An efficient dose calculation strategy for intensity modulated proton therapy

While intensity-modulated proton therapy (IMPT) has great potential to improve the therapeutic efficacy of radiotherapy, IMPT optimization can be computationally demanding, particularly for large and complex tumors. Here we propose a dose calculation strategy to accelerate IMPT optimization while reducing memory requirements. By using two adjustable threshold parameters, our method separates dose contributions from proton beamlets into major and minor components for each dose voxel. The optimization proceeds with two levels of iterations: in inner iterations, doses are updated in correspondence with changes in beamlet intensities from only the major contributions while keeping the portions from the minor contributions constant; in outer iterations, doses are recalculated exactly by considering both major and minor contributions. Since the number of elements in the influence matrix for major contributions is relatively small, each inner iteration proceeds quickly. Each outer iteration requires a longer computation time, but only a few such iterations are needed. Our study shows that the proposed strategy leads to nearly identical dose distributions as those optimized with the full influence matrix, but reducing computing time by at least a factor of 3 and internal memory requirements by a factor of 10 or more. In addition, we show that the proposed approach could enhance other optimization-related applications such as optimizing beam angles. By using an advanced lung cancer case that would demand large computing resources by conventional optimization approach, we show how our method may potentially help improve IMPT treatment planning in real clinical situations.