a result, computed tomography on these radiation research platforms is more and more combined with other imaging modalities to improve target selection. These modalities include optical imaging, magnetic resonance imaging, and nuclear imaging techniques.

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References

  1. Malvezzi M, Carioli G, Bertuccio P, Boffetta P, Levi F, La Vecchia C, et al. European cancer mortality predictions for the year 2017, with focus on lung cancer. Ann Oncol [Internet]. 2017;28(5):1117–23. https://academic.oup.com/annonc/article-lookup/doi/10.1093/annonc/mdx033.

  2. Petrik V, Apok V, Britton JA, Bell BA, Papadopoulos MC. Godfrey Hounsfield and the dawn of computed tomography. Neurosurgery. 2006;58(4):780–7.

    Article  Google Scholar 

  3. Khan FM. The physics of radiation therapy. 4th ed. Philadelphia: Lippincott Williams and Wilkins; 2010. 531 p.

    Google Scholar 

  4. Aird EGA, Conway J. CT simulation for radiotherapy treatment planning. Br J Radiol. 2002;75(900):937–49.

    Article  CAS  Google Scholar 

  5. Baker GR. Localization: conventional and CT simulation. Br J Radiol. 2006;79(Spec. No. 1):S36–49.

    Article  Google Scholar 

  6. Hoffmann AL, Huizenga H, Kaanders JH. Employing the therapeutic operating characteristic (TOC) graph for individualised dose prescription. Radiat Oncol [Internet]. 2013;8(1):55. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3606307&tool=pmcentrez&rendertype=abstract.

  7. Bentzen SM, Gregoire V. Molecular imaging-based dose painting: a novel paradigm for radiation therapy prescription. Semin Radiat Oncol [Internet]. 2011;21(2):101–10. https://doi.org/10.1016/j.semradonc.2010.10.001.

    Article  Google Scholar 

  8. Diaz-Cano SJ. Tumor heterogeneity: mechanisms and bases for a reliable application of molecular marker design. Int J Mol Sci. 2012;13(2):1951–2011.

    Article  CAS  Google Scholar 

  9. Metz S, Ganter C, Lorenzen S, Van Marwick S, Holzapfel K, Herrmann K, et al. Multiparametric MR and PET imaging of intratumoral biological heterogeneity in patients with metastatic lung cancer using voxel-by-voxel analysis. PLoS One. 2015;10(7):1–14.

    Article  Google Scholar 

  10. Hamstra DA, Rice DJ, Anthony P, Oyedijo D, Ross BD, Rehemtulla A. Combined radiation and enzyme/prodrug treatment for head and neck cancer in an orthotopic animal model. Radiat Res. 1999;152(5):499–507.

    Article  CAS  Google Scholar 

  11. Verhaegen F, Granton P, Tryggestad E. Small animal radiotherapy research platforms. Phys Med Biol. 2011;56(12):R55–83.

    Article  Google Scholar 

  12. Butterworth KT, Prise KM, Verhaegen F. Small animal image-guided radiotherapy: status, considerations and potential for translational impact. Br J Radiol. 2015;88(1045):4–6.

    Article  Google Scholar 

  13. Siewerdsen JH, Moseley DJ, Bakhtiar B, Richard S, Jaffray DA. The influence of antiscatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors. Med Phys. 2004;31(12):3506–20.

    Article  CAS  Google Scholar 

  14. Bolcaen J, Descamps B, Deblaere K, Boterberg T, De Vos F, Kalala Okito J-P, et al. F18-fluoromethylcholine (FCho), F18-fluoroethyltyrosine (FET) and F18-fluorodeoxyglucose (FDG) for the discrimination between high-grade glioma (HGG) and radiation necrosis (RN): a μPET study. Soc Nucl Med Annu Meet Abstr [Internet]. 2014;55(Suppl. 1):1379. http://jnumedmtg.snmjournals.org/cgi/content/meeting_abstract/55/1_MeetingAbstracts/1379.

  15. Clarkson R, Lindsay PE, Ansell S, Wilson G, Jelveh S, Hill RP, et al. Characterization of image quality and image-guidance performance of a preclinical microirradiator. Med Phys [Internet]. 2011;38(2):845–56. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3188651&tool=pmcentrez&rendertype=abstract

    Article  CAS  Google Scholar 

  16. Baumann BC, Benci JL, Santoiemma PP, Chandrasekaran S, Hollander AB, Kao GD, et al. An integrated method for reproducible and accurate image-guided stereotactic cranial irradiation of brain tumors using the small animal radiation research platform. Transl Oncol [Internet]. 2012;5(4):230–7. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3431032&tool=pmcentrez&rendertype=abstract.

