Abstract
A commercial three-dimensional (3D) inverse treatment planning system, Corvus
(Nomos Corporation, Sewickley, PA), was recently made available. This paper reports our preliminary results and experience with commissioning this system for clinical implementation. This system uses a simulated annealing inverse planning algorithm to calculate intensity-modulated fields. The intensity-modulated fields are divided into beam profiles that can be delivered by means of a sequence of leaf settings by a multileaf collimator (MLC). The treatments are delivered using a computer-controlled MLC. To test the dose calculation algorithm used by the Corvus software, the dose distributions for single rectangularly shaped fields were compared with water phantom scan data. The dose distributions predicted to be delivered by multiple fields were measured using an ion chamber that could be positioned in a rotatable cylindrical water phantom. Integrated charge collected by the ion chamber was used to check the absolute dose of single- and multifield intensity modulated treatments at various spatial points. The measured and predicted doses were found to agree to within 4% at all measurement points. Another set of measurements used a cubic polystyrene phantom with radiographic film to record the radiation dose distribution. The films were calibrated and scanned to yield two-dimensional isodose distributions. Finally, a beam imaging system (BIS) was used to measure the intensity-modulated x-ray beam patterns in the beam's-eye view. The BIS-measured images were then compared with a theoretical calculation based on the MLC leaf sequence files to verify that the treatment would be executed accurately and without machine faults. Excellent correlation (correlation coefficients 
) was found for all cases. Treatment plans generated using intensity-modulated beams appear to be suitable for treatment of irregularly shaped tumours adjacent to critical structures. The results indicated that the system has potential for clinical radiation treatment planning and delivery and may in the future reduce treatment complexity.