Class Solution for Prostate High Dose Rate Brachytherapy with Inverse Planning Simulated Annealing
N Sheth*, N Mistry, Y Chen, C Yang, Monmouth Medical Center, Long Branch, NJSU-E-T-428 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit Hall
Purpose: To develop and validate a class solution for inverse planning simulated annealing (IPSA) with CT based prostate high dose rate brachytherapy (HDR).
Methods: Between November 2008 and November 2011, our institution treated 40 prostate cancer patients with HDR in 7 Gy fractions followed by external beam radiotherapy. The HDR treatments were planned with Nucletron Oncentra using manual graphical optimization (GO). Plans were optimized to the following clinical goals: = 95% of prostate volume received 7 Gy, < 1 cc of rectum received 5.6 Gy, < 0.1 cc of rectum received 6.3 Gy, and < 0.01 cc of urethra received 8.75 Gy. New plans were manually customized using IPSA (MC-IPSA) for each patient to match prostate coverage by the prescription dose to within ± 1% of the GO plans while meeting the rectal and urethral dose constraints. An IPSA class solution (CS-IPSA) was created from the mean MC-IPSA parameters. New plans were developed for each of these 40 patients using only CS-IPSA with no further optimization. Additionally, plans were created on an independent dataset of 30 different patients using only CS-IPSA with no further optimization.
Results: Plans were optimized in about 30 minutes using GO, MC-IPSA took an average of 14.1 ± 6.5 minutes, and CS-IPSA optimization was < 1 minute. There was no significant difference (p > 0.05) among the optimization methods for all clinical goals over the 40 CS-IPSA source patients. There was no significant difference (p > 0.05) between the source and the independent datasets for all clinical goals when using CS-IPSA with no further optimization.
Conclusion: A prostate HDR IPSA class solution was developed and validated on a source and an independent dataset. The IPSA class solution yields plans comparable to custom manual IPSA and graphical optimization while saving considerable time.