Adapting IMRT delivery fraction-by-fraction to cater for variable intrafraction motion.
This paper presents a technique for coping with variable intrafraction organ motion when delivering intensity-modulated radiation therapy (IMRT). The strategy is an adaptive delivery in which the fluence delivered up to a particular fraction is subtracted from the required total-course planned fluence to create an adapted residual fluence for the next fraction. This requires that the fluence already delivered can be computed, knowing the intrafraction motion during each fraction. If the adaptation is unconstrained, as would be required for perfect delivery of the planned fluence, then the individual fractional fluences would become unphysical, with both negative components and spikes. Hence it is argued that constraints must be applied; first, positivity constraints and second, constraints to limit fluence spikes. Additionally, it is shown to be helpful to constrain other quantities which are explained. The power of the strategy is that it adapts to the (potentially variable) moving geometry during each fraction. It is not a perfect delivery but it is always better than making no adaptation. The fractionated nature of radiation therapy is thus exploited to advantage. The fluence adaptation method does not require re-planning at each fraction but this imposes limitations which are stated. The fuller theory of dose adaptation is also developed for intrafraction motion. The method is complementary to other adaptive strategies recently discussed with respect to interfraction motion.
Webb
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Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT, UK.
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D006801:Humans; D008962:Models, Theoretical; D009038:Motion; D009369:Neoplasms / Q000532:radiotherapy; D011880:Radiotherapy Planning, Computer-Assisted; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods* / Q000706:statistics & numerical data