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Functional lung imaging in radiation therapy for lung cancer: A systematic review and meta-analysis

  • Nicholas W. Bucknell
    Correspondence
    Corresponding author at: Department of Radiation Oncology, Peter MacCallum Cancer Center, 302 Grattan St, 3002 Melbourne, Victoria, Australia.
    Affiliations
    Department of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne, Australia

    Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia
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  • Nicholas Hardcastle
    Affiliations
    Department of Physical Sciences, Peter MacCallum Cancer Center, Melbourne, Australia

    Center for Medical Radiation Physics, University of Wollongong, Australia
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  • Author Footnotes
    1 Author responsible for statistical analysis.
    Mathias Bressel
    Footnotes
    1 Author responsible for statistical analysis.
    Affiliations
    Department of Biostatistics and Clinical Trials, Peter MacCallum Cancer Center, Melbourne, Australia
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  • Michael S. Hofman
    Affiliations
    Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia

    Center for Molecular Imaging, Cancer Imaging, Peter MacCallum Cancer Center, Melbourne, Australia
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  • Tomas Kron
    Affiliations
    Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia

    Department of Physical Sciences, Peter MacCallum Cancer Center, Melbourne, Australia
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  • David Ball
    Affiliations
    Department of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne, Australia

    Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia
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  • Shankar Siva
    Affiliations
    Department of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne, Australia

    Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia
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  • Author Footnotes
    1 Author responsible for statistical analysis.

      Abstract

      Rationale

      Advanced imaging techniques allow functional information to be derived and integrated into treatment planning.

      Methods

      A systematic review was conducted with the primary objective to evaluate the ability of functional lung imaging to predict risk of radiation pneumonitis. Secondary objectives were to evaluate dose–response relationships on post treatment functional imaging and assess the utility in including functional lung information into treatment planning. A structured search for publications was performed following PRISMA guidelines and registered on PROSPERO.

      Results

      814 articles were screened against review criteria and 114 publications met criteria. Methods of identifying functional lung included using CT, MRI, SPECT and PET to image ventilation or perfusion. Six studies compared differences between functional and anatomical lung imaging at predicting radiation pneumonitis. These found higher predictive values using functional lung imaging. Twenty-one studies identified a dose–response relationship on post-treatment functional lung imaging. Nineteen planning studies demonstrated the ability of functional lung optimised planning techniques to spare regions of functional lung. Meta-analysis of these studies found that mean (95% CI) functional volume receiving 20 Gy was reduced by 4.2% [95% CI: 2.3: 6.0] and mean lung dose by 2.2 Gy [95% CI: 1.2: 3.3] when plans were optimised to spare functional lung. There was significant variation between publications in the definition of functional lung.

      Conclusion

      Functional lung imaging may have potential utility in radiation therapy planning and delivery, although significant heterogeneity was identified in approaches and reporting. Recommendations have been made based on the available evidence for future functional lung trials.

      Keywords

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