Development and clinical application of a fast superposition algorithm in radiation therapy.
OBJECTIVE
Dose calculation algorithms play a central role for the optimization and verification of treatment plans in radiation therapy. Complex treatment techniques like intensity modulated radiotherapy (IMRT) require accurate and fast dose algorithms especially for clinical cases which involve severe tissue inhomogeneities. For these cases the standard dose engine in current treatment planning systems--the convolution of photon pencil beams--usually fails to predict the dose with the required accuracy. The role of more accurate but time consuming dose calculations like superposition algorithms or Monte Carlo simulations in clinical practice is under investigation at several therapy centers.


METHODS
The paper presents the design, implementation and the first application of a superposition algorithm in a clinical setting at the German Cancer Research Center (DKFZ). It first describes in detail how the superposition algorithm is adapted to the dose delivery system at DKFZ in terms of standard dosimetric data. Then details of the implementation of the algorithm are given with a focus on various methods for the reduction of dose computation times. Next, the algorithm is evaluated in various experiments with dosimetric phantoms. These studies are employed for the development of time efficient sampling strategies of the elemental dose kernels. Finally, the algorithm is applied to dose calculations of clinical cases with tumors adjacent to lung tissue.


RESULTS
Severe differences in dose coverage of the tumors and dose burden of the surrounding tissues in comparison to standard pencil beam calculations are observed. A standard 4-7 beam plan in a convenient dose grid (approximately 3 mm in each direction) is calculated in about 30 min on a Pentium 4 (1.9 GHz) applying the superposition algorithm described here.
German Cancer Research Center (DKFZ), Department of Medial Physics, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. c.scholz@dkfz.de
Christian
C
Scholz
Carsten
C
Schulze
Uwe
U
Oelfke
Thomas
T
Bortfeld
D000465:Algorithms; D006801:Humans; D008175:Lung Neoplasms / Q000532:radiotherapy; D008654:Mesothelioma / Q000532:radiotherapy; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D010997:Pleural Neoplasms / Q000532:radiotherapy; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*