Modulated photon radiotherapy (XMRT): An algorithm for the simultaneous optimization of photon beamlet energy and intensity in external beam radiotherapy (EBRT) planning

This is a proof of principle study on an algorithm for optimizing external beam radiotherapy in terms of both photon beamlet energy and fluence. This simultaneous beamlet energy and fluence optimization is denoted modulated photon radiotherapy (XMRT). XMRT is compared with single-energy intensity modulated radiotherapy (IMRT) for five clinically relevant test geometries to determine whether treating beamlet energy as a decision variable improves the dose distributions. All test geometries were modelled in a cylindrical water phantom. XMRT optimized the fluence for 6 and 18 MV beamlets while IMRT optimized with only 6 MV and only 18 MV. CERR (computational environment for radiotherapy research) was used to calculate the dose deposition matrices and the resulting dose for XMRT and IMRT solutions. Solutions were compared via their dose volume histograms and dose metrics, such as the mean, maximum, and minimum doses for each structure. The homogeneity index (HI) and conformity number (CN) were calculated to assess the quality of the target dose coverage. Complexity of the resulting fluence maps was minimized using the sum of positive gradients technique. The results showed XMRT's ability to improve healthy-organ dose reduction while yielding comparable coverage of the target relative to IMRT for all geometries. All three energy-optimization approaches yielded similar HI and CNs for all geometries, as well as a similar degree of fluence map complexity. The dose reduction provided by XMRT was demonstrated by the relative decrease in the dose metrics for the majority of the organs at risk (OARs) in all geometries. Largest reductions ranged between 5% to 10% in the mean dose to OARs for two of the geometries when compared with both single-energy IMRT schemes. XMRT has shown potential dosimetric benefits through improved OAR sparing by allowing beam energy to act as a degree of freedom in the EBRT optimization process.