  17. James ML, Gambhir SS. A molecular imaging primer: modalities, imaging agents, and applications. Physiol Rev. 2012;92(2):897–965.

    Article  CAS  Google Scholar 

  18. Cunha L, Horvath I, Ferreira S, Lemos J, Costa P, Vieira D, et al. Preclinical imaging: an essential ally in modern biosciences. Mol Diagn Ther. 2014;18(2):153–73.

    Article  Google Scholar 

  19. Sato A, Klaunberg B, Tolwani R. In vivo bioluminescence imaging BLI: an overview. Comp Med. 2004;54(6):631–4.

    CAS  PubMed  Google Scholar 

  20. Tuli R, Surmak A, Reyes J, Hacker-Prietz A, Armour M, Leubner A, et al. Development of a novel preclinical pancreatic cancer research model: bioluminescence image-guided focal irradiation and tumor monitoring of orthotopic xenografts. Transl Oncol [Internet]. 2012;5(2):77–84. https://doi.org/10.1593/tlo.11316%5Cnpapers2://publication/doi/10.1593/tlo.11316

    Article  Google Scholar 

  21. Tuli R, Armour M, Surmak A, Reyes J, Iordachita I, Patterson M, et al. Accuracy of off-line bioluminescence imaging to localize targets in preclinical radiation research. Radiat Res. 2013;179(4):416–21.

    Article  CAS  Google Scholar 

  22. Weersink RA, Ansell S, Wang A, Wilson G, Shah D, Lindsay PE, et al. Integration of optical imaging with a small animal irradiator. Med Phys [Internet]. 2014;41(10):102701. http://www.ncbi.nlm.nih.gov/pubmed/25281980.

    Article  Google Scholar 

  23. Yang Y, Wang KK-H, Eslami S, Iordachita II, Patterson MS, Wong JW. Systematic calibration of an integrated X-ray and optical tomography system for preclinical radiation research. Med Phys [Internet]. 2015;42:1710–20. http://scitation.aip.org/content/aapm/journal/medphys/42/4/10.1118/1.4914860.

    Article  Google Scholar 

  24. Zhang B, Wang KK-H, Yu J, Eslami S, Tran PT, Iordachita I, et al. Bioluminescence tomography guided radiation therapy for preclinical research. Radiat Oncol Biol [Internet]. 2016;94(5):1–27. https://doi.org/10.1016/j.ijrobp.2015.11.039.

    Article  Google Scholar 

  25. Dehghani H, Davis SC, Jiang SD, Pogue BW, Paulsen KD, Patterson MS. Spectrally resolved bioluminescence optical tomography. Opt Lett. 2006;31(3):365–7.

    Article  Google Scholar 

  26. Dehghani H, Davis SC, Pogue BW. Spectrally resolved bioluminescence tomography using the reciprocity approach. Med Phys [Internet]. 2008;35(11):4863–71. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2737244&tool=pmcentrez&rendertype=abstract.

  27. He X, Liang J, Wang X, Yu J, Qu X, Wang X, et al. Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method. Opt Express [Internet]. 2010;18(24):24825–41. https://doi.org/10.1364/oe.18.024825

    Article  Google Scholar 

  28. Wooten HO, Green O, Yang M, DeWees T, Kashani R, Olsen J, et al. Quality of intensity modulated radiation therapy treatment plans using a (60)Co magnetic resonance image guidance radiation therapy system. Int J Radiat Oncol Biol Phys [Internet]. 2015;92(4):771–8. http://www.sciencedirect.com/science/article/pii/S0360301615003004.

    Article  Google Scholar 

  29. Wooten HO, Rodriguez V, Green O, Kashani R, Santanam L, Tanderup K, et al. Benchmark IMRT evaluation of a Co-60 MRI-guided radiation therapy system. Radiother Oncol [Internet]. 2015;114(3):402–5. https://doi.org/10.1016/j.radonc.2015.01.015.

    Article  Google Scholar 

  30. Lagendijk JJW, Raaymakers BW, Raaijmakers AJE, Overweg J, Brown KJ, Kerkhof EM, et al. MRI/linac integration. Radiother Oncol. 2008;86(1):25–9.

    Article  Google Scholar 

  31. Schmidt MA, Payne GS. Radiotherapy planning using MRI. Phys Med Biol [Internet]. 2015;60(22):R323–61. http://stacks.iop.org/0031-9155/60/i=22/a=R323?key=crossref.73d6c6caed0c84bc13887e1da0f28de1.

