title: The impact of different leaf limited accelerations on leaf-positional error of a self-developed MLC prototype.
abstract: Multi-leaf collimator (MLC) provides an available approach to achieve sophisticated radiotherapy techniques and plays an important role in advanced high quality radiation therapy. Delivery accuracy of radiation therapy mainly depends on the leaf sequence generated by treatment plans and dynamic performance of MLCs. Previous studies have explored the influence of various leaf limited velocities and dose rates on the leaf-positional error. However, there is a lack of research on the influence of different leaf limited accelerations on the delivery accuracy or leaf-positional error. Confining our study to the technique of sliding window, we investigate the effect of various leaf limited accelerations in treatment plans on leaf-positional error of a self-developed MLC prototype. In order to preliminarily verify the assumption, experiments of leaf trajectories sequenced with different limited accelerations under the same displacement were performed. Thereafter, according to the principle of the sliding window technique and the prescribed intensity profile, leaf trajectories for different leaf limited accelerations from 1.0 m/s2 to 5.0 m/s2 were calculated. Conducted on the self-developed MLC prototype, the experiment results have shown that the maximum leaf-positional error can be kept within 0.5 mm while the average and RMS of the leaf-positional error vary from leaf limited accelerations. Under the proposal leaf limited acceleration of 3 m/s2, the self-developed MLC achieved the optimal dynamic performance. In conclusion, for commercial MLCs, optimal constraint for treatment plans should be investigated and determined because incorporation of reasonable servo-mechanical constraints into leaf sequencing algorithm can enhance the conformity between planned and delivered fields.
authors.lastname: Xiang Zhang
authors.lastname: Peiqing Ye
authors.lastname: Hui Zhang
mesh_terms: D000054:Acceleration; D000465:Algorithms; D006801:Humans; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*