Ryerson collaboration yields innovative algorithm for the use of mixed photon energy beams in volumetric modulated arc therapy
Left to Right: Collaborators Shadab Momin (Department of Physics, Ryerson University and Department of Radiation Oncology, Washington University School of Medicine), James Gräfe (Department of Physics, Ryerson University), Konstantinos Georgiou (Department of Mathematics, Ryerson University), and Rao Khan (Department of Radiation Oncology, Washington University School of Medicine)
A team of researchers from Ryerson University, Toronto, and Washington University School of Medicine, St. Louis, Missouri, has devised a novel algorithm for simultaneous optimization of mixed photon beams for volumetric modulated arc therapy (MP-VMAT), potentially offering a significant improvement in cancer treatment over current options.
VMAT is a state-of-the-art external beam radiation therapy treatment used routinely in cancer clinics to treat prostate, head and neck tumours, as well as others. Unlike intensity-modulated radiation therapy (IMRT), VMAT’s photon beams of varying intensities are rotated 360 degrees around the patient for one or more arcs. Compared to IMRT, its precision and speed allow for a shorter treatment time (typically under two minutes) and reduction in the amount of healthy tissue affected.
However, optimization of this relatively new form of radiation therapy is currently limited to a single photon beam. Better targeted tumour treatment with further reduced damage to surrounding organs at risk could be achieved through simultaneous optimization of mixed photon beams, for which there is no present option. A solution to this problem has been offered by an interdisciplinary and international research team, whose results are available in an article titled “Simultaneous optimization of mixed photon energy beams in volumetric modulated arc therapy” published in the journal Medical Physics.
The novel dual-energy algorithm devised by Biomedical Physics graduate student Shadab Momin (Department of Physics, Ryerson University and Department of Radiation Oncology, Washington University School of Medicine), Drs. James Gräfe (Department of Physics, Ryerson University), Konstantinos Georgiou (Department of Mathematics, Ryerson University), and Rao Khan (Department of Radiation Oncology, Washington University School of Medicine) was modelled for two prostate cases. Results showed that mixed photon beams for VMAT (MP-VMAT) were able to achieve substantial dose reduction in surrounding rectum and bladder tissue while yielding a similar target coverage compared to single-energy VMAT.
Dose comparison between proposed approach (MP-VMAT) and conventional approach (SE-VMAT) with a region to be treated (target region = prostate) and two surrounding healthy organs at risk (rectum and bladder). Superior sparing of two healthy organs at risk by MP-VMAT can be seen by comparison of the radiation dose (in form of colors) to each structure by each technique.
MP-VMAT is a two-step comprehensive approach that first determines the optimal dose through simultaneous optimization of dual-energy intensity maps and subsequently optimizes intensity apertures for a complete 360-degree arc rotation.
“Using more than one energy simultaneously in an optimization algorithm increases the solution search space to improve the treatment outcome by better protecting surrounding organs at risk,” explains lead author Shadab Momin. “Before our study, mixed-energy VMAT required optimization of each energy individually with a manually pre-determined dose contribution, which can be a time-consuming trial-and-error process.”
The research team’s algorithm overcomes this limitation by utilizing an additional photon energy as an extra degree of freedom. It decides how much contribution should be given to each energy in the place of manual decision making in order to best meet the dose prescription.
“The overall results of this study show both the feasibility and benefits of implementing simultaneous optimization of mixed photon energy beams in VMAT treatment planning,” says Gräfe. “This novel approach has the potential to produce better quality radiation therapy plans, which could lead to better treatment options. It also has potential applications for many types of cancer, especially those with deep-seated tumours surrounded by other organs.
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