Comparison of 3 image-guided adaptive strategies for bladder locoregional radiotherapy

The objective of this study was to compare the dosimetric differences of a population-based planning target volume (PTV) approach and 3 proposed adaptive strategies: plan of the day (POD), patient-specific PTV (PS-PTV), and daily reoptimization (ReOpt). Bladder patients (n = 10) were planned and treated to 46 Gy in 23 fractions with a full bladder in supine position by the standard strategy using a population-based PTV. For each patient, the adaptive strategy was executed retrospectively as follows: (1) POD-multiple distributions of various PTV sizes were generated, and the appropriate distribution based on the bladder of the day was selected for each fraction; (2) PS-PTV-population-based PTV was used for the first 5 fractions and a new PTV derived using information from these fractions was used to deliver the remaining 18 fractions; and (3) ReOpt-distribution was reoptimized for each fraction based on the bladder of the day. Daily dose was computed on all cone beam computed tomographies (CBCTs) and deformed back to the planning computed tomography (CT) for dose summation afterward. V_{95_Accu}, the volume receiving an accumulated delivered dose of 43.7 Gy (95% prescription dose), was measured for comparison. Mean V_{95_Accu} (cm³) values were 1410 (standard deviation [SD]: 227), 1212 (SD: 186), 1236 (SD: 199), and 1101 (SD: 180) for standard, POD, PS-PTV, and ReOpt, respectively. All adaptive strategies significantly reduced the irradiated volume, with ReOpt demonstrating the greatest reduction compared with the standard (- 25%), followed by PS-PTV (- 16%) and POD (- 12%). The difference in the magnitude of reduction between ReOpt and the other 2 strategies reached statistical significance (p = 0.0006). ReOpt is the best adaptive strategy at reducing the irradiated volume because of its frequent adaptation based on the daily geometry of the bladder. The need to adapt only once renders PS-PTV to be the best alternative adaptive strategy.