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Karl-Heinz Küfer

Publications and source records attributed to Karl-Heinz Küfer.

2 recordsLinked to original sources

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

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.

Algorithms↗

Characterization of dose distributions through the max and mean dose concept.

A new approach for the determination of the equivalent uniform dose (EUD) for inhomogeneously irradiated normal organs is developed and tested. The EUD is calculated as a linear combination of the maximum and the mean dose: EUD = alphaDmax + (1 - alpha)D. We call this the max & mean model. The values of alpha are determined by a fit to the Emami tables for complication levels of 5% and 50%. The predictions of the max & mean model are compared with the Emami tables for different treatment volume fractions. The quality of the fit is also compared with the well-known power-law EUD model. The max & mean model makes it possible to make useful predictions of the EUD for organs having an organization anywhere between serial and parallel. The model can be fitted to the Emami tables within the same error range as the widely used power-law model (about 10%) and can be integrated into linear multicriteria optimization algorithms for planning of intensity-modulated radiotherapy.

Dose Fractionation, Radiation↗