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Quantitative Bioluminescence Tomography for In Vivo Volumetric-Guided Radiotherapy

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Biomedical Engineering Technologies

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2393))

Abstract

Several groups, including ours, have initiated efforts to develop small-animal irradiators that mimic radiation therapy (RT) for human treatment. The major image modality used to guide irradiation is cone-beam computed tomography (CBCT). While CBCT provides excellent guidance capability, it is less adept at localizing soft tissue targets growing in a low image contrast environment. In contrast, bioluminescence imaging (BLI) provides strong image contrast and thus is an attractive solution for soft tissue targeting. However, commonly used 2D BLI on an animal surface is inadequate to guide irradiation, because optical transport from an internal bioluminescent tumor is highly susceptible to the effects of optical path length and tissue absorption and scattering. Recognition of these limitations led us to integrate 3D bioluminescence tomography (BLT) with the small animal radiation research platform (SARRP). In this chapter, we introduce quantitative BLT (QBLT) with the advanced capabilities of quantifying tumor volume for irradiation guidance. The detail of system components, calibration protocol, and step-by-step procedure to conduct the QBLT-guided irradiation are described.

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Acknowledgements

The authors would like to thank the funding support from CPRIT RR200042, NIH-NCI (R21CA223403, R37CA230341, R01CA240811, and P30CA006973), and Xstrahl Inc.

Author information

Authors and Affiliations

  1. Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA

    Zijian Deng, Xiangkun Xu, Daniel M. Sforza, John W. Wong & Ken Kang-Hsin Wang

  2. Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Zijian Deng, Xiangkun Xu & Ken Kang-Hsin Wang

  3. School of Computer Science, University of Birmingham, Birmingham, UK

    Hamid Dehghani

  4. Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD, USA

    Iulian Iordachita

  5. Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA

    Michael Lim

  6. Department of Neurosurgery, Stanford University, Stanford, CA, USA

    Michael Lim

Authors
  1. Zijian Deng
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  2. Xiangkun Xu
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  3. Hamid Dehghani
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  4. Daniel M. Sforza
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  5. Iulian Iordachita
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  6. Michael Lim
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  7. John W. Wong
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  8. Ken Kang-Hsin Wang
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Corresponding author

Correspondence to Ken Kang-Hsin Wang .

Editor information

Editors and Affiliations

  1. Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA

    Miguel R. Ossandon

  2. Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA

    Houston Baker

  3. Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA

    Avraham Rasooly

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Deng, Z. et al. (2022). Quantitative Bioluminescence Tomography for In Vivo Volumetric-Guided Radiotherapy. In: Ossandon, M.R., Baker, H., Rasooly, A. (eds) Biomedical Engineering Technologies. Methods in Molecular Biology, vol 2393. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1803-5_38

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  • DOI: https://doi.org/10.1007/978-1-0716-1803-5_38

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1802-8

  • Online ISBN: 978-1-0716-1803-5

  • eBook Packages: Springer Protocols

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