Monte Carlo simulations of prostate implants to improve dosimetry and compare planning methods.
The objective of this study is to use Monte Carlo simulations to assess the sensitivity of implant planning methods to seed misplacement. A model of seed misplacement is first developed. It is based upon data gathered after a study on source migration performed on 30 patients treated with I-125 transperineal implants. It consists of applying elementary transformations to every needle in a loading plan to produce a distorted implant mimicking the effect of migration. After being validated, the model has been used to tune the inverse planning system in use at our institution. The new planning system is now used clinically and actual results are compared with those predicted by simulations. Simulations were also used to compare our planning method with others. The new planning system increased the average postimplant dose-volume histogram DVH(160) from 82% to 93%, which is the value predicted by the simulations. This improvement is due to an increased dose margin providing coverage even in the presence of migration. At the same time, the dose to the urethra remained at 267 Gy because of a special protection feature included in the planning system. Some other implant planning methods are not as robust [average DVH(160) ranging from 76% to 85%] and deliver a higher dose to the urethra (close to 400 Gy). To conclude, a simple model of source migration can provide realistic feedback about sensitivity to migration of planning methods. It allowed a significant clinical improvement at our institution. The improved inverse planning system provided better coverage with fewer seeds (but equal total activity) than a manual method. Hence, a properly tuned inverse planning system has the potential to deliver the less sensitive plans. The model also helped demonstrate that planning methods are not equally robust to migration and that they should not be evaluated solely by the plans they produce, but also by their clinical (or simulated) results.
Taschereau
R
R
Radiation Oncology Service, Centre de Recherche en Cancérologie de l'Université Laval, Canada. rtascher@phy.ulaval.ca
Roy
J
J
Pouliot
J
J
D055592:Biophysical Phenomena; D001703:Biophysics; D001918:Brachytherapy / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data; D003198:Computer Simulation; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011786:Quality Control; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data; D015203:Reproducibility of Results