IMRT planning on adaptive volume structures—a decisive reduction in computational complexity

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Abstract
The objective of radiotherapy planning is to find a compromise between the contradictive goals of delivering a sufficiently high dose to the target volume while widely sparing critical structures. The search for such a compromise requires the computation of several plans, which mathematically means solving several optimization problems. In the case of intensity modulated radiotherapy (IMRT) these problems are large-scale, hence the accumulated computational expense is very high. The adaptive clustering method presented in this paper overcomes this difficulty. The main idea is to use a preprocessed hierarchy of aggregated dose-volume information as a basis for individually adapted approximations of the original optimization problems. This leads to a decisively reduced computational expense: numerical experiments on several sets of real clinical data typically show computation times decreased by a factor of about 10. In contrast to earlier work in this field, this reduction in computational complexity will not lead to a loss in accuracy: the adaptive clustering method produces the optimum of the original optimization problem.