Purpose: In contrast to computer optimized three-dimensional (3D) treatment planning, we have used maximally separated, noncoplanar beams as the starting point for 3D treatment planning of prostate cancer to maximize the rate of dose fall off from the target volume and minimize dose to surrounding tissues.
Materials and methods: A planar four-field plan, a planar six-field plan, a tetrad plan, and a hexad plan are analyzed using a 3D treatment planning system which is capable of displaying real-time 3D dose distributions within volume reconstructed data sets (VISTAnet--an extension of the virtual simulator). The tetrad plan is based on the methane molecule and the hexad plan has a minimum separation of 58 degrees on beam entrance. All fields are conformal. The irradiated volume equals the clinical target volume plus a 1 cm margin. Competing plans are compared using cumulative dose-volume histograms and normal tissue complication probabilities.
Results: The crossover point, the isodose surface that conforms more to the beams than the target, is introduced and described. The hexad and tetrad plans result in tighter dose distributions when compared to the planar plans with the same number of beams. The tetrad plan treats a volume less than or equal to the planar six-field plan at isodose surfaces above 18% except between 37% and 44% where the tetrad volume is slightly larger. As expected from integral dose considerations, the amount of normal tissue receiving some radiation increases, but the amount receiving clinically significant amounts of radiation decreases as the number of beams increase. The plan involving the largest number of noncoplanar beams results in the tightest isodose distribution. Analysis of rectal and bladder cumulative dose volume histograms does not reveal a clearly superior plan based on normal tissue complication probabilities.
Conclusions: Using basic principles of solid geometry, maximally separated beams without significant overlap on exit or entrance can be designed which minimize clinically significant dose to surrounding tissues and tighten the isodose distribution around the target volume. The emphasis of this treatment plan optimization is geometric in contrast to methods using computer optimization or artificial intelligence.