Urethra-sparing stereotactic body radiotherapy for prostate cancer: how much can the rectal wall dose be reduced with or without an endorectal balloon?

BACKGROUND

This is a dosimetric comparative study intended to establish appropriate low-to-intermediate dose-constraints for the rectal wall (R) in the context of a randomized phase-II trial on urethra-sparing stereotactic body radiotherapy (SBRT) for prostate cancer. The effect of plan optimization on low-to-intermediate R dose and the potential benefit of an endorectal balloon (ERB) are investigated.

METHODS

Ten prostate cancer patients, simulated with and without an ERB, were planned to receive 36.25Gy (7.25Gyx5) to the planning treatment volume (PTV) and 32.5Gy to the urethral planning risk volume (uPRV). Reference plans with and without the ERB, optimized with respect to PTV and uPRV coverage objectives and the organs at risk dose constraints, were further optimized using a standardized stepwise approach to push down dose constraints to the R in the low to intermediate range in five sequential steps to obtain paired plans with and without ERB (Vm to Vm). Homogeneity index for the PTV and the uPRV, and the Dice similarity coefficient (DSC) for the PTV were analyzed. Dosimetric parameters for R including the median dose and the dose received by 10 to 60% of the R, bladder wall (B) and femoral heads (F) were compared. The monitor units (MU) per plan were recorded.

RESULTS

Vm reduced by half D, D, D and D for R and decreased by a third D while HI, HI and DSC remained stable with and without ERB compared to Vm. HI worsened at Vm both with and without ERB. No statistical differences were observed between paired plans on R, B except a higher D for F with and without an ERB.

CONCLUSIONS

Further optimization to the R in the context of urethra sparing prostate SBRT is feasible without compromising the dose homogeneity to the target. Independent of the use or not of an ERB, low-to-intermediate doses to the R can be significantly reduced using a four-step sequential optimization approach.