Poster - 52: Smoothing constraints in Modulated Photon Radiotherapy (XMRT) fluence map optimization

Authors

  • McGeachy Philip,

    1. Department of Medical Physics, CancerCare Manitoba, Winnipeg, MB, CAN, Department of Physics and Astronomy, University of Calgary, Calgary, AB, CAN, Department of Mathematics and Statistics, University of Calgary, Calgary, AB, CAN, Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO, USA
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  • Villarreal-Barajas Jose Eduardo,

    1. Department of Medical Physics, CancerCare Manitoba, Winnipeg, MB, CAN, Department of Physics and Astronomy, University of Calgary, Calgary, AB, CAN, Department of Mathematics and Statistics, University of Calgary, Calgary, AB, CAN, Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO, USA
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  • Zinchenko Yuriy,

    1. Department of Medical Physics, CancerCare Manitoba, Winnipeg, MB, CAN, Department of Physics and Astronomy, University of Calgary, Calgary, AB, CAN, Department of Mathematics and Statistics, University of Calgary, Calgary, AB, CAN, Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO, USA
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  • Khan Rao

    1. Department of Medical Physics, CancerCare Manitoba, Winnipeg, MB, CAN, Department of Physics and Astronomy, University of Calgary, Calgary, AB, CAN, Department of Mathematics and Statistics, University of Calgary, Calgary, AB, CAN, Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO, USA
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Abstract

Purpose:

Modulated Photon Radiotherapy (XMRT), which simultaneously optimizes photon beamlet energy (6 and 18 MV) and fluence, has recently shown dosimetric improvement in comparison to conventional IMRT. That said, the degree of smoothness of resulting fluence maps (FMs) has yet to be investigated and could impact the deliverability of XMRT. This study looks at investigating FM smoothness and imposing smoothing constraint in the fluence map optimization.

Methods:

Smoothing constraints were modeled in the XMRT algorithm with the sum of positive gradient (SPG) technique. XMRT solutions, with and without SPG constraints, were generated for a clinical prostate scan using standard dosimetric prescriptions, constraints, and a seven coplanar beam arrangement. The smoothness, with and without SPG constraints, was assessed by looking at the absolute and relative maximum SPG scores for each fluence map. Dose volume histograms were utilized when evaluating impact on the dose distribution.

Results:

Imposing SPG constraints reduced the absolute and relative maximum SPG values by factors of up to 5 and 2, respectively, when compared with their non-SPG constrained counterparts. This leads to a more seamless conversion of FMS to their respective MLC sequences. This improved smoothness resulted in an increase to organ at risk (OAR) dose, however the increase is not clinically significant.

Conclusions:

For a clinical prostate case, there was a noticeable improvement in the smoothness of the XMRT FMs when SPG constraints were applied with a minor increase in dose to OARs. This increase in OAR dose is not clinically meaningful.

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