    Article  CAS  Google Scholar 

  32. Bolcaen J, Descamps B, Deblaere K, Boterberg T, Hallaert G, Van den Broecke C, et al. MRI-guided 3D conformal arc micro-irradiation of a F98 glioblastoma rat model using the Small Animal Radiation Research Platform (SARRP). J Neuro-Oncol. 2014;120(2):257–66.

    Article  CAS  Google Scholar 

  33. Bryant MJ, Chuah TL, Luff J, Lavin MF, Walker DG. A novel rat model for glioblastoma multiforme using a bioluminescent F98 cell line. J Clin Neurosci. 2008;15(5):545–51.

    Article  CAS  Google Scholar 

  34. Cherry SR. In vivo molecular and genomic imaging: new challenges for imaging physics. Phys Med Biol. 2004;49(3):R13–48.

    Article  CAS  Google Scholar 

  35. Gutierrez S, Descamps B, Vanhove C. MRI-only based radiotherapy treatment planning for the rat brain on a Small Animal Radiation Research Platform (SARRP). PLoS One [Internet]. 2015;10(12):e0143821. http://dx.plos.org/10.1371/journal.pone.0143821.

    Article  Google Scholar 

  36. Ling CC, Humm J, Larson S, Amols H, Fuks Z, Leibel S, et al. Towards multidimensional radiotherapy (MD-CRT):biological imaging and biological conformality. Int J Radiat Oncol Biol Phys. 2000;47(3):551–60.

    Article  CAS  Google Scholar 

  37. Wahl RL, Jacene H, Kasamon Y, Lodge MA. From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors. J Nucl Med [Internet]. 2009;50 Suppl 1(5):122S–50S. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2755245&tool=pmcentrez&rendertype=abstract.

  38. Lopci E, Grassi I, Chiti A, Nanni C, Cicoria G, Toschi L, et al. PET radiopharmaceuticals for imaging of tumor hypoxia: a review of the evidence. Am J Nucl Med Mol Imaging [Internet]. 2014;4(4):365–84. http://www.ncbi.nlm.nih.gov/pubmed/24982822.

  39. Gregoire V, Chiti A. PET in radiotherapy planning: particularly exquisite test or pending and experimental tool? Radiother Oncol. 2010;96(3):275–6.

    Article  Google Scholar 

  40. Chiti A, Kirienko M, Grégoire V. Clinical use of PET-CT data for radiotherapy planning: what are we looking for? Radiother Oncol [Internet]. 2010;96(3):277–9. https://doi.org/10.1016/j.radonc.2010.07.021

    Article  Google Scholar 

  41. Delikgoz Soykut E, Ozsahin EM, Yukselen Guney Y, Aytac Arslan S, Derinalp Or O, Altundag MB, et al. The use of PET/CT in radiotherapy planning: contribution of deformable registration. Front Oncol [Internet]. 2013;3(April):33. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3624079&tool=pmcentrez&rendertype=abstract.

  42. Schütze C, Bergmann R, Yaromina A, Hessel F, Kotzerke J, Steinbach J, et al. Effect of increase of radiation dose on local control relates to pre-treatment FDG uptake in FaDu tumours in nude mice. Radiother Oncol. 2007;83(3):311–5.

    Article  Google Scholar 

  43. Trani D, Yaromina A, Dubois L, Granzier M, Peeters SGJA, Biemans R, et al. Preclinical assessment of efficacy of radiation dose painting based on intratumoral FDG-PET uptake. Clin Cancer Res [Internet]. 2015;21:5511–9. http://clincancerres.aacrjournals.org/cgi/doi/10.1158/1078-0432.CCR-15-0290.

    Article  CAS  Google Scholar 

  44. España S, Marcinkowski R, Keereman V, Vandenberghe S, Van Holen R. DigiPET: sub-millimeter spatial resolution small-animal PET imaging using thin monolithic scintillators. Phys Med Biol [Internet]. 2014;59(13):3405. http://stacks.iop.org/0031-9155/59/i=13/a=3405.

    Article  Google Scholar 

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Correspondence to Christian Vanhove .

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Vanhove, C., Vandenberghe, S. (2019). Multimodality Imaging in Small Animal Radiotherapy. In: Kuntner-Hannes, C., Haemisch, Y. (eds) Image Fusion in Preclinical Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-02973-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-02973-9_10